I intentionally wrote this piece not as a technical primer but rather as a blog post of my experience going through the DeAI rabbithole.

The purpose of this article is to share the "wow moments" from my research and discuss the framework on how I view this vertical. There's still a ton I have to learn and I am by no means an expert on this topic.

A few notes before we get started:

• There are a ton of resources I've come across and have included them at the bottom of this post.

• If you want to skip my personal journey into DeAI and get into the meat of the content, go to section #3 (Crypto x AI's 4 Horesemen).

• I'm not an investor nor do I have sponsorship contracts with any of the companies mentioned below.

• Lastly, a huge thanks to Sam, Daniel, Karthik, and Kevin for helping me flush out these ideas.

Sections Below

1. Acquiring fresh talent through hype cycles

2. 6 months in 6 paragraphs

3. Crypto x AI's 4 Horsemen

4. Flashback to the '90s: Enterprise vs Consumer

5. Tennessee and Texas are only so big

6. Enabling creativity through society-of-minds

7. What to keep an eye out for in 2025

8. Curated set of resources by topic

Let's dive in.

Acquiring fresh talent through hype cycles

Vaporware. Bullshit projects. Everything's going to zero. Oh god, people who are talking about this meta have like three brain cells.

Anyone on crypto twitter probably saw these kinds of takes dominate their timelines in the past six months as the agent meta was in full swing.

The reality is that all of the statements above are actually spot on. Most projects and ideas we saw were all fluff...quickly spun up in the excitement of the moment, hoping to grab a sliver of the market cap from a shiny new asset class.

Today, Zerebro is down ~90%. AIXBT was literally moving marketcaps in minutes but now comes off as obnoxious and annoying. Many people round tripped generational wealth. The actual AI researchers probably think crypto people are even stupider and irrelevant.

Again, these things are all true.

But! As with any hype cycle in crypto - or in any industry really - there's a key win that we don't celebrate enough.

The most underrated part about hype cycles is their role in acquiring new talent for a vertical.

Okay...but why does this matter in a post about DeAI? Because I noticed a cohort of researchers and builders who are now spending the majority of their time in the crypto x AI vertical even after markets died down post $TRUMP in January.

It's clear to us that there's something brewing up in this niche ecosystem and it's only a matter of time before others start realizing.

YB

@yb_effect

you have 3-4 months to get up to speed on DeAI and find your alpha

57

11:35 AM • Mar 28, 2025

And this epiphany wouldn't have been possible without the agent meta serving its role as a hook. So for those of you reading right now that have a sour taste in your mouth about what happened in Q4, I hope you keep an open mind to better understand everything that's happening in crypto x AI.

6 months in 6 paragraphs

(yes I know this section is more than 6 paragraphs but it's catchy okay just go with it)

For the first 9 months of this newsletter, I was writing about all kinds of topics in crypto. Prediction markets, zkTLS, stablecoins, Farcaster, and so on.

My knowledge on AI was no better than an average ChatGPT user. And the only thing I knew about DecentralizedAI was that $TAO had a huge run up in early 2024.

It wasn't until September of last year that I even made my first post on crypto x AI. I was inspired after seeing tweets from both Brian Armstrong and Jeremy Allaire.

And then, as everyone knows, a month later Truth Terminal and $GOAT popped off and that marked the start of the agent meta.

I vividly remember, two caramel lattes in at a coffee shop in midtown, finishing the 13 page whitepaper on infinite backrooms and feeling totally hooked. There was a "oh fuck! what the hell did I just read" moment that we all experience every now and then. A moment where you need to drop everything else and go in as deep as you can on the new thing.

And then, the following two months was all hands on deck with anything and everything related to agents.

I wrote several posts covering a variety of sub-topics I noticed: Zerebro as the BAYC of agents, the differences of agent infrastructure on Farcaster, the new cycle of trends for the agent meta, and so on.

But, the post that truly gave me the "click" moment for crypto x AI was What did Marc Andreessen see?

Last week, I noticed myself bouncing around different onchain agent whitepapers.

But something was bothering me. It felt like I was getting sucked into the frothiness of the inevitable copycat launches and half assed roadmaps.

And then, I asked myself...how the fuck did all this Onchain AI craziness even happen?

The research for this post led me down a series of write-ups from the AI world that caught my attention. And I knew for a fact that there was a lot more here than what everyone was talking about on the timeline.

YB

@yb_effect

rn most people are focused only on agents (including me) but only a matter of time before the attention & ideas there hit a local top and focus starts shifting to learn the rest of the stack

25

11:52 AM • Dec 11, 2024

After the holidays, I tried to understand how to better approach this topic. For a hot second, I thought maybe it's not worth it....should I just go back to talking about general onchain strategy?

But then, the Deepseek R1 moment happened and that was the green flag for me to double down.

YB

@yb_effect

my takeaway from learning more about deepseek is that it's time to be extra bullish on @NousResearch and @PrimeIntellect

130

1:51 PM • Jan 29, 2025

The reason I've been loving this crypto x AI vertical is because it's forcing me to go deeper on everything.

But! It's a double edged sword.

It can also feel overwhelming if you haven't been plugged into the AI world the last few years. There's constantly a feeling that you need to catch up on so much in order to understand what's going on. And it doesn't help that the rate of progress is continuously increasing week over week.

So, here's my framework on how to make crypto x AI more approachable at a high level.

Crypto x AI's 4 Horsemen

Since the end of January, I've completely absorbed myself in learning everything related to the 4 buckets below. How AI actually works, the differences between centralized-open source-decentralized AI, filtering through the plethora of projects in DeAI, listening to as many podcasts as I can on current events in AI, going through the history of tech to identify any parallels, and so on.

Crypto x AI's 4 Horsemen...

1. AI technicals & fundamentals

2. Open source AI community

3. Decentralized AI efforts

4. Open source history & philosophy

Note: all the resources mentioned are linked below at the bottom of this post for easy access.

Here are some initial thoughts.

• In terms of AI fundamentals, it's not that hard to catch up. If you take a weekend and watch all 3 of Karpathy's talks and the 3Blue1Brown neural net series, you're already at a point where you can understand a good chunk of the lingo on AI twitter. You're not in the AI trenches by any means, but you'll feel a confidence boost just to get started.

  The AI world (not DeAI) is composed of two parts.

  1. The "SF AI cabal". These folks are the researchers at OpenAI, Anthropic, DeepMind, etc. They've probably been guests on the Dwarkesh podcast and get the most hype when they tweet some new breakthrough.

  2. The "OS AI community". Also insanely cracked but are less so in the spotlight. These are the research oriented people who are in the "Nathan Lambert type" category. Think companies such as EleutherAI, TogetherAI, AI2, Fireworks, HuggingFace, and so on.

• There are a lot of companies in DecentralizedAI. Like seriously, the ecosystem maps are running out of space at this point. I've filtered down the set of companies I want to keep tabs on by focusing on 1) what have they actually shipped and 2) how plugged in are they with the rest of the AI community. Hyperbolic, Nous, and Prime Intellect are great examples here.

• It helps a ton to keep up with all the AI podcasts! I'm not exaggerating, but I think I've been able to learn so much about AI so quickly because I have a podcast playing for a good chunk of the day. If you don't have time to dive deeper, just try listening to these as a start. Don't worry about understanding everything, just focus on keeping up with what the current discourse is.

• I've noticed that pretty much all the cracked people who talk about open source AI always provide a historical backdrop of what has happened in previous computing eras. So, I've been taking extra time to make sure I better understand the parallels to form my thoughts on value flow and the realities of whether open source and DeAI even stand a chance.

YB

@yb_effect

As someone who is young in tech, I’m realizing one of the best things to do is make time to learn the history of technology and map it to current events.

There’s so much alpha in understanding how certain trends from previous computing eras played out from the 1980-2010s.

And

4

9:10 PM • Apr 21, 2025

With that being said, let's go ahead and rewind the clock back to the '90s. My goal with the next section is to provide a brief historical backdrop to set the tone for the rest of the post.

Flashback to the '90s: Enterprise vs Consumer

For a second, pretend there's no such thing as Decentralized AI.

Let's simply focus on closed source vs open source AI. How do things play out?

Enterprise AI

Recently, both Bill Gurley and Satya Nadella came to similar conclusions that it's becoming increasingly clear that enterprise AI is not going to be a winner-take-all market.

This is because previous computing eras have shown us that businesses are smart buyers.

Let's walk through the historical analogy they both refer to and break it down.

Throughout the '90s and especially during the dot com boom, Sun had a stronghold on internet businesses. They provided top of the line servers at a high premium and locked in customers with their vertical stack (SPARC/Solaris).

Naturally, they were one of the companies that crushed it going into the new millenium. Sun was literally responsible for the growth of so many new consumer internet companies of that era.

But throughout the '90s, Linux and its open source counterparts were slowly starting to gain momentum on the side. And after the dot-com crash, the open source LAMP stack (Linux, Apache, MySQL, PHP) was getting to a point where the tech was good enough to use for businesses purposes.

Post 2000-2001, most companies couldn't justify Sun-Oracle when there was the Linux-MySql-x86 alternative that was a fraction of the cost.

Naturally, as more and more of the developer community realized the potential of open source web infra, an increasing number of bugs were squashed and the tooling only got better.

Enterprises eventually switched over and even companies like Sun had to embrace Linux with open arms.

On the point of enterprise customers being smart buyers, it's worth noting that the same thing happened in the cloud wars. Even though AWS had a massive headstart with cloud, there was still room for Azure and GCP to take some of the marketshare.

How does this analogy draw back to AI?

It may be the case that because it's so easy to switch models, companies will start quickly prototyping with a closed source provider such as OpenAI and then switch over to open source.

Why?

Because at scale, they can't justify the closed source costs even if they're only more expensive by a slight margin. Or perhaps the AI product line/feature becomes critical enough to the business where they can't risk the model provider changing up rates or access limits (aka rug pull). Or maybe product leads decide it's time to start differentiating and they need the open weights to fine-tune their models. Or it could even be the possibility that there are some privacy / on-prem mandates from a legal standpoint.

Consumer AI

On the other hand, in terms of consumer AI, there is a realistic scenario where something more akin to search or mobile happens. Just like how Google and Apple were able to lock in consumers by being the de facto product in the everyday lingo.

It wasn't "I'm going to use the internet" but rather "I'm going to google it".

It's always been "download it from the app store".

And similarly, as of the last three years, using AI has become synonymous with "just ChatGPT it".

Blake Robbins

@blakeir

Random thoughts:

saw someone on here mention 'login with chatgpt' the other day, and i can't stop thinking about it.

feels inevitable

302

8:53 PM • Apr 18, 2025

To add on, there's also a new moat on the streets that people are worried about: memory.

To be upfront, I'm still unsure how deep the memory moat is. I need to think more about the portability vs consumer lock-in. But it's clearly one of the biggest advantages on the consumer side...all roads in AI lead to personalization.

With that being said, it's worth noting that there are a lot more well resourced competitors trying to fight for the consumer marketshare. You could argue that ChatGPT is in the lead right now, but to what extent? Remember, Sam and team aren't just competing against new AI startups we've hearing about recently (Anthropic, Deepseek). It's also a battle against social incumbents that have massive distribution and network effects like Google, Meta, and X.

Key Takeaway for DeAI

Ok! Wow! That was a lot and we haven't even started discussing DecentralizedAI.

What was the point of me providing all this context?

If there's one takeaway I want you to remember from this section it's that there is room for more than one kind of AI to exist.

It's not closed source vs open source. It's closed source and open source.

The reason it's important to understand this is because the same logic follows for Decentralized AI. It's hard to believe in DeAI if you think it's closed vs open source vs decentralized.

There's room for all these types of AI infra, tooling, economics, developments, etc. to co-exist.

With this mindset, it becomes a lot more reasonable to accept that if DeAI can attract talent and build unique enough offerings, there is in fact an opportunity for the vertical to thrive.

Now that we've established that, let's jump into the next two sections that cover different layers of AI and how DeAI can fit in. I've organized them as follows:

1. Pre-Training: the massive training sessions you hear about that require tens of thousands of Nvidia H100s. This is the foundation of any model that uses the petabytes of data on the internet and is heavily dependent on compute & capital.

2. Post-Training: the focused polishing loops that steer the model toward specific behaviors or domains after pre-training.

Texas and Tennessee are only so big

On the pre-training side, you can argue there's a spectrum of reasoning of how necessary DeAI is that goes from philosophical to practical to experimental.

Let's go through all three.

Philosophical

Open-source AI isn’t truly open source if a single entity sponsors the GPU bill.

In regards to the section above on the '90s, one key thing to remember about the open source Linux era versus open source in AI is that there's an extra component of upfront capex for hardware that's needed.

Meta spent hundreds of millions of dollars to make Llama3. AI2 receives funding from the Allen Institute. Alibaba uses their enormous treasury to support Qwen.

So why have a decentralized state-of-the-art model? Because at any given moment even open source companies can change their policies or simply stop developing.

It might not even be malicious. These companies could be legally constrained because of geopolitical reasons. Or research institutes like AI2 might get their funding cut off and can’t continue to develop at the rate that’s needed to keep up against their centralized counterparts.

If a business in India depends on the latest versions of Llama to support their customers, and all of a sudden Meta decides that the next Llama is going to be proprietary...what happens to that business? And how is this situation any different than the potential "rug pulls" that we claim closed source companies will do?

There is always a central point of failure for open source models as they stand today: whoever is providing the capital and the jurisdictions of that institution.

So by just the reasoning of a “black swan event” or “the desire to be antifragile”, it’s good to have this decentralized model backup where funding and training isn’t restricted to any one company or country.

At a minimum, we as a global community need a model that is not developed, funded, or owned by any one entity.

Fortunately for us, the world has already proved out a network that coordinates massive amounts of hardware that's globally distributed through a well defined incentive mechanism.

Just as Bitcoin built out infrastructure for truly free money, we need to build out infrastructure for truly free intelligence.

Last thing I want to mention in this section is that there's a real possibility that niche and open source companies can't keep up with the rate of progress closed source companies are going at. And if that's the case, then it's imperative that we at least have a means to get everyone outside of these companies working together on an open, global model.

Practical

Okay, moving on to a part of DeAI where even folks who are working in centralized AI are paying attention to: distributed training research.

The big unlock that slowly formed from 2017 (release of transformers paper) to 2019 (GPT-2 launch) was that it's possible to make these assistants smarter by adding more compute and scaling up the underlying models.

This marked the start of the GPU gold rush and the AI space started shifting to being more closed source as pre-training became the competitive margin. And since ChatGPT launched in 2022, we've seen unfathomable numbers on how much the largest tech companies are spending on data centers (Meta, xAI, Microsoft, Google).

All these big training runs you hear about from the hyperscalers who have billions of dollars to spend are done so with GPUs that are co-located in massive data warehouses.

Now, the key part to understand is that it's not just about who has the most number of GPUs.

Rather, the north star is how well these teams set up their data centers to maximize efficiency. This is known as Total Cluster Efficiency which accounts for GPU failures, continuity of systems, etc.

As the newer models get exponentially larger, these optimizations become crucial.

The reality is that eventually there will be a physical limitation on how big warehouses can get.

Not only that, but there will be a point where hyperscalers realize that the decrease in data center efficiency is not justifying the operational expenses to run these warehouses such as cooling equipment and expensive InfiniBands.

This is where it turns out that the research DeAI folks have been doing is quite useful. In fact, teams such as Prime Intellect and Nous Research have been working closely with the general AI community to make progress.

The core question of this research paradigm is: can we train a state of the art LLM over the internet?

And in order to do that, it really comes down to reducing the communication needs between GPUs.

The Nvidia GPUs in a large central warehouse can talk to each other at speeds of 1800 GB / sec. On the other hand, a normal internet speed is ~500 MB / sec. There's clearly an uphill battle to making distributed training work.

Notice I said distributed, not decentralized. Companies like Google obviously aren't worried about malicious actors / Byzantine Fault Tolerance (BFT).

BUT the hardware optimization solutions help everyone!

Note: don't worry if you don't understand the examples below, it's more so evidence that there's actual progress that has already been made.

Two key developments worth noting are:

1. The Prime Intellect team working with Arthur Douillard from Deep Mind on Open DiLoCo (distributed low communication). Key learning from that paper is inner-outer optimization works, reducing GPU communication needs by 500x.

2. The Nous team working with Diederik Kingma, who invented the AdamW optimizer, on the DeMo (Decouples Momentum Optimizer) paper. I won't get into details here but simply put, it turns out you can compress how gradient optimizers work (a key part of the training process) without harming model performance. This research resulted in an 857x reduction in communication needs.

What these teams are doing is basically questioning the current methods of how models are trained, breaking down the different components, and trying to optimize them in creative ways. Just these first iterations led to drastic reductions. Imagine combining these strategies - all of a sudden, how we think about training looks totally different.

And what's amazing about this research is that if the DeAI teams can in fact build out protocols that allow for anyone to join in with their compute, there's no reason that enterprises won't collaborate if it's more capitally efficient for them. Somewhat similar to how RedHat and IBM stated rolling Linux into their servers because it turns out the open source software could actually run enterprise level apps.

As Jeffery Quesnelle from Nous Research puts it:

Only a handful of data-centre campuses have 20,000+ GPUs under one roof, but there’s a fat middle of facilities with something like 2,000 H100s apiece. The next logical step is to train a single model across a hundred of these 2 K-GPU clusters.

That shift benefits even the “centralized” players first: a cloud provider with multiple sites can simply treat each data-centre as a node in the network, linked by ordinary 100 Gb/s WAN pipes, instead of pouring more money into one giant InfiniBand fabric. They get higher utilization and avoid buying ever-bigger monolithic super-pods.

In other words, the method can be decentralized without requiring a fully permissionless swarm from day one.

Just a few days ago, Jack Clark, who is the co-founder of Anthropic wrote in his blog about Prime Intellect's 32B decentralized model and how these developments can totally shift the political economics of AGI.

It's also worth noting even the team at OpenAI understands that if you want to scale humanity's model on the order of 10 million GPUs, you're going to have to need some form of decentralized pre-training.

Experimental

For the last part of the pre-training spectrum, let's discuss the part of DeAI research that isn't in production yet but is quickly becoming a contender in reshaping everyone's framework on model economics.

And to best understand it, it's worth bringing up protocols we're all familiar with such as Bitcoin, Ethereum, and Farcaster. At their core, each of these systems commoditized the infrastructure for their respective parts of society (money, computing, social).

The reason Bitcoin works is because no one entity or person controls the ledger and can change it to work in their favor. And no one can run away with all the Bitcoin (yes, I know what the 51% role is don't at me).

In order to apply this same concept for intelligence, the main challenge at hand is create a model that no one entity owns and can run away with. Or more practically put, it's not possible for someone who helped train a model to just upload it to Hugging Face whenever they want.

At a high level, this is what Alexander Long and the Pluralis team call Protocol Learning.

It's a training process in which compute providers are only given a section of the model (the weights) to do work on. This is itself is not something that's a new concept. The hyperscalers use model parallelism strategies in their large data centers.

But the part that hasn't been solved for is creating a decentralized model parallel system.

In my opinion, if we can get fully decentralized model parallelism working through the efforts of what Pluralis and others are making, then we finally see what it means to have models as true global commodities.

Now, the reason I called this section experimental is because of the second sentence in the screenshot above - specifically the part that says "the economic sustainability of closed model releases".

By having a model that no one can tamper or own, there is a new opening for an asset class based on models-as-a-commodity. This warrants new kinds of economics and business ideas that no one is really even thinking of right now. I don't think this is necessary for the future of humanity (at least as it stands) but the comparison is more so how Uniswap provides a lot more interesting financial use cases and Farcaster provides a different set of social experiences.

I asked ChatGPT to come up with some use cases if we could financialize the development of intelligence. To be clear, this doesn't even have to be tokens. Literally, everything we're talking about could be done with stablecoins. What matters here is the point that financialization can exist because of model parallelism.

To wrap this section up, let's recap the 3 parts of pre-training that intersect with DeAI.

1. Philosophical: training models requires up front capital expenditure which leads to reliance on a single entity. A model can only be truly open source when there's no central point of failure.

2. Practical: there's an upper limit to how much hyperscalers with large treasuries can expand their centralized warehouses. These teams are already working closely with DeAI folks to improve distributed training and GPU communication standards.

3. Experimental: models as a commodity in its purest form means no one can run away or take advantage of the model itself. If decentralized model parallelism can work at scale, then you own an entirely new asset class around intelligence giving the long tail of consumers opportunities to gain exposure in the new AI wave.

On to post-training!

Enabling creativity through society-of-minds

Before we dive into the main part of this section, it's worth quickly defining what post-training is.

Post-training is what gives LLMs personality, expertise, niche knowledge, and adds another dimension to the experience of how you interact with AI.

This can come in different flavors such as:

• Supervised Fine Tuning (SFT) - having people write out thousands of sample questions and answers which are then fed to the model so it can learn the style of answering

• Reinforcement Learning (RL) - do more of what humans reward / upvote you to do. The more thumbs up votes you get, the higher the score

Centralized Training is locked in on Post-Training

When Deepseek R-1 came out, you may have seen many tweets pointing out how post-training techniques will be the next big thing in terms of making models significantly better.

In fact, a month before that, Ilya Sutskever made the bold claim that pre-training as we know it will end because of data limitations.

Note: remember that it was OpenAI that came out with the first chain-of-thought reasoning model in September 2024 which was super impressive. But more people understood the impact of post-training & inference-time compute in January because of Deepseek's ability to do it at a fraction of the cost with a new kind of RL technique know as GRPO (out the scope for this post).

All of these post-training strategies come down to the need for unique data that others don't have access to. Every major AI company is focused on improving their data inputs in some form or fashion.

For example, news about OpenAI trying to buy Windsurf for $3 billion came out last week.

Why the heck would they do this? Because Windsurf has a crazy amount of data on how developers are using AI.

Jon Chu // Khosla Ventures

@heyjchu

My personal guess:

OAI is buying Windsurf for the distribution and coding telemetry data.

They're on track to spend hundreds of millions yearly on Mercor. This is another avenue for capturing that type of data, and also gets them a great product and reduced mercor spend

440

10:08 PM • Apr 16, 2025

In fact, after reading that tweet by Jon, I was shocked to find out that OpenAI pays upwards of $300 million to Mercor (AI hiring platform), ScaleAI, Upwork, etc. to source domain experts to help out with things like data labeling, RLHF, and post-training in general.

Okay let's pause for a second. What are the key points made so far?

1. We know that pre-training in a decentralized way is really hard because it requires the coordination of a ton of compute and capital that's all crowdsourced. But there's still progress being made.

2. Most AI developers are realizing that the next major developments in model performance and scaling will come from reinforcement learning and test-time compute.

3. The limitation of post-training seems to actually be acquiring the data, expertise, and experience of people in niche subjects, less so the compute & synchronicity requirements.

If these statements make sense, then there's a clear argument for crypto x AI folks to diligently work on a "post-training marketplace" with incentives / rewards baked into the network.

And that's right along the lines of what Andrej Karpathy and Yann LeCun are calling for.

Yann LeCun

@ylecun

I've been arguing for something like this for over a year: crowdsourced distributed fine-tuning.

Andrej Karpathy

@karpathy

For friends of open source: imo the highest leverage thing you can do is help construct a high diversity of RL environments that help elicit LLM cognitive strategies. To build a gym of sorts. This is a highly parallelizable task, which favors a large community of collaborators.

3,089

2:57 PM • Jan 29, 2025

Society of Minds Architecture

In this post, I'm not going to get into the details of how the RL gyms should be structured but rather focus on why it matters that there is a way to make crowdsourced distributed fine-tuning actually work.

ChatGPT already has 300-400 million monthly active users. Many people already claim that they use AI in some form or fashion in multiple parts of their lives.

At the end of the day, if 4-5 closed source models decide who the experts are to rank data sets and develop evals (framework to evaluate LLMs), then the general population pretty much has to blindly follow and use what these teams decide. It's philosophically no different than the social media feeds argument. What is one of decentralized social's main selling points? That there's an opportunity for anyone to build a client / UI that isn't decided by a team at Instagram or X - you have the freedom to choose your own feed (you don't have to but the option to do so is key here).

I personally believe that there is a vast amount of untapped experience and wisdom around the world. We want these models to have the opportunity to learn from all of this data. Anyone should be able to contribute to these models, explore as much as possible, wander through diverse environments, share their experiences, etc.

The analogy that clicked for me was GitHub.

Github enabled talented developers from any corner of the world to contribute to whatever open source repo they wanted to. It's important to note that this doesn't mean every single PR was merged. Obviously a lot of the contributions around the world are low quality efforts (or even malicious) but the community has the option to simply not include them. Or, those that believe their efforts are ~contrarian~ can simply fork a repo and continue building for themselves.

We need a onchain network of RL gyms that enables anyone to permissionlessly create and/or contribute to models through post-training processes.

Contributions can be in the form of providing expert evaluations, scoring model answers, providing unique datasets, and so on.

Wait a minute! You may be thinking...why does it have to be onchain YB?

Well, the reality of how open source worked in the '90s and 2000s doesn't exactly map to how open source AI contributions will happen. In the era of Linux, MySQL, etc. open source was more philosophically driven (cypherpunk era vibes) and didn't require additional resources other than a computer & internet.

If someone made a bad PR, it would just be deleted or ignored. On the other hand, if someone maliciously trains a model on bad data or submits pooly designed evals, then there is capital being unnecessarily burned because of GPU costs.

Network participants in these RL gyms needs to be held accountable through well designed incentive systems. Similar to how if a Bitcoin miner submitted a block that gave itself more money, the network will penalize the miner.

The scarce resource for the early Github open source era was just time and knowledge. On the other hand, making AI models better have additional requirements of compute and data.

If this onchain RL gym network is built out properly and can attract enough contributors in the marketplace, then it's very realistic to see the modular thesis of AI play out.

A world where there are many different specialized models that users can plug in when needed. And the people who contribute to making these niche models work will be rewarded based on model performance in the open markets.

My friend Sam Lehman likes to call this the "decentralized school approach". An opportunity for the smartest people around the world to come together and permissionlessly contribute their knowledge and experience in order to help build the technology that will define the next era of how we think, act, and live.

The world is an abstract, messy, and complicated place. Not everything looks like a math problem that you can have a boxed answer to at the end. For non-verifiable and subjective topics, it's important that people who think they should have a say are in fact allowed and incentivized to pitch in. Let the markets decide if their contributions are valuable or not.

Recently, Packy asked ChatGPT the following question:

One of the answers it gave was as follows:

In other words, let the hivemind win. This is how you enable creativity around the edges.

To end this section, I want to quickly revisit the Sun-Linux backdrop from earlier in this post.

Imagine if we didn't have Linux? There would be countless innovations that we take for granted today that probably would not have even had the chance to come to life.

If the last 30 years of software depended strictly on Sun and Oracle infra, it's pretty safe to say that we may not have progressed as fast as we have. Creativity would be stunted and contributing to technology would be an activity strictly for the business elites.

And for that reason, it's my view that if you think Linux was critical to the internet, then it's a no brainer that having a truly open source post-training network with proper incentives is a necessity for the AI era we're just starting to enter.

To wrap this section up, I want to clarify the fact that setting up a decentralized RL network is a non-trivial problem. There's so many different parameters and components to think about. We're a long ways from it but teams such as Prime Intellect and Gensyn are showing some rapid iteration in the last couple of months.

Hervé Cuviliez

@hervecuviliez

If you are in AI, no matter which side of the table and you are not following @gensynai recent updates
You are missing out bigly !!
Congrats @fenbielding & @_grieve

Harry Grieve

@_grieve

rl-swarm repo stars, or @gensynai team vibes?

26

11:23 AM • Apr 19, 2025

Again, the technical details are out of scope for this post, but I'll be going through these efforts in depth the next couple of weeks so make sure to subscribe to Terminally Onchain!

What to keep an eye out for in 2025

At the end of the day, this post was really just for myself.

It was a chance for me to take a deep breath and see if I could come up with a compelling argument to continue going down the DeAI rabbithole.

And it seems to me that there's enough evidence and reasoning to continue tracking the new developments at least until the end of 2025.

Jake Brukhman (co-founder of CoinFund) has "deAI Summer 2025" in his X name. To me, this feels accurate. Not in the sense that the world will be using decentralized AI services by September. But more so that a lot of key releases are coming up in all parts of the AI world and it'll be clear if DeAI can keep up or it can't. For example, ICML is coming up this July - what are the AI community's reactions on the new papers DeAI teams are expected to publish then?

In my opinion, at the rate AI is accelerating, it'll be pretty clear by Q4 of this year if there's a reasonable shot or not for crypto x AI to actually have mainstream merit. To be clear, I'm not saying things will be robust and working but more so that there will be enough data points for anyone to agree that DeAI has a unique enough value prop.

Of course I'll be keeping up with the projects mentioned in the post above such as Nous, Gensyn, Prime Intellect, etc. But this primer barely touched the surface of all the developments going on!

There's a ton of amazing teams cranking away on different parts of the AI stack and are trying out a variety of solutions - none of which should be ignored considering how early it is in this hyper niche vertical.

For example, here's a couple of things I didn't even have a chance to get to but I know for a fact that I'll be tracking closely over the next few months.

1. Sovereign Agents - if we really are headed to a world where agents will be doing more than we can imagine...then there's a chance to make onchain infra the no-brainer choice for agents to complete their tasks. What does that infra look like compared to web2 rails? AI researchers themselves can have bias, but agents are looking to just be efficient. And if there is merit behind the idea that privacy, micropayments, agent-to-agent communication is in fact better onchain, then let's build for that!

2. AI L1s - I haven't gotten a chance to look into AI L1s such as the Bittensor ecosystem, Ritual, Ambient, etc. This is my first priority going into May and it's clear that there's a ton of work happening in terms of attracting fresh developers (i.e. new subnets popping up). I want to dive deeper and understand how the economics differ in the L1 model and if there's enough merit to argue that the developer ecosystem will continue to grow.

3. Data Providers - I've published a piece on Vana back in December. In that post I made the argument that decentralized data marketplaces need to rebrand from the idealistic "protect your data" punch line to focusing on data as a new asset class that has financial upside. The reality is that the average Joe doesn't care about their data that much. Data marketplaces in my opinion will only gain steam in a way that probably looks similar to the agent meta from Q4 of last year. I also need to look into Masa, another solution for data marketplaces.

4. AI on local hardware - there's a lot of research efforts going into creating agent frameworks that can run on your local hardware. In fact, Soumith Chintala (creator of PyTorch) has an amazing talk covering why it's important to have an agent that runs locally. The team at Exo Labs is working diligently towards this goal. If you have some time, I highly recommend checking out their 12 days of Exo series where they showcase fun projects like running Llama on Windows98!

5. Memory & Personalization - as I mentioned in the enterprise vs consumer section above, memory was recently handed the first place award by the moat committee. If this is the case, then how do we think about personalization lock-in and portability for DeAI? Ejaaz has a good tweet about this. I haven't gone deeper yet, but am definitely looking forward to check out companies like Plastic Labs, Heurist, Honcho, etc.

I could go on and on, but the point is that there's still a ton I have to understand in the crypto x AI vertical.

To me, it's clear that if there's a window of opportunity to start getting as deep as you can on DeAI, it would be like...right about now.

YB

@yb_effect

worth noting that just in the past month @PluralisHQ announced a seed led by USV and Coinfund. and @PrimeIntellect raised a round led by founders fund

more announcements also coming p soon in this vertical

YB

@yb_effect

you have 3-4 months to get up to speed on DeAI and find your alpha

49

11:40 AM • Mar 29, 2025

If you don't have time and want to follow along my journey as I continue making my way through the "DeAI idea maze", then make sure to subscribe to Terminally Onchain for all my insights.

Curated set of Resources by Topic

YB's Content

• Key takeaways from DeAI founders

• Open source & DecentralizedAI Twitter List

DeAI Resources

• The World's RL Gym

• GSR Report

• Cyber Fund Crypto x AI thesis

• Scaling through Decentralization

• Frontier Training

• Big Brain Decentralized Training

• Why (good) AI needs crypto

• Agents Unleashed

• Protocol Learning

• Inference reshaping AI governance

• Chain of Thought Newsletter

• How to build an American Deepseek

Getting up to speed on AI

• Karpathy LLM talks (Deep dive into LLMs, Intro to LLMs, How I use LLMs)

• 3Blue1Brown Neural Network series

• LessWrong Technical Prime on O1

• NovaSky train your own AI

• Nielsen's textbook: follow 3blue1brown examples and get hands on practice

• FineWeb: basically the "internet data" compressed for you through crawlers

• Common crawler: open repository that's used to scrape all the internet data

• Tiktokenizer: select a model and you can covert between plain text and tokens

• BBY Croft: fantastic LLM Visualization tool to understand the training process

• RLHF Handbook by Nathan Lambert

• Chatbot Arena - LLM Leaderboard

• Hugging Face LLM pricing

• Questions about the future of AI

• The Era of Experience

Relevant Podcasts

• Redpoint's Unsupervised Learning

• Dwarkesh Podcast

• No Priors

• a16z AI

• Interconnects (& newsletter)

• Into the Bytecode episodes with Nous & Pluralis

Talks

• Nathan Lambert's talk on open source AI at Harvard

• Derek's talk on Crypto x AI at Collab Currency

• Delphi Digital Crypto x AI Month

I hope all 9676 of you had a great week

In case you don't read my full post, putting this request at the top.

Please take a second and vote for me to give a talk at Farcon (Farcaster conference).

Anyone can vote and it only takes a few seconds.

There were 35 submissions and the top 6 will be selected to give an 8-minute presentation.

Even if you don't read all the entries, it would mean a lot if you could put me down as one of the votes and hit submit!

🙏 Please vote for Talk #32 here by Monday April 7th 12 pm EST 🙏

I've always viewed crypto as the dark knight of frontier tech.

The hero that people shit on. The hero whose reputation is tainted by scandals. The hero that most people will never understand but will end up benefitting from anyways.

To be clear, we're not there yet...crypto is still in its "Batman Begins" era.

My belief in crypto is it's ability to serve as the backend of society.

It will keep the networks alive. It will keep the markets moving. And it will handle the burden of commitments and identity.

You're probably thinking...YB why the hell are you being so deep and dramatic all of a sudden?

The honest answer? I think this double shot is really hitting right now.

Okay okay sorry I'll be serious now.

I've been feeling a bit anxious about my decision of committing to the DeAI rabbithole the past few days.

Am I just wasting my time with this? I had a good thing going with general onchain strategy. Will the AI people ever take this seriously? Heck, do the crypto people even care about this?

All week, I've been feeling this lingering nervousness that I publicly committed myself to something stupid. Side note: I was talking to my friend about this and he said "bro you publicly committed to something stupid when you went full time crypto 5 years ago" 🤣

The truth is, I felt a mix of unease, imposter syndrome, and fear about "going all in on DeAI" up until this morning. But as I started drafting this post, I asked myself...what even hooked you to DeAI in the first place? Why have you been enjoying it so much even after the agent meta died down?"

The answer to that is simple. I've been having so much fun learning about AI - the technicals, history, key researchers, vertical nuances, etc. And it's been a blast for two reasons: 1) I'm being intellectually challenged and 2) I've been enjoying making comparisons between the crypto & AI industries.

YB

@yb_effect

one benefit of going down the DeAI rabbithole is that even if it doesn't work out in the big picture sense, i'm having a blast going through the AI papers and understanding the fundamentals there

similar rabbithole experience to when i first got into crypto 2019-2020

6

10:03 AM • Apr 4, 2025

At the end of the day, I realized what I enjoy most is going down rabbitholes and learning everything I can about a topic.

So, why did this realization ease my anxiety?

Because I realized that it wasn't actually about "publicly committing to DeAI". I reframed it to me being a crypto evangelist for other verticals of frontier tech - I just happen to be starting with intelligence. Maybe in the future I add in energy (Daylight, Flow) or DeSci or DePin.

It's now clear that what I've really committed to is taking the time and effort to truly go deep into other verticals and craft an honest narrative of how crypto can effectively plug in as a backend.

Let's be real for a second. Founders from AI or biotech or energy don't have the patience to figure out why crypto may be worth thinking about.

Folks from our "dark knight industry" have to do the hard work of learning about the other frontier technologies and coming up with a sales pitch of why crypto as a backend is the more effective solution. Look - it's easy for anyone to grab a megaphone and scream out "decentralization, privacy, no centralized AI!" but it doesn't mean shit. The only thing that matters is understanding the tech (i.e. AI, nuclear) and coming up with a practical solution of how you can help researchers and builders in that industry think differently about network effects, scaling, and incentives. And if you can't do that, then it's okay to be intellectually honest and admit that maybe it doesn't make sense for crypto to serve a purpose for that topic.

So, that's exactly how I'm going to approach DeAI this next month. The worry is now less about me and more back to the point of...does crypto make sense for AI?

And I mean it when I say a month. By my last post of April, you'll know exactly where I stand with DeAI and how I want to proceed.

Okay with that being said, what's the plan?

Farcon Talk & YB's Thesis

In February and March, I spent a ton of time getting caught up on the fundamentals of this vertical - including learning AI, using the tools, reading all the primers, mapping out the DeAI ecosystem, filtering out the noise by talking to researchers and founders, etc.

Now, it's time to take all these learnings, sit down, and do the actual hard part of developing my own thesis on how I view decentralizedAI.

In order to this, I have one (maybe two if you all vote and I'm selected for the talk!) deliverables:

On Friday, April 25th, I commit to publishing my DeAI thesis.

And if I'm selected to give a talk at Farcon, I'll repurpose that thesis into a presentation which would happen the following week on May 2nd.

Both of these tasks feel pretty intimidating. Who am I to give a talk on this topic? Do I have anything meaningful and unique to say in my thesis? But I know they'll serve as a forcing function for me to stop puttering and get practical.

In fact, I titled the talk: Decentralized AI Needs a Rebrand: Less Idealism, More Incentives.

Here's the abstract for the talk I submitted...please reply to this e-mail with any feedback or ideas!

I mentioned this above but it's so important I'm quoting myself in the same post:

Look - it's easy for anyone to grab a megaphone and scream out "decentralization, privacy, no centralized AI!" but it doesn't mean shit. The only thing that matters is understanding the tech (i.e. AI, nuclear) and coming up with a practical solution of how you can help researchers and builders in that industry think differently about network effects, scaling, and incentives.

Less idealism, more incentives! Let's get practical and show why crypto should be the backend.

By the end of the month, if I'm asked this question/request I should know exactly what to say:

Notes from talking to DeAI experts

Today's post and the next two posts as well (11th and 18th) will basically be me building my thesis in public.

So, what were the main things I did this week?

1. Finished up most of my calls with founders and DeAI friends - ready to go back to heads down time

2. Dictated a ton of voice messages of my notes for each of the calls I did (roughly 10 in the past two weeks) to chatGPT in order to get organized and keep the key takeaways top of mind

3. Made a list of the best resources I've come across and want to go through again + created a task list for things mentioned in the calls that I need to look into. For example, multiple folks told me to look into BagelAI. I also didn't feel prepared when it came to discussion on MCP.

Since I enjoy giving away all my research and work for free in return for a market that just keeps giving me red candles, I will of course share all my notes from the calls 😭

I've grouped them together and mixed the bullet points up to respect the privacy of the people I've talked to. Naturally I've had calls with some investors and founders that have their own personal bias so keep that in mind.

Key Takeaways from DeAI Calls

• Network effects + parallelization as critical competitive advantages for DeAI

• Bullish on training side of decentralized AI (less excited about GPU aggregation)

• Believes commodity hardware can win, despite 10-20% performance hit

• Sees value in historical context for "why DeAI" (2015–2020 open, 2020–2025 closed)

• Sees global latent demand beyond state-of-the-art models (i.e. researchers in Australia, India)

• Suggests decentralized solutions help general AI advancement (i.e. distributed training, optimizers)

• ICML 2025 (Vancouver, July this year) will be a big catalyst for DeAI

• Centralized players fundamentally constrained on RL (compute limits for real-time RL)

• Strategy: Build developer moat, first targeting Web2 AI devs. Incremental crypto integration later

• Believes strongly in open-source inference era

• Need to clearly highlight reliability/speed trade-off in decentralized AI

• Critical question: "What advantages justify decentralization?"

• Vertical integration seems to be growing trend from infra & consumer AI founders

• There will be increased demand for exposure to AI past Nvidia stock

• Goal is to refine pitch for AI founders to leverage crypto network effects

• Bold thesis is that open source AI can't win without crypto

• Level 4 & 5 AI as defined by OpenAI paper will be more effective with DeAI solutions

It's worth noting that these notes aren't totally game changer ideas or anything, but I do believe they help me create a "scaffolding" for my framework and overall serve as a good starting point to figure out what the vibe of my own thesis will be.

I'm going to hold off on sharing the resource list + tasks for right now. I'd rather give a complete one that's packaged nicely when I'm wrapped up with my full thesis post on the 25th.

In terms of main focuses for next week...

1. Have the outline for the thesis ready to go

2. Write a really shitty first draft of the intro

3. Go through the following companies, use the products, do another round of deep dives on their blog posts, send any questions to the founders, etc. (Hyperbolic, Prime, Pluralis, Nous, Bagel, Vana, and Gensyn)

I'll be back next week with updates on how it's going 🤝

I hope all of you have a fantastic weekend!

Please remember to vote for my talk at Farcon here 🙏

- YB

I hope all 9656 of you had a great week

In a post from two weeks ago I said this:

So why not host my own events? To keep it simple, I've challenged myself to put together an IRL social for NYC crypto folks by the end of March.

I'll hold myself accountable by sharing a picture before my first April post. I'm not exactly sure about my execution, but I'll figure it out - time constraints will solve everything.

And I did it...this is the last post before April!

First Terminally IRL event ✅

This past Wednesday, around 50 people showed up in midtown to meet other founders, investors, researchers, etc. Yes, the majority of people were crypto but I was surprised by the number of "AI people" that came as well.

The best feedback I got (from multiple friends) was that the quality of people that attended was really high which resulted in a ton of interesting conversations for folks.

Oh...and of course that the Samosa + Diet coke combo hit the spot 😂

YB

@yb_effect

hosted my first event in NYC last night and it went really well!

~50 people showed up, had some Indian food, and enjoyed the @yapsterxyz office

also made a TG channel (read only) where I’ll be curating any crypto & AI NYC events, just comment below if you want to join

188

10:45 PM • Mar 27, 2025

With that being said, what are my thoughts from hosting this event? And what's next?

I feel like the main takeaway for me was how surprisingly high the value / time metric was.

In all honestly, it didn't feel like I had to do much to set up the event.

• Post tweet, gauge interest

• Ask Salvino if I can use the Yapster office

• Create Luma event, share to people who commented

• Share Luma on newsletter

• Order food and instacart drinks

Of course, it's worth noting that my distribution on X and this newsletter helped a ton...after posting I just had to copy pasta the Luma event to everyone and that itself led to 100+ signups.

Anyways, my point is that just by doing the steps above, I met a ton of new people I wouldn't have normally come across, had interesting conversations not related to my day to day work, and got invited to a bunch of other events. And the cherry on top is that I've received multiple texts from investors and founders that they'd be happy to use their office and sponsor future Terminally IRL events!

Hosting an event is somewhat like having 50 1:1 coffee chats in parallel. Sure, you probably miss out on some depth but it's way more efficient than doing them independently.

And you can always filter down folks who you want to talk to more in detail in the weeks after the event.

If there was one thing I'd give myself feedback on, it would be to get better at actively listening and not forcing conversation.

Maybe I was a bit nervous about being a host but I noticed myself feeling slightly robotic with my conversations. "What are you working on full time?" "How did you hear about this?" "What's most exciting to you in the space rn?" You get the point. To give myself some credit, I did feel above average pressure to say hi and talk to everyone there which probably led to this. And it's not that my conversations were bad or anything like that, but there's always room for improvement.

I think one thing to keep in mind as I go to more IRL events is aiming to ask at least one question to each person that can't be "copy pasted" in another conversation. It kills two birds with one stone: forces me to be present in the conversation and gives assurance to the person I'm talking to that I'm genuinely curious.

Terminally IRL (NYC events) TG Channel

Okay so what's next? I'll definitely be hosting more events...thinking a monthly cadence is good enough for right now. The second Terminally IRL event will be around Farcon (last week of April).

But, I want to take it one step further. Why not use this opportunity to get started on being an NYC tech event aggregator / curator?

I can start simple - just crypto & AI events. To me, it's clear there's a need for someone to intentionally merge both communities together.

This first event resulted in 100+ e-mails that signed up on the Luma. So yesterday, I sent an e-mail blast out letting people know about my TG channel (read only, so no spam) where I'd curate crypto and AI events going on in the city. And if anyone else wanted to share their own events, I'd be happy to blast it out for them.

If you want to join, feel free to do so here: Terminally IRL Telegram Channel.

In less than 12 hours, the channel already has 140 subscribers and I've gotten one request for an event blast!

I'll keep you all posted on how Terminally IRL is going the next couple of months - my mindset with this is to keep it casual, fun, and see what opportunities come out of it. *insert increase your luck surface area something something quote*

I know we didn't cover DeAI stuff today but trust me I had a lot of great epiphanies regarding this vertical the past few days and I'm excited to sit on them a bit and share more next week!

Truly, I do believe that these next few months is basically an arbitrage opportunity to get in and dissect the DeAI space before it becomes consensus to do so.

YB

@yb_effect

you have 3-4 months to get up to speed on DeAI and find your alpha

45

11:35 AM • Mar 28, 2025

I got a chance to talk to Alexander Long (Pluralis), Vincent Weisser (Prime Intellect), and David Sneider (Lit Protocol) earlier this week - the conversations were super helpful in guiding me on what to focus on next.

In parallel, I'm also applying to give a talk at Farcon and have been figuring out the structure of an 8 minute lightning talk on DeAI. If anyone has ideas for what they think would make for an interesting presentation, please reply to this e-mail...will gladly give you a shoutout if I'm selected!

At a high level, my goal is basically this:

YB

@yb_effect

my goal in the next month is to be able to articulate a "why DeAI" thesis that I feel truly confident pitching to anyone

rn I get the appeal at a high level, but the "why AI needs crypto" pitch still isn't hitting for me

I want to craft a story for DeAI that clicks immediately

48

6:28 PM • Mar 24, 2025

I've also been spending a ton of time pouring through Dwarkesh's new Scaling book - basically a cheat code to get up to speed on the last 5 years of AI in one place.

YB

@yb_effect

started @dwarkesh_sp scaling book and asked gpt to read with me

best part of the book are all the footnotes. i've been tagging new material as either concepts or papers as I'm asking clarification questions

then at the end of each section, it'll generate a quiz and grade me

10

9:22 PM • Mar 25, 2025

That's all for today's post, I hope everyone has a fantastic weekend!

See you all next week 🤝

- YB

I hope all 9629 of you had a great week

Alright the weather is beautiful outside so I'm going to keep this short...let's all go touch grass this weekend since spring is here and the seasonal depression is finally over.

Before I get into the takeaway of the week, a few updates.

IRL Events

In last week's post, I gave my reasoning as to why attending and hosting IRL events is going to be increasingly important. And I challenged myself to organize an event in NYC before the end of the month.

So on Sunday, I tweeted this...and omg having a bit of distribution is game changer. In less than an hour, there were 50 registrations and the event booked up.

YB

@yb_effect

this past week it's really hit me how increasingly important your IRL network is going to be in the coming years

so I'm going to try experimenting w diff kind of meetups

will start w friends in crypto & ai but expand over time

if you're in NYC and want to join, pls comment!

165

9:24 PM • Mar 16, 2025

If you're in the city and want to attend, please sign up on the Luma and reply to this e-mail so I can take you off the waitlist. Special privileges for people who actually read Terminally Onchain 🤝

Something unexpected that happened because of the tweet above is that I had other event organizers reach out and invite me to their events as well!

So this week, I went to my first two AI meetups. Not going to lie, I was a bit nervous and felt the same excitement I did when I first started going to crypto conferences a few years ago.

Both events ended up having demos and discussions related to MCPs (model context protocol). I got a ton of interesting insights but will wait to share until next week after I do some research and get answers to a few questions I have. But the point is that it seems like developers are locked in on MCP server development and we should be paying attention to what's happening there as well.

One thing I'm curious about is how "far behind" the AI discussion in NYC is compared to the meetups in SF. If any TOC readers are in the bay and have context, would love to get more insight on this!

YB

@yb_effect

went to my first few AI events this week in NYC and MCP was the core topic / demos at all of them

what's the pulse check on sf ai scene? i wonder if devs here are "behind" on what the main focus is

2

11:46 AM • Mar 21, 2025

I also learned about ainyc.net in case you're interested in signing up for their list of IRL events.

More chats, more context

On Monday morning, I was a bit frustrated because of how many companies there are in the crypto x AI vertical.

YB

@yb_effect

there are way too many companies in the DeAI sector that all have exactly the same descriptions on their websites

challenging myself to curate a golden basket of 5-7 companies that I would personally invest in

- shipped anything in past 6 months?
- any unique insights on blog?

55

2:03 PM • Mar 17, 2025

I had the realization that I had learned enough of the basics on AI / DeAI and it was time to start having conversations with others in this vertical. If I stick to just reading, I'll have a limited perspective and miss some important insights.

So, I reached out to 5 friends to get started and ended up having some awesome coffee chats & phone calls. Got new alpha, resources, and directions for further research. The 2-3 hours of conversations helped save soooo much time filtering out the noise.

I was pretty quickly able to put together my "golden basket" list for DeAI with their help. And I already have a packed week of calls next week with some of the teams mentioned below.

Worth noting that Pluralis just announced their seed round led by USV and CoinFund this week.

Pluralis Research

@PluralisHQ

1/ We are excited to announce our $7.6M seed round led by @usv and @coinfund_io to make true open source AI a reality. Pluralis has a new approach - we're calling this Protocol Learning.

533

10:30 AM • Mar 19, 2025

Also, it became clear to me that I seriously need to understand RL (reinforcement learning) and why it's game changing for DeAI. Multiple, smart people all pointed to this as the next big shift. That's going to be the focus for next week.

Twitter list for open source & DeAI

I finally took some time this week to go through my recent follows and make a Twitter list of people I believe are worth keeping tabs on when it comes to open source, decentralized, and distributed AI.

There are 50 or so folks in it right now but I'll be slowly adding over time, enjoy!

YB

@yb_effect

made a list for anyone interested in keeping tabs on open source & DeAI

50ish people rn but wip

x.com/i/lists/190277…

24

1:50 PM • Mar 20, 2025

Many long time TOC readers know that I'm a sucker for tech history.

While eating lunch on Wednesday, I was watching this Bill Gurley - Brad Gerstner discussion. Around the 14 min mark, Gurley gives a beautiful analogy as to why corporations ("smart buyers") will start migrating to open source solutions.

Basically in the '90s, as the # of internet companies was taking off, high-traffic businesses were willing to pay for the Sun + Oracle server-DB stack. It was the professional thing to do and all the companies wanted the top of the line server solution. And this lasted throughout the dot com bubble.

However, in parallel, the open source community was relentlessly building out Linux and MySQL. And by the early to mid 2000s, the "LAMP" stack had gotten robust enough to where the new set of startups could bypass the Sun stronghold and just get started for free. Think MySpace, Facebook, etc.

Open source's "meets expectations + trivial cost" > first class b2b solutions for the majority of customers.

I also asked o1 for some numbers on Linux vs Unix domination over the '90s and 2000s. Look at how different the server market share looked in just one decade.

Based on that analogy, it's not crazy to think that corporations will have a lot more say in what set of models they want to use in the next 5-7 years. No different than how enterprises had multiple cloud solutions to pick from in the mid-late 2010s after AWS dominated the first couple years of cloud computing.

Bill's main point is that if we really are moving to the point of 99% inference and other layers in the AI stack start taking more importance as models get commoditized, then it's probably going to be the case that the enterprise AI framework shifts to:

• open source general models

• fireworks ai / open router model orchestrator solutions for inference

• company specific tooling

• fine tuning with private data using cloud providers

This also lines up exactly with what Satya Nadella said on a recent Dwarkesh episode:

"Consumer markets sometimes can be winner-take-all, but anything where the buyer is a corporation, an enterprise, an IT department, they will want multiple suppliers. And so you got to be one of the multiple suppliers.

That, I think, is what will happen even on the model side. There will be open-source. There will be a governor. Just like on Windows, one of the big lessons learned for me was, if you have a closed-source operating system, there will be a complement to it, which will be open source.

And so to some degree that's a real check on what happens. I think in models there is one dimension of, maybe there will be a few closed source, but there will definitely be an open source alternative, and the open-source alternative will actually make sure that the closed-source, winner-take-all is mitigated."

And in terms of consumer AI, the analogy was more akin to the search wars. Meaning, it is in fact possible that consumer AI is a winner take all game.

But! The key point Gurley mentioned which is worth taking note of is the competitor set for each "war" in the image above. For search, it was pretty clear that Google's page rank model was superior and the rest were falling behind quickly from a business plus a technical perspective.

On the contrary, with the current AI wars, the set of logos on the right all hold a certain advantage to the point where it's simply not possible to eliminate anyone just yet.

Obviously, ChatGPT has impressive numbers and "normie mindshare".

But, you also have Elon, Zuck, and Pichai quickly following up with their own breakthroughs and using their deep pockets to dig deeper into the generative AI advertising moat.

As Ben Thompson explained last October in his bullish Meta AI post:

Not only that, but the last couple of months have showed us that now even Chinese competitors such as DeepSeek, Baidu's Ernie, etc. are not only on the racetrack but running side by side a few lanes away.

So what are the key takeaways? Well, for me:

1. On the enterprise side, I need to seriously lock in on companies like Fireworks, Hugging Face, and Together AI. That means understanding their business models, how they're catering hosting and inference solutions for enterprise customers, their feedback loops with the open source community, etc.

2. And on the consumer side, of course it's about keeping up with the numbers. But more importantly, having an on the ground pulse of what different audience segments are thinking about in terms of model performance.

   For example, at one of the AI meetups I went to this week, the developers all agreed that Claude Sonnet 3.5 was in fact better than 3.7. They all thought 3.7 was too "one shot" oriented and it would often double down on the wrong direction too confidently.

   Another example is talking to people outside of tech and getting their views on things like Google's AI answers or how they're using GPT. Random example, but I recently found out my mom uses the WhatsApp AI (Llama) a couple of times per week! I was shocked to see her use it so casually.

That's all for today's post, I'll see you all next week!

Hope all of you have a great weekend :)

- YB

I hope all 9602 of you had a great week 🔥

A few years ago, a mentor who has been active in the tech space since the 2010s told me that what a lot of people don't know about Marc Andreessen is that he's one of most prolific WhatsApp group chat creators & curators out there. He's started hundreds of chats for all kinds of topics with a variety of people to make sure he's in the know about everything.

To be clear, these groups he's making aren't simply just for "s-tier influencers and founders". Of course, he has access to and conversations with them as well. But from my understanding, it's more so Andreessen's ability to identify people who may not have a public presence but clearly know something about a niche topic that he wants to keep tabs on. And it's through these light green texts where he gets his head start on understanding what everyone else finds out a few months (or years) later.

In a post from December, I mentioned the following:

I titled this article "What did Marc Andreessen see?". And to be honest, I think it made the most sense.

It's amazing to me that pmarca was not only able to sniff out Truth Terminal months before anyone else but also strategically talk to the agent and give it a $50k grant in BTC. We all know this lore by now but the impact of it only gets stronger as the new meta continues to increase in relevance.

Marc understood that there's deep value in giving grants to these hackers and letting them experiment at the frontier of new technologies.

When I first started going down the agent rabbithole in September, it was wild to see that some of the most random accounts with 200 followers had pmarca following them but not a single other person I follow!

Anyways, what's the point of this Andreessen group chat fanboying?

It's now clear to me that the most important skill going forward in this AI world is what access you have to trade secrets and alpha that others don't know about.

Not my own insight, but something I saw both Tyler Cowen and Ben Thompson say this past week. I spent some time to digest it and the point really started to make sense.

The concept itself is not complicated or anything but I want to explain my chain of thought 😉 to all of you because of how important I think it is.

In my last post, I made it clear that I needed to "learn smarter" with frontier models:

So last week I bought the $200 OpenAI deep research subscription.

There's no excuse for me to have extended timelines on learning new material. It's cope. There's a hammer available to me but I'm still banging the nail with a rock.

The goal is to learn the smart way and be fast about it.

Those who quickly adapt to the new methods of consuming and learning information will have a headstart on the way things are headed. And it's clear that even a few months of using these tools before others is enough to make the margin larger than most of us realize.

I've really stuck to that promise. In the past two weeks, I've been very intentional about using o3-mini, o1, and deep research as much as I can. In fact, this past week, my deep work session went something like this:

1. Read deep research report generated from day before (I'm most sharp with my first coffee)

2. Explore all the links that were cited in the report and draft a tweet or two as "my notes"

3. I then dump all my thoughts to o3-mini and ask it to find a common thread with what's on my head from all the reading. Based on this context it has, I have o3-mini generate a prompt for me that I then give to o1

4. Then I have o1 give me a couple of different angles on how I can explore the given topic. I'll have it generate 1-2 pages that cover the main bullet points and context. From there, I'll pick and choose what I think is most important and then have o1 generate an essay of a prompt that I can feed in to deep research

5. Generate deep research report for the next day's morning reading

It's not a perfect process by any means. But given the changes I'm seeing with my work flow already, it's clear that if I continue refining my approach...there's no going back.

My favorite part about deep research is that it serves me the rabbithole. I just have to read and click. The time saved on surfacing the right information is simply mind-blowing.

Here's the thing. Right now deep research costs $200 / month and definitely takes some prompt tinkering to get truly personalized reports that hit the nail on the head.

In other words, it's not accessible to most people right now.

But it's only a matter of time before it is. It's not that crazy to think that the current deep research capabilities we're seeing right now will move to the general, cheaper subscription by the end of 2025. And the premium version will be a 5x better reasoning model or whatever upgrades SF is cooking up right now.

So what are the implications?

Well, as the number of people using advanced reasoning tools grows, there starts to be less of an advantage in your ability to curate and produce high quality research on any given topic that's on the internet.

Key words being "on the internet". Whatever frontier models can train on is fair game.

So if there's diminishing returns on who can spend the most time sleuthing for links and typing up the longest reports, where does the value flow to?

To those who have access to information that's not already in the public domain.

YB

@yb_effect

yea definitely. but i think the importance is orders of magnitude more bc it's a lot easier to "know everything".
there used to be an advantage in being able to surface valuable info in the public domain, but that seems to be going down. which imo makes the "secrets" stronger

1

10:44 AM • Mar 14, 2025

Or as Tyler Cowen beautifully puts it in an interview with David Perell (a bit long but just read the damn quote it's important)

Humans know secrets; maybe AIs can be fed secrets, but they don't in general know secrets. Now, a human only knows so many secrets—that's partly where decentralization comes in.

How AIs will handle secrets, I think, is a big and interesting question; it's somewhat under-discussed.

It seems like in the Peter Thiel definition of a secret, which is something you know about the world that other people don't know, there's a chance that those go up because now there's less of an incentive to put things in the public domain since they can spread so much faster.

So there might be more of an incentive to hoard information. It will be worth more to you because the public information you used to hold is now worth very little. The future—the AI-rich future—is also a world replete with secrets.

Secrets are super important; gossip is very emotionally and practically potent. It's another part of this new structure we're not ready for. We got to talk more about this: why social networks are more important now.

How good are you with secrets? Are you good at trading secrets? If you are, you're a lot more productive than you used to be. You ever have these conventions with your closer friends like, 'I'll tell you this secret, it's not quite a deal, but it's understood that you'll tell me that secret in return?'

Increasing returns to social networks—social networks become way more important as well.

And very similarly, Ben Thompson mentions this in a post of his covering deep research

One additional point he makes that piqued my interest was how these "secrets" are actually a huge bull case for prediction markets. If this information will go into the public domain, how can those with the information asymmetry capture some of that value?

YB

@yb_effect

never thought about AI & prediction markets in this way

bc of deep research like tools that will only get better, the advantage is in what information isn't publicly available

PMs are the best way for people to profit from secrets before they're in the training data

11

3:46 PM • Mar 12, 2025

For what it's worth, the whole concept of defining insider trading in this new paradigm of information markets is still in its earliest stages. It'll be interesting to see what happens in terms of legal and ethical standpoints going forward.

I did want to share a brief exchange I had with my friend who was questioning the above tweet:

So then, the natural question should be "how do I acquire more secrets?"

• Learn how to rally an IRL community through meetups

• Be selective about which events you attend, spend your social battery wisely

• Go travel to different parts of the world

• Get closer to the gossip

• Be the reason people connect, make yourself a critical node in your greater social graph

It's having the "create your own yacht" mentality - find ways to bring interesting people to your home turf and share things.

What are the key takeaways from all this? For me, three things.

Embrace what is most +EV in the new world

YB

@yb_effect

seems like the two advantages going forward are:

1. how much better can you prompt and have models work together (multi-step orchestration)?

2. what trade secrets / alpha do you know that isn't already in the public domain?

10

10:22 AM • Mar 14, 2025

Make my own yacht

I live in NYC, one of the most (if not the most) important cities and hubs for crypto. But all I do is go to the occasional meetup hosted by VC funds.

So why not host my own events? To keep it simple, I've challenged myself to put together an IRL social for NYC crypto folks by the end of March. I'll hold myself accountable by sharing a picture before my first April post. I'm not exactly sure about my execution, but I'll figure it out - time constraints will solve everything.

⚠ If you're in NYC and want to come, please reply to this e-mail ⚠

Learn about the privacy side of DeAI

I need to spend time learning what products are working on the importance of handing secrets between AIs and humans on a decentralized network

YB

@yb_effect

so far, I've only been focused on the pre-training side of DeAI but I'm realizing I also need to spend time on the verifiability & privacy side (zkml) as well

basically how MPC, FHE, etc. come into play

"how AIs will handle secrets is somewhat under discussed" - Cowen

12

3:31 PM • Mar 12, 2025

That's all for today's post, I hope you all have a great weekend!

See you next week 🤝

- YB

Welcome to the 25 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Happy Friday everyone!

I went through a major work crisis last week.

To a certain extent, I'm sure many of you have gone through this train of thought as well.

It goes something like this.

For a few months you're locked in and killing it at work. The metrics are growing. Your confidence is increasing. And you're feeling just the right amount of learning obstacles to overcome and grow.

Things start feeling comfortable and you're in a weekly routine.

But soon the thought creeps in that maybe you're....a bit too comfortable?

You start seeing others on the timeline flexing their updates and you can't help but compare your work to the flashiness of their announcement.

And before you know it, the dominoes are starting to fall.

Have I been wasting the last few months? What have I actually achieved? Is this even the right vertical to be in? Ugh have I been spending way too much time on Twitter?

Here's the thing though. As with any crisis, it sucks in the moment. But once you walk out the other side, it actually feels damn refreshing and there's a new boost of energy you have for a couple of months till the cycle repeats.

So the good part is that I have a lot more clarity on a few things and I'm excited to share them with you all. Maybe some of the thoughts will help you as well!

None of these insights are groundbreaking to be clear. The more important thing is that they clicked for me in a serious way.

I feel a true sense of urgency to improve on all three of the things below.

Sections below:

1. Update my inputs (deep reading)

2. Learn smarter (deep research)

3. Evoke emotion (deeply personal)

Let's dive in.

For anyone who has been following my journey the last year or so, I've had a pretty consistent pattern with my writing. I would cover anything interesting that was happening in the crypto space. Stablecoins, zkTLS, EIPs, Farcaster, prediction markets, etc.

My posts were not for beginners but they also weren't the ultimate primer that got excessively deep. Let's call it 80th percentile coverage.

I do posts every Tuesday and Friday. The flow is: scroll X, pick topic, read/cram necessary material, write up the post, and repeat every three days.

And I'm glad I did that for my first 100 posts. I knew my writing wasn't amazing. And I knew my insights weren't anywhere close to Ben Thompson level. And that's okay. The whole point was to build the habit of publishing, explore a variety of topics, understand my research framework, etc.

Khe Hy

@khemaridh

Mr Beast tells aspiring YouTubers to make 100 videos and he'll give them feedback and advice.

2 things happen.

98% never get close and give up.

The 2% who do, no longer need his help.

What's the lesson here?

3,319

5:41 PM • Sep 28, 2023

I remember seeing this quote and locked in on getting my 100 posts out. And it worked!

There's a clear niche, mission, and goal I have now.

Many consistent TOC readers have seen me get totally nerdsniped by Decentralized AI. It started with the agent craziness in September and since then it's been a rabbithole that has fully hooked me.

I'll repeat my goal that I mentioned in a previous post:

My mission in these upcoming months is to become the crypto x AI guy.

I want to be the subject matter expert that glues both of these sectors together by understanding what's happening at the frontier of open source AI and decentralized AI.

In order for this to happen, I need to be reading a lot more research papers and books. That's the only way I can become a true 1% subject matter expert on DeAI.

I've "maxxed out" how much I can learn from scrolling through other people's thoughts and basic blog posts. If I need to form novel insights, it's time to update my inputs.

This means intentionally sitting in the silence and reading. And then reading some more. In fact, the reading I'm doing should hurt my brain. It should feel challenging.

I won't lie. The 30 page arxiv pdfs feel intimidating. I mean, there's clearly a reason it's so hard to become the top 1% in any field right? There's only so much you can learn trying to get by with executive summaries.

But there's clearly ways to get rid of that fear. I don't have to go down new rabbitholes the same way I did before.

I couldn't help but notice how slow my learning rate has been the past few weeks. It felt a bit pathetic. Like why is it taking me so long to get through topics x, y, and z? And that honestly felt discouraging and made me question this whole DeAI thing for a bit. Maybe I'm not the right person.

And then on a walk, I had the most obvious epiphany. Why am I not AI maxxing? Don't get me wrong, I use chatGPT just as much as the average joe on tech twitter. But if my job is to literally research, I should be doing everything I can to work smarter and expedite my learning process.

So last week I bought the $200 OpenAI deep research subscription.

There's no excuse for me to have extended timelines on learning new material. It's cope. There's a hammer available to me but I'm still banging the nail with a rock.

The goal is to learn the smart way and be fast about it.

Those who quickly adapt to the new methods of consuming and learning information will have a headstart on the way things are headed. And it's clear that even a few months of using these tools before others is enough to make the margin larger than most of us realize.

It's only been a few days and I'm already loving this new deep research experience. I'm getting through material wayyy faster. For example, in just two days I was able to go through all 3 DiLoCo papers on the docket. This would have normally taken me at least a week.

And yesterday, I prompted deep research to build me an entire primer on the open source AI side - key companies, metrics, business models, etc. I basically started with one tab and let deep research guide me through the maze.

On a recent Dwarkesh episode, Satya Nadella mentioned something that I literally can't get out of my head.

The key skill is not research anymore. Rather it's having the big picture framework in your head and being able to make quick decisions on what the most critical thing to learn next is.

You point in the right direction and let AI shine the light.

Another thing to note. If you're worried about prompting and making your money's worth. Even that's not an excuse anymore through multi-step prompting!

Bucco has a fantastic template I've been using to get started and the results have been outstanding. Over time, I'll of course slightly tune this to increasingly fit my needs.

BuccoCapital Bloke

@buccocapital

People were curious, so here's how I'm using Deep Research. I'll walk through the prompting and then an example:

1. First, I used O1 Pro to build me a prompt for Deep Research to do Deep Research on Deep Research prompting. It read all the blogs and literature on best practices…

4,487

7:50 AM • Feb 15, 2025

And like clockwork, just yesterday, the legend himself once again dropped the perfect video at the perfect time. I'm going to be going through this over the weekend and want to be using LLMs like Andrej. Why am I doing less than 1 prompt a day while Andrej is saying he's constantly using it in his workflow?

Andrej Karpathy

@karpathy

New 2h11m YouTube video: How I Use LLMs

This video continues my general audience series. The last one focused on how LLMs are trained, so I wanted to follow up with a more practical guide of the entire LLM ecosystem, including lots of examples of use in my own life.

Chapters…

8,069

5:41 PM • Feb 27, 2025

I highly recommend all of you to read this tweet by David Perell - it's incredibly well written.

David Perell

@david_perell

This AI boom has set off an existential crisis in me.

Some background: I’ve been teaching writing for the past six years. In that time, I developed frameworks for how to write well and a reputation as a good teacher to learn from. Partially because of the AI wave, I decided to…

2,587

4:52 PM • Feb 24, 2025

Since I started actively writing in the crypto space 4 years ago, I've always considered my job to be the guy who breaks down technical concepts. Read whitepaper, translate to english, and provide some fun context around the new subject.

But it's becoming clear to me that doing "deep dives" are becoming increasingly futile.

The amount of expertise required to out-do an LLM is rising fast. For example, the quality of a well-prompted, ChatGPT Deep Research report is already higher than what I can produce in a day's worth of work on almost any subject.

It feels like a waste of time for me to break down any whitepaper considering all of you have an on demand custom tutor that can explain it any way you'd like.

I know ChatGPT has been around since the end of 2022 but it only recently has started feeling like the tools have gotten so good that they're worth it for most complicated research now (personal opinion of course).

If that's the case, then what's the moat for writers like me?

The question is: What kinds of non-fiction writing will continue to last? Here’s a heuristic: The more a piece of writing comes from personal experience, the less it’s likely to be overtaken by AI. Personal writing, like biographies and memoirs, aren’t going away anytime soon.

That's because people have data about their lives that LLMs don’t have. Having a unique perspective helps too. This is Peter Thiel's famous interview question: "What very important truth do few people agree with you on?” If you have an idiosyncratic way of looking at the world, you don't have much to worry about.

The common thread here is humanity. People are also interested in people. Their stories, their struggles, their emotions, their drama, their unique insights into how the world works.

To me, it seems like 3 things are worth focusing on and getting really good at:

1. Being as authentic about my learning journey as possible. Sharing all the highs, lows, frustrations, obscure epiphanies, etc.

2. Getting really good at asking unique questions and being able to articulate insightful opinions / takes as effectively as possible.

3. Curating the best takeaways from the most niche content in my vertical. Finding the gold nuggets that most people don't have time to come across.

So what does this mean in practice?

My guess is that the north star metric now goes from # of posts published / week to # of takeaways provided / week. I know takeaways is a vague term. But I would define it as providing concise, meaningful commentary on something I researched or consumed.

I imagine that some of my posts may look like Byrne Hobart's weekly longreads format or Packy's weekly dose of optimism. These kinds of articles will force me to focus on increasing the quality of my content inputs and help me train the active reading muscle. Meaning, I'm actually elaborating on ideas proposed in a blog post or providing counter-arguments to a segment of a podcast episode.

In all honesty, I'm not exactly sure what this directional change ends up looking like in the posts. BUT! What I do know for a fact is that I'm going to be treating my writing that I send out less as deep dives and more as updates on my learning journey. They may feel like the same thing but I believe the subtle difference is actually huge.

I don't just want to explain things I'm learning. I want to seriously feel passionate about what I'm doing and convey that enthusiasm through text. All of you aren't just reading a newsletter covering decentralized AI but rather joining me on an intellectual journey that resonates with you.

For example, I was hesitating to send this post out because I felt a bit cringe about sharing "my crisis" and "lessons I'm applying". In my head, the content wasn't technical so I thought what's the point?

Wrong!

If anything, my guess is that these kinds of posts will resonate the most with all of you because they're thoughts that you simply can't reproduce with ChatGPT. This write-up was a direct result of my crisis that I had the last two weeks and how I got through it.

That's it for today's post.

I hope all of you have a great weekend and touch some grass!

I'll see you all next week 🤝

- YB

Welcome to the 25 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Hi TOC fam, happy Friday!

Great news. I'm really starting to understand this decentralized AI stuff.

Not saying that I'm a subject matter expert just yet, but I've been locked in the last two weeks on all the material I can possibly find on this vertical and have been reading non-stop.

I was talking to my friend (and TOC subscriber!) Derek from Collab Currency about how there's probably less than 50 people in the world who actually care about DeAI. He said something that hooked me even more..."there's a huge asymmetry between attention and fundamentals. Maybe one of the largest I’ve seen in my career" .

We also discussed how it's only a matter of time before the traditional open source AI community realizes they'll have to depend on crypto for scaling their models. In my Crypto enabled accelerationism bubble post from November, I mentioned the following:

Crypto needs its "poster children".

The real fun will start when the cream of the crop developers and researchers from other tech verticals take note that their chances of success are higher through this new crypto-agentic enabled model.

DeAI will need its "poster children" to showcase to the rest of the AI world that these experiments actually work at some reasonable capacity. Projects like Nous and Prime Intellect "de-risks DeAI quickly if others can see these ideas in production".

And it's clear that we're getting close.

For example, this is a timeline of released models kept up to date by Hugging Face. It was cool to see that they added in Hermes 3 by Nous (check the August 2024 column).

And in a recent interview, Dylan Patel (founder of Semianalysis) mentioned the following:

Ronan

@Ronangmi

@dylan522p (leading AI researcher) was asked about what spaces in the AI startup world he is is excited about.

his first answer?

distributed training and inference. in particular, @NousResearch and @PrimeIntellect

179

1:28 AM • Jan 22, 2025

Also, it's worth noting that the speed of shipping from these DeAI teams is increasing a lot more quickly than people realize. Just in the last week...there were announcements from:

• Prime launching SYNTHETIC-1 dataset

• Bittensor going through its huge dTAO upgrade today

• Nous launching DeepHermes-3

I won't get into the details of these today as I don't think any of them are time sensitive (there will be extreme volatility and sell pressure on the Bittensor subnet tokens at the beginning) so we'll save them for next week.

With that being said, let's dive into today's post.

Last Friday, I gave all of you a framework on how to think about crypto x AI. Here's a refresher:

Today, we're going to zoom in on the bottom-left quadrant and breakdown the decentralized AI efforts happening.

There were 3 main reads that were game changers in terms of getting me up to speed on DeAI. They're technical and dense but I'll do my best to help all of you understand the overarching narrative and the key points to keep in mind.

Here are the posts I'm referring to:

1. Decentralized Training by Naman Kapasi

2. Scaling through Decentralization by Ronan

3. Frontier Training by Sam Lehman

Let's dive in.

At its core, decentralized AI is not a new concept. The idea is to basically build a world computer (sound familiar?) that can train a state of the art (SOTA) model that has no central node and is fault tolerant.

It's worth remembering that Bitcoin is the world's largest supercomputer by multiple orders of magnitude. We've technically proved it's possible to build a decentralized network that combines compute + economic incentives + utility. If we can do it for "digital gold", why not AI?

Of course, there will be a different set of challenges just like Ethereum vs Bitcoin. But these ideas are all variants of each other serving different real world assets (money, programmability, intelligence).

The big unlock that slowly formed from 2017 (release of transformers paper) to 2019 (gpt-2 launch) was that it's possible to make these "assistants smarter" by adding more compute and scaling up the underlying models.

This marked the start of the GPU gold rush and the AI space started shifting to being more closed source as pre-training became the competitive margin.

And since chatGPT launched in 2022, we've seen unfathomable numbers on how much the largest tech companies are spending on data centers (i.e. Meta, xAI, Microsoft, Google).

This Dylan Patel piece on how much goes into these data centers on the backend and how the hundreds of billions of dollars will be spent.

Now the key part to understand is that it's not just about who has the most number of GPUs. Rather, the north star is how well these teams set up their data centers to maximize efficiency. This is can be calculated by:

MFU (model flop utilization) / PUE (power usage effectiveness) = total cluster efficiency

This accounts for GPU failures, continuity of systems, etc. For reference, Llama 3 had a MFU of ~40%.

As these models get exponentially larger, these optimizations become crucial. This leads into the topic of Parallelism which allows model training to happen in parallel.

There's 3 main types: data, tensor, and pipeline. I won't go into detail here but just know that most of these big tech data center setups use a combo of all three known as 3D parallelism.

This brings us to DeAI's first challenge which is distributed training. Centralized data centers have the advantage that their hardware is co-located so GPU communication is very fast.

Nvidia NLINK connects GPUs with speeds of 1800 GB / sec while a normal internet speed is ~500 MB / sec.

If you don't know how pre-training works, here's an eli5 of why GPUs need to communicate.

Let's say you have 10 data sets that you need to train the model with. After each data set, the model needs to update and adjust based on how poorly it did (loss function). You may have heard of gradient descent before? Basically, the goal is to iteratively bring the gradient down after each data pass.

Now, remember, there are tens of thousands of GPUs that all need to sync up after each pass...you can imagine how that gets heavy quickly.

So, the main question for distributed teams becomes: how do we reduce the communication needs?

Is there a way to not have every single GPU sync up in the system after each run?

Four parts in this section.

Prime & DiLoCo

In my opinion, the key breakthrough for distributed training was when Google released their DiLoCO paper in November 2023. @Ar_Douillard is a fantastic follow to keep up with updates here.

The key learning from that paper is inner-outer optimization which reduces GPU communication needs by 500x!

Inner refers to a single node of GPUs making quick, local updates. Outer refers to a less frequent system wide updates between nodes. Think: intra-node vs inter-node.

From here, the PrimeIntellect team decided to implement this paper at scale. They used the Hivemind library and published OpenDiLoCo which also included a fault tolerance mechanism known as the "heartbeat". Basically, if any hardware didn't send a beat it would be removed from the system. This enables hardware to come in and out of the network.

They launched the PRIME-INTELLECT model in November 2024 which was a 10b parameter model trained on Open DiLoCo. It's amazing to see that @vincentweisser and team were actually apply this Google research at scale. This model release is a "poster-child" moment for DeAI.

Nous & DeMo

The second approach is led by @NousResearch and their DeMo & Distro paper. This method focused on decoupled momentum optimization. Remember how we discussed the eli5 on changing gradients after every data pass?

I won't get into details here but optimizers are used to update the model weights to minimize the loss function (margin of error).

Most training methods today use the AdamW optimizer which was released back in 2014 by Diederik Kingma.

Kingma worked with the Nous team (@bloc97_ & @theemozilla) to improve the AdamW optimizer and use discrete cosign transformation (DCT) to decouple fast and slow momentum changes.

The core concept here is that it's possible to split the importance of gradient changes into fast & slow. There are some changes that need to be immediately communicated and others that can be done over time.

It turned out that the gradient compression solution ended up being as good as if not better than models that just used the AdamW +allReduce optimizer. And most importantly, there was an 857x reduction (4-5 orders of magnitude) in communication needs!

The Nous team also announced their 15B parameter model in December 2024 - the second poster child for DeAI.

SWARM Parallelism
The third main approach is SWARM parallelism which heavily relies on pipeline parallelism. You know the classic picture of a neural net which has columns of circles that go from left to right? Each of those columns is a layer and pipeline parallelism basically splits the training vertically by layers.

So some GPUs are focused on the initial inputs, some are focused on the middle blackbox layers, and others are focused on the weights and layers closes to the output.

As models get super large, this approach is fantastic as it removes the GPU RAM bottleneck.

However, as Sam puts it concisely, "the key innovation with SWARM is their approach to handling the flow of data through the network of devices in a messy training network".

Basically, the architecture manages all the different kinds of hardware (that all have separate compute power) during a run.

I still need to dive deeper into how the routing mechanism works, but one of the most interesting discoveries by @m_ryabinin, @Tim_Dettmers, and team was the square-cube law of distributed training which notes that compute time grows much faster than communication time as model sizes increases.

This is a huge win for distributed model training because the biggest bottleneck of quick GPU communication becomes less important.

Non-Transformer Architecture Routes

I haven't looked into any of the following but just noting as Naman included it in his post. There's some non-transformer related architectures also trying to make progress in this vertical. Some examples he lists:

- Mixtral

- Switch transformers

- DiPaCo (distributed path composition)

All the approaches discussed above in reducing GPU communications are basically different optimizations on the current centralized pre-training process.

The part that stood out to me most - and something I think should be the key takeaway of this post - is that the real magic will come when these approaches are combined together to immediately 100x or even 1000x the training efficiency.

For example, Distro + DiLoCo or SWARM + DiLoCo.

It seems like the teams are actively exploring each other's works and we'll probably see a lot more these optimization permutations in 2025.

One big call out here is making sure to differentiate two terms I see incorrectly interchanged. Distributed just means the hardware is not co-located...even big tech companies like Microsoft are working on this.

Decentralized specifically means that there's no central node and the training process is fault tolerant - exactly what the Bitcoin network preaches.

So what are the specific needs for decentralized training to happen?

This gets into the topic of security, encryption, and verification.

Again, details are out of scope rn but wanted to include a few examples that Sam included in his post:

- Zero knowledge proofs (@ezklxyz)

- Fully homomorphic encryption

- Multi party computation

- Trusted environment executions (@PhalaNetwork, Flashbots, @sxysun1)

Incentive Alignment

I've compared decentralized AI networks to Bitcoin a couple of times in this post.

It's worth noting that the same financial incentive mechanisms will need to apply here as well.

- slashing mechanisms to penalize malicious actors

- huge reduction in up front cost with hardware providers taking a bet on the long term revenues and appreciation of network ownership

- network effects as markets form around a liquid model token

@_AlexanderLong from @PluralisHQ has some great insights here on protocol models (post linked below as well).

Also worth noting that Nous Research recently announced Nous Psyche which aims to bring the verification and incentive mechanisms in partnership with Solana.

Since the Deepseek craziness from a month ago, the next big thing in AI seems to be researching new reinforcement learning (RL) techniques and using chain of thought (CoT) to let the models learn from the current context.

Deepseek showed us that it's possible to match current model performance benchmarks without the same hardware requirements by doing other kinds of optimizations.

We can go into a lot more depth here, but for the scope of this post I want to call out the fact that if in fact the next big thing in AI is moving from pre-training scaling to RL & inference time compute then it seems like the uphill battle of compute constraints that decentralized AI faces somewhat goes away.

I'm not well versed here so don't want to make any claims just yet but Ronan had a fantastic sentence in his post I wanted to copy over:

"The newest vector to scale model performance — reasoning and inference-time compute — naturally enjoys this described communication reduction. There is no inherent disadvantage to a distributed approach: the importance of this paradigm shift for distributed (and decentralized) training cannot be understated."

That's all I have for today's post!

I hope all you have a great weekend and I'll see you next week 🤝

- YB

Welcome to the 6 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Hi everyone, happy Friday!

Imagine you've had your eye on this awesome puzzle for a while, and you finally decide to get it. It's on the table in front of you. All the pieces are there. You have your coffee ready and some background music playing. No one's in the house. Just you and this puzzle.

There's only one problem. IT'S SO OVERWHELMING. Where do you start? Am I stupid...why aren't any of these fitting? Ugh, should I have just stuck to watching a movie?

But then, you calm down and think logically. Okay, first let me do an initial sort of all the pieces based on which quadrant they fall in. And then I'll start connecting the low hanging fruit so I can have some small wins. And so on.

This is basically how my past week has been.

The puzzle that's been frustratingly delightful is called "Decentralized & open source AI".

The true TOC fans may have noticed that I didn't send my usual Tuesday post. Well, that's because I hadn't fit together any of the pieces by then and decided it would be dumb to draft a half ass piece and waste all of your time.

But, fortunately, on Wednesday and Thursday I had some luck and I've finally given this puzzle some shape and life. However, to be totally transparent...I'm not done with the puzzle and it might take a bit longer than I thought which I'm okay with as long as I'm making progress.

My mission in these upcoming months is to become the crypto x AI guy.

I want to be the subject matter expert that glues both of these sectors together by understanding what's happening at the frontier of open source AI and decentralized AI.

This means depth and breadth - I don't want there to be a single thing that is past me in this vertical.

For today's post, I want to share my framework on how I'm approaching this goal. Below is the "puzzle quadrants" that make the most sense to me and brief thoughts + a todo list for each section.

1. AI fundamentals: It's not that hard to catch up

2. Open source AI community: How far behind is open source?

3. Decentralized AI: What's the golden basket?

4. Open source history: What are the key learning lessons?

Let's dive in.

I started this week by attempting to draft a post on Nous Psyche. Obviously, I started by going through the docs and even managed to understand most of it at a high level.

But I didn't truly get it.

So then I decided to read the Nous Distro paper thinking it might help me. And even that - with the help of ChatGPT - I was able to understand at a high level.

But once again, I didn't truly get it.

It was clear to me there was an AI knowledge gap. There's no way I could have novel insights without understanding fundamental AI concepts.

So, I decided it was time to go off into the deep end.

I started with Karpathy's famous talk.

After taking notes on this, I already felt a huge boost in confidence. A lot of the terms that I had read and heard on Twitter / podcasts started making more sense.

And then, as a math person at heart, I decided to understand how neural networks and transformers work at a more deeper level. So, I binged the entire 3blue1brown series on LLMs.

By this point, I was ecstatic. So many of the AI concepts started clicking. If you're anything like me, you'll understand how annoying it is when you don't understand the entire stack of a new concept (not there yet but finally in the rabbithole).

YB

@yb_effect

It’s actually insane as to how quickly you can get up to speed on basic AI fundamentals by simply watching the @3blue1brown neural network series and @karpathy intro to LLM video (he published a new one today that I need to get to)

25

3:32 PM • Feb 5, 2025

And then! It's as if the tech gods were listening to me. Right after I finished those videos, Andrej Karpathy drops this 3.5 hour video on everything you'd possibly want to know about LLMs at an intermediate level. His first video in several months came literally at the perfect time.

Believe me when I say this...if you are feeling AI imposter syndrome, I promise this video will single handedly cure the problem. I'm only 2 hours in (going really slow + taking notes) and I can already say this is one of the most amazing tutorial videos I've ever watched.

YB

@yb_effect

going through it rn and can’t believe this is just free content for everyone

1

1:23 PM • Feb 6, 2025

It was super helpful to see the tools/resources he was using throughout the video as well:

• FineWeb: basically the "internet data" compressed for you through crawlers

• Common crawler: open repository that's used to scrape all the internet data

• Tiktokenizer: select a model and you can covert between plain text and tokens

• BBY Croft: fantastic LLM Visualization tool to understand the training process

• GPT-2 from scratch: Karpathy's repo to do everything from ground up

• Hyperbolic: access pre-hosted models without any setup

• UltraChat: synthetic data improvements repo for post-training process

• Nielsen's textbook: follow 3blue1brown examples and get hands on practice

After finishing the last hour of the LLM tutorial above, here's the upcoming agenda:

• Familiarize myself with Hugging Face

• Follow the ChatGPT-2 tutorial and run it from scratch

• Briefly go through both the Llama & Deepseek papers to understand open source SOTA models

• Read through Leopold's situational awareness essays

Just to clarify, the AI fundamentals section is one that requires a larger ramp up at the beginning which is where I'm at now. Once my base knowledge clears up, then it's more of just keeping up with the latest papers and releases. No different than the rabbithole you have to go down when first learning about crypto.

I know there's been a lot of recent hype around Deepseek and open source, but I'm still trying to figure out where exactly we are with open source AI developments.

Fortunately, Lex Fridman's podcast episode this week introduced me to Nathan Lambert and his work with Ai2. Nathan has been an open source AI advocate the past few years and writes a fantastic substack called Interconnects that covers many of the happenings in the OS AI world.

And just yesterday, he published a post on why he thinks the recent Deepseek news should be a huge wake up call for Americans to invest even more in open source.

Making the U.S. the home for open-source AI

Open-source AI is here to stay, but it is not a given that it will be American.

https://www.interconnects.ai

The core point was that in the last 30 years, China has just been copying western tech and improving the margins. But in this current AI race, it's clear that they are trying to be the ones spreading the innovations. So if U.S. companies don't make the effort to open source their models, the rest of the world (including Americans) will be quick to adopt Chinese tech.

The section that was a reality check in the essay was this:

Building strong AI models is far, far easier than building a sustainable open-source ecosystem around AI.

Building a better, truly open ecosystem for AI has been my life’s work in the last years and I obviously want it to flourish further, but the closer you are to the core of the current open-source ecosystem, the more you know that is not a given with costs of doing relevant AI training skyrocketing (look, I know DeepSeek had a very low compute cost, but these organizations don’t just fall out of the tree) and many regulatory bodies moving fast to get ahead of AI in a way that could unintentionally hamper the open.

Yes, efficiency is getting better and costs will come down, as shown with DeepSeek V3, but training truly open models at the frontier isn’t much easier.

Specifically, "the closer you are to the core of the current open-source ecosystem, the more you know that it is not a given with costs to doing relevant AI training".

Look, I'll be the first to admit that I have no idea what's actually going on in the open source AI world. But! I have to say that I was surprised that there was no mention of crypto whatsoever from my readings this week by OS AI researchers like Nathan and Tim Dettmers.

And I know I know. They don't take the crypto industry seriously. Scams, grifts, blah blah blah.

But fuck that.

As I was reading Nathan's essay, I couldn't help but notice the core issue he was presenting was a cost one. And if that's the case, then to me it's a no brainer that crypto incentives could enhance open source research big time.

So, is it that these guys have already considered crypto and came to the conclusion that it's not worth the efforts? Or is it more of an avoidance to the crypto space in general?

If the former, then I'd like to see examples. And if the latter, then that's a blind spot they have that I'd like to double down on.

Anyways, I've barely scratched the surface in terms of understanding the open source AI landscape but Lambert's work was a great start.

One thing that was painfully clear to me is that these OS AI guys are actually preaching the exact same thing as folks in the crypto world. I mentioned it in last Friday's post, but the open source AI challenge is truly so similar to Bitcoin that it's a no brainer these two communities (crypto and open source AI) need to be collaborating more and more. Hopefully, I can help bridge this gap.

Some checklist items for this quadrant:

• Watch Lambert's talk on open source AI that he gave to Harvard Law

• Understand what Ai2 does and their progress so far

• Find companies and researchers similar to Nathan/Ai2 and get a big picture understanding of the state of open source AI (create Twitter list as well)

• Understand the different kinds of licenses and their impacts (i.e Amazon has to pay Meta for Llama but Deepseek is MIT license and more "free")

• Form a thesis on the current state of OS AI from the perspective of Lambert type researchers. Try to understand the biggest bottlenecks and what solutions they think will work (keeping crypto bias aside)

To start this section off, I recommend everyone take 10 minutes to read this post on why AI needs crypto specifically. I've already covered the core thesis in previous posts, but I think Daniel does a fantastic job of really laying out the past, present, and future.

Why (Good) AI Needs Crypto - Variant

Open source AI combined with crypto leads to better AI by enabling larger models and driving more innovation.

https://variant.fund

He nails the point about how open source AI has a resource problem and why crypto solves for that.

YB

@yb_effect

good read by @dbarabander on crypto x ai:

- It's better to compare open source AI to Bitcoin rather than to Linux. Both are software projects that require massive amounts of resources & hardware to function

- OSS contributors need to give time + compute & data

- almost…

12

7:20 PM • Feb 4, 2025

One thing that caught my eye was the folks that helped review and edit the essay. The thanks section gave me a solid list of companies to start off with in terms of breaking down the decentralizedAI sector once I brush up on AI fundamentals. Note: I'm aware there may be some bias considering Daniel works at Variant but helpful regardless.

A question that has been top of mind for me recently is how aware are the folks in AI of decentralizedAI (what we would consider crypto) companies?

I don't have an answer for you just yet, but I'll admit that it was pretty damn cool to see Andrej Karpathy use Hyperbolic in his new LLM tutorial video I mentioned above. A few years ago, I remember having a call with Jasper (founder of Hyperbolic) when seemingly no one cared about crypto x AI, and it's so cool to see the team's hard work pay off.

Hyperbolic

@hyperbolic_labs

We are honored that Andrej Karpathy @karpathy has recognized Hyperbolic as his favorite platform for interacting with LLM base models. In his latest deep-dive video on Large Language Models (LLMs), he also commented that “Hyperbolic is the only place that hosts my <3 Llama 3 405B…

483

2:57 PM • Feb 5, 2025

You may be wondering...YB why is it taking you so long to understand these DeAI companies? Well, like I mentioned above with Nous Psyche, I'm bottlenecked by my AI knowledge. For example, 48 hours ago, I wouldn't be able to understand what this tweet below even meant.

Andrej Karpathy

@karpathy

afaik Hyperbolic is the only place that hosts my <3 Llama 3 405B Base, and in bf16 precision. So thank you :)

612

2:33 PM • Feb 5, 2025

But! I can confidently say that as I wrap up my AI fundamentals crash course, I'll be able to speed through all of these companies and form a thesis on them over the next 2 weeks.

My goal will be to create a golden basket of DeAI companies. If I could angel invest into just 5 of these startups, which ones would they be and why? And then my plan is to become the biggest hype man for these teams. Two of them that I already feel like may be on the list are Nous and Prime as I've mentioned them several times in my posts the last few months.

Teng, a friend and fellow crypto x ai researcher, is doing a fantastic job of covering these companies in his newsletter and I'm excited to start going through his primer as well. Check out Chain of Thought if you haven't already, its a must read!

At the end of the day, the thesis for DeAI is as follows. Our job is to make this a reality.

Bharat Krymo

@krybharat

The next AI X Crypto wave is going to be driven by real AI builders leveraging crypto rails and not crypto native grifters slapping AI on their token slop.

220

8:25 AM • Jan 31, 2025

With that being said, here's the checklist for this section:

• Go through Nous, Prime, & Hyperbolic to get started next week & publish Tweet summaries

• Read through Ronan's piece Can decentralized AI compete?

• See if other DeAI companies are talked about and/or used by AI researchers (i.e. Hyperbolic-Karpathy type examples. I know Nous is well discussed, but checking for others as well)

• Start reading through the resources in CoT's primer

• Dive deeper into what Teleport and Nous are working on with TEEs

• Draft my own thesis on why crypto needs AI and create the golden basket

And finally, open source.

I'll keep this section short. Technically, it's not a requirement but I think by spending time learning about the history of open source, I'll have a much better grasp of why the fight for DeAI even matters in the first place.

The truth is that I'm not old enough to remember the Linux days or early 2000s era of computing when open source was the norm. I grew up in the FB / Twitter / Uber era and centralized platforms have always been the default for me.

That's why I want to better understand what happened in the past with open source and what I can learn from those examples.

The other day, I was listening to the BG2 podcast, and Bill Gurley was comparing Meta's Llama strategy to what MongoDB and others did back in the day. I thought that was fascinating and I really want to understand the nuances there. Many OG Terminally Onchain readers know that I'm obsessed with tech history, so this quadrant is really scratching my itch to make obscure comparisons from the past to what's happening now.

I think this will help me not only discover unique insights in this vertical but will also help me feel philosophically more aligned with becoming a subject matter expert on crypto x AI.

YB

@yb_effect

started this today

30

8:48 PM • Feb 3, 2025

• Read Working in Public

• Read Cathedral and Bazaar

If you made it this far, I'm guessing you are just as passionate and excited about the DeAI vertical as I am. I purposely hid this sentence at the very end, but reply to this e-mail with your TG handle if you'd like to be added to a TOC chat where we can discuss all the topics / resources mentioned above. I haven't made the group yet, but if I get interest from even a few excited folks, then I'd love to make the chat so all of us crazies can help each other out and have fun.

That's all I have for today's post!

I hope all you have a great weekend and I'll see you next week 🤝

- YB

Welcome to the 51 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Happy Friday TOC fam!

Since Tuesday's post, I've been out and about. Lots happening in NYC this week. Normally, I try to avoid conferences or events because of how draining they can be, but I was excited by the line up this week.

Here's the rundown.

On Tuesday, I went to the Archetype Agent day where friends from Pond, AICC, Coinbase, Clanker, and Tenbase gave presentations on what they're building and how they think the agent vertical progresses. To be honest, the speakers were great, but content wise nothing really stood out to me. I didn't come out of agent day with a takeaway that I was excited to share with all of you. However, the presentations did reassure some of my takes I've shared here on TOC the last couple of weeks (gaming, TEE, security, etc).

On Wednesday, the roles were reversed. I was invited by VectorDAO to give a presentation on crypto x AI at their monthly lunch 'n learn. I was pretty happy with my rundown. I specifically didn't want to make slides but instead created this primer that I want to share with all of you as well. Think of it like a quick overview on the crypto x AI space with bullet point takeaways and relevant links to my posts.

VectorDAO | Terminally Onchain Presentation (Crypto x AI)

Terminally Onchain by YB Onchain strategy deep dives every Tuesday & Friday Newsletter | Twitter | Farcaster Crypto x AI: VectorDAO How did we end up here? Open source anons on Discord Jailbreakers Decentralized AI AI hackers + Crypto coordinators Smart wallets, stablecoins, & ...

http://docs.google.com

And yesterday, I was at the Nous x Solana event to learn more about the Psyche launch which is bringing some of their training efforts onchain on Solana. There was a panel with folks like Shaw from ai16z, somewheresy, and a few others. I wasn't the biggest fan of how the discussion was curated. Other than a few practical examples of jailbreaking that caught my attention, the rest felt a bit tooo philosophical and "up in the air" for my taste.

But I definitely enjoyed the other two talks. One was by sxysun who works at Teleport and is experimenting with TEEs in order to better understand agent autonomy. And the latter presentation was by Bowen Peng who is the chief scientist at Nous. He covered the Nous roadmap and covered what to expect with Distro and Psyche in 2025.

PsycheFan123

@karan4d

Rn @sxysun1 is giving one of the best presentations I’ve ever seen

48

8:23 PM • Jan 30, 2025

With that being said, let's continue this Nous thread and dive into today's post.

In Tuesday's post I gave a rundown of my thoughts on Deepseek and mentioned how it was a bullish signal for decentralized AI.

To be clear, this is also a huge win for anyone excited about decentralized AI. I'm not saying everything is solved now but there's some new found hope that the vertical's biggest bottleneck (centralized hardware clusters) might be getting smaller over time. Of course, the capital that the big dogs have is still going to pour into making their general models 10x better, but that doesn't mean distributed players can use less capital to focus on specialized, niche models.

To be honest, I thought I was done with that train of thought but then on Wednesday I kept going down the rabbithole.

Ben Thompson published this Deepseek FAQ which was helpful to understand the implications of the new model. The key takeaway, in my opinion, was in this section:

This blew my mind.

A bunch of researchers were given a hardware constraint (not having access to H100s) and found a way around it.

But! This was old news for the most part. A lot of researchers (clearly not me lmao) who were paying attention to Deepseek's v3 launch in December already had their "woah moment".

And that's when I realized...December of last year had a series of breakthroughs that were critical for open source & decentralized AI.

1. On November 29th, Prime Intellect announced a 10 billion parameter model that was trained from hardware spread across 3 continents

2. On December 2nd, Nous announced they pre-trained a 15 billion parameter language model over the internet using heterogeneous hardware (not just H100s)

3. On December 27th, Deepseek announced v3 which was trained in a centralized cluster BUT with H800s which lack the interchip bandwidth of H100s (what OpenAI, Anthropic, X use)

Now, you might be thinking..."YB it feels like you're stretching this whole Deepseek - DeAI link a bit too much". And maybe you're right. But, here's my counter.

All of the examples above showed that it's possible to train large and effective models without having the optimal hardware setup that American AI companies have. Optimal meaning gigantic, centralized warehouses of H100s.

I believe that the Deepseek R1 craziness this past week was less of a technical breakthrough (that was v3) and more of a mental breakthrough on the future of AI.

The R1 news cycle finally helped everyone realize that there may actually be a future of AI that is not solely dependent on OpenAI, Anthropic, Google, and the other 2-3 behemoths that have hundreds of billions of dollars to spend on compute.

It gave hope not only to the teams building distributed training processes, but also to the independent researchers and smaller enterprises that were restricted to approaching AI as to how big tech wanted them to.

And that's why my takeaway from all the Deepseek craziness is that it's time to start taking DecentralizedAI very seriously. Because it's only a matter of time before these projects hit an inflection point and the majority of people looking for AI solutions will start shifting over to solutions that provide more freedom and economic benefits on how they train and use models.

YB

@yb_effect

my takeaway from learning more about deepseek is that it's time to be extra bullish on @NousResearch and @PrimeIntellect

129

1:51 PM • Jan 29, 2025

Heck, let's take it a step further. It won't be long before people stop caring about the underlying models used. OpenAI's god like stronghold over the industry might start to slowly wither away as the availability and utility of distributed, open source solutions become more cost-efficient.

This time last year, the tweet below by Balaji would have been an absurd statement. Now, we're starting to see a real narrative shift on where value will move to next in the AI stack.

Balaji

@balajis

It might turn out that the GPT wrapper has more of a moat than GPT.

5,792

9:40 AM • Jan 30, 2025

The first moat of AI was the model/training layer. To continue breaking the walls down depends on three things:

1. Reducing the need for communication frequency between GPUs during training so there's no need to have one huge central node in the system

2. Being able to efficiently use multiple hardware solutions together in order to be less dependent on access to H100s specifically

3. Properly aligned economic incentives to make sure the independent nodes in the distributed training process are not degrading quality

Now, this may be obvious, but I can't help but point out the fact that the points above look exactly like the requirements that went into the Bitcoin whitepaper...

No central nodes. No dependencies on a single piece of hardware (and hardware provider). And economic consequences incorporated to enforce accuracy.

With that being said, it's not surprising that Nous - a company in the "AI trenches" - announced their partnership with Solana to build an end to end distributed, open source AI stack. To be clear, this is significantly different than Meta's Llama. With Llama, the weight are open source but Meta controls the training process, data, and hyperparameters.

Tarun Chitra

@tarunchitra

Nothing is more aggressively ambitious than @NousResearch announcing Psyche + end-to-end open source models (data, methods, gradients, not just final weights) on the week the world went crazy about DeepSeek

Imagine if quant funds are competing on Nous to make the best e2e model

275

1:10 AM • Jan 31, 2025

I haven't gotten a chance to finish going through the Nous Psyche docs so I'll save the details for Tuesday's post to better explain how exactly the Solana integration will happen.

But it's starting to seem that I have no choice but to understand the key technical implementations that teams like Nous and Prime are delivering.

Why?

Because I want be able to provide an accurate forecast to all of you on how I think the growth of DeAI looks like this upcoming year. What are the margins? What are the bottlenecks? And how can onchain verifiable states and tokenomics help accelerate progress?

Not only that, but I want to understand the open source AI lore more in depth as well. This week, I started reading the following papers to get better context:

1. Google's DiLoCo (distributed low communication) paper which was released in December 2023 and seems to be the major breakthrough of hardware optimization

2. The Nous DeMo (decoupled momentum optimization) paper which was released in March 2024 and a separate implementation to reduce inter-hardware communication

I wanted to end today's post with this video snippet of Dylan Patel (founder of SemiAnalysis and the goto semiconductor guy) who said the following:

"I think there's a lot of interesting stuff happening on the distributed training side like with Nous and Prime Intellect..."

Ronan

@Ronangmi

@dylan522p (leading AI researcher) was asked about what spaces in the AI startup world he is is excited about.

his first answer?

distributed training and inference. in particular, @NousResearch and @PrimeIntellect

177

1:28 AM • Jan 22, 2025

Apologies if today's post was more narrative driven and less rooted in technical details. Like I said earlier, I was out most of Wednesday and Thursday so this write-up was a bit last minute. However, I do think the core thesis in the section above is critical to understanding how the crypto x AI vertical progresses in the coming months.

I have a lot of reading ahead of me, but honestly feel so excited to get through all of these papers! The bull case is starting to get more and more clear for the parts of the crypto x AI stack that aren't strictly agent based.

Have a great weekend and I'll see all of you on Tuesday!

- YB

Welcome to the 22 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Sections below:

1. AI's Google S-1 Moment

2. Opens source for the non-technical

3. Coinbase listings uproar

Let's dive in.

This past weekend, the main character on tech twitter was obviously the Deepseek R1 model. If you were out touching grass, here's the 30 second rundown:

• DeepSeek (Chinese AI startup) launched the model DeepSeek R1 which matches or surpasses OpenAI’s o1 model in performance

• Open-source under the MIT License model

• The R1 model was developed for under $6 million vs the billions of dollars it cost OpenAI and American tech giants like Meta and Google

• Even the API pricing is significantly lower. $0.14 per million tokens compared to OpenAI’s $7.50

• Broader implications is that everyone is worried American AI is behind China's AI. And there were a ton of discussions around "it being over" for Nvidia.

Now, I'm sure all of you have seen countless reports, hot takes, and debates on the topic so I won't go too in depth here. Instead, I'll just share a few points from others that helped me form a better opinion.

Overall, even if you're bearish and think DeepSeek fudged the training cost numbers a bit, this is still a phenomenal achievement. I mean, the performance was on par for a fraction of the cost and the paper is out in the public for American companies to copy!

Initially, much of the conversation was centered around the fact that because DeepSeek proved it costs so much less to train a model, then Nvidia will take the biggest hit because there won't be a need for that many GPUs anymore. If you took one look at the market yesterday, it was clear that this opinion was reflected with Nvidia and semiconductors in general being down 15%.

But then Satya tweeted this which changed the narrative. Basically, if the cost of a technology goes down --> then it becomes accessible to more people --> which leads to increased usage of that tech --> and that slowly drives costs back up again over time. jEvOnS pArAdOx

Satya Nadella

@satyanadella

Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can't get enough of. en.m.wikipedia.org/wiki/Jevons_pa…

12.1K

12:48 AM • Jan 27, 2025

And to be honest, this feels pretty straightforward to me. This isn't unprecedented. It's happened countless times with prior technologies such as computer storage, fuel for transportation, and agriculture.

6529

@punk6529

14/ We have just gotten started on compute.

Like my friend's hard drive, the amount of compute we use today will look pathetically laughable in 5 years and again 5 years after that and will continue that way for the rest of our days.

98

5:20 PM • Jan 27, 2025

The two best tweets I saw on the matter were from Yishan and Zhiding Yu.

In one sentence, the takeaway was that Deepseek R1 does not have to be an extreme geopolitical matter.

Yes...obviously there are tensions between which country has more control over AI. But this specific moment of a Chinese company sharing their results and open sourcing the work has been dramatized into a war like narrative. Remember, the Deepseek model weights are all open source! Meaning you can go and use their model locally on your computer without having to use their app that the Chinese government may or may not be monitoring. In fact, Perplexity has already implemented the model into their product so you can use it there as well.

A bit long, but read this from Yishan:

After everyone has been sensitized over the H1BLM uproar, we are conditioned to think of OMG Immigrants China as some kind of Alien Other. As though the Alien-Other Chinese Researchers are doing something special that's out of reach and now China The Empire is somehow uniquely in possession of Super Efficient AI Power and the US companies can't compete. The subtext of "A New Fearsome Power Now Under The Command of the CCP" is what's driving the current sentiment, and it's not really valid.

Like, no. These are guys basically working on the same problems we are in the US, and not only that, they wrote a paper about it and open-sourced their model! It is not actually some sort of tectonic geopolitical shift, it is just Some Nerds Over There saying "Hey we figured out some cool shit, here's how we did it, maybe you would like to check it out?"

That last sentence was so real. Like why can't Deepseek R1 be a cool breakthrough that researchers are just excited to share with each other? I know you're probably thinking "YB you're so naive, this has CCP written all over it". And yea maybe you're right. But based on the facts I see so far, it seems to me that a bunch of smart researchers in China had an amazing breakthrough and shared all the details with the rest of the world. All major American players will replicate this in a matter of months into their training flows and we're back to an even playing ground.

As someone who loves learning the history of tech, Yishan's analogy of this Deepseek moment to Google's S-1 filing in 2004 made a ton of sense to me.

Basically, in that era, in order for companies to scale they had to buy larger mainframes (similar to buying more GPUs). But then Google came out of nowhere and fixed the issue by revealing that they didn't need to scale vertically anymore because they built the largest supercomputer through distributed networking.

Eventually, Google published their MapReduce and BigTable papers and everyone else in the industry followed suit. Of course, they had a huge competitive lead and didn't open source their findings right away.

Deepseek basically gave us the equivalent hardware reduction moment but also decided to open source how they did it from the get go.

Yishan

@yishan

I think the Deepseek moment is not really the Sputnik moment, but more like the Google moment.

If anyone was around in ~2004, you'll know what I mean, but more on that later.

I think everyone is over-rotated on this because Deepseek came out of China. Let me try to un-rotate…

4,360

11:48 PM • Jan 27, 2025

With that being said, what's the key takeaway here?

Deepseek R1 lets the small players finally compete and form their own wedges.

This snippet from Daniele sums it up:

Deepseek R1’s arrival underscores a pivotal shift: open-source AI no longer demands exorbitant compute or licensing fees. By offering robust reasoning at a lower cost, it paves the way for broader adoption, from small-scale dev teams to large enterprises.

To be clear, this is also a huge win for anyone excited about decentralized AI. I'm not saying everything is solved now but there's some new found hope that the vertical's biggest bottleneck (centralized hardware clusters) might be getting smaller over time. Of course, the capital that the big dogs have is still going to pour into making their general models 10x better, but that doesn't mean distributed players can use less capital to focus on specialized, niche models.

This is a half joke from Ansem but I'm sort of with him on the acceleration of open source AI.

Ansem 🧸💸

@blknoiz06

iight bros deepseek validates the thesis of open sourcing AI models & the acceleration of innovation in that space

we must determine how this is bullish for our decentralized AI bags immediately

training & inference? specialized agents? cmon bros its money szn

980

10:49 AM • Jan 27, 2025

Anyways, this is where I'm at with all of the Deepseek stuff. Overall, I think the hype will die down pretty quickly until we start seeing cost reduction data from American players with the new Deepseek training method.

Unrelated to Deepseek, yesterday a token called VVV launched and hit a $350 million market cap in a day!

The $vvv token is for a product called AskVenice that has been around since May '24. AskVenice is basically a ChatGPT UI but focused on privacy.

Here's the rundown:

• Venice makes it easy to use open source models for people who don't want to download from Hugging Face and run models like Llama locally

• Your requests are encrypted and the actual conversations you have only exist in your browser

• They host multiple open source models: Nous theta, Llama 3.1 405B, Dogge 70B, & a few others for image generation. Over the weekend, they added in DeepSeek as well

• 400k registered users & 50k DAU

• Venice uses multiple decentralized GPU providers, so it's not possible for any compute provider to have your entire history***

• The only thing Venice knows is your e-mail & IP address

• Started and run by Erik Voorhees, Teana Taylor, and a small team

• The token vvv is on Base and there's an airdrop for wallets holding Virtuals ecosystem tokens (i.e. aixbt, vader). Check the claim page here to see if you qualify (only 1 month left!)

• Worth noting that Coinbase listed the token on day 1 of it being launched. Not something they usually do, could be a signal of them leaning into the new meta. Imagine if Kraken listed vvv before them, would be a major flop

• Devs an access the API for $149 / yr which is the pro plan.

That's pretty much it. The product itself is simple - if you've used ChatGPT before then this isn't anything new. Rather it's the fact that the models you can pick are open source and uncensored + the key point that they're going for privacy first.

***BUT! I want to call out an important point in the marketing pitch that's a bit misleading.

This tweet below by Eric is a bit harsh but a really important callout in regards to the privacy part.

Notice how in the bullet points above, I mention the fact that Venice uses multiple decentralized GPU providers? Sounds great! But the key point worth emphasizing is that this means privacy in the sense that no one provider has the entire context on you. But, any single thread is available to the compute provider processing your request. So, if there's any sensitive information in one chat with Venice, that's fair game to be used against you in the same way that centralized players can.

Eric gives a solid counterexample of someone uploading their job offer letter that includes their name, salary, company, etc. that the GPU provider then has access to.

The only reason I noticed this caveat is because I actually went through the docs and found the mention in one of their blog posts. Venice's marketing needs to make that crystal clear for the average user!

YB

@yb_effect

Def agree, nothing to do w onchain. In terms of privacy, not having all conversations linked back to u is miles better than any provider rn.

But huge +1 to the point of making it more obvious that if there's anything sensitive that links back to you in a single thread, then it's…

2

7:57 AM • Jan 28, 2025

In regards to the VVV token above, many people were upset about the fact that Coinbase listed the token on the first day it launched. Specifically, the community was calling out the fact that $VIRTUALS (which at one point hit $4b mc) hasn't even been listed yet so this clearly feels like Coinbase playing the "favorites game".

I agree with that take for the most part. Look, I'll be the first to say that as a public American company, Coinbase faces the most headwinds in terms of regulation restrictions. But the Virtuals argument feels like a legitimate counterargument. It's less about the fact that Virtuals hasn't been listed yet and more so that there's no transparency on how the process actually works.

But, it seems like the Coinbase team is taking this a lot more seriously as hypertokenization is only going to increase over this year.

Jesse and Paul Grewal (Coinbase chief legal officer) are going to have a live discussion on the topic this Thursday, so I'll keep you all posted on what happens there.

jesse.base.eth

@jessepollak

I've spent the last few months in deep conversation with the @coinbase listings team on how they can better support and lift up builders, whether it's on @base or any other chain (L1, L2, everywhere)

There's a difference between what Coinbase wants to list, and what they're able…

paulgrewal.eth

@iampaulgrewal

The @coinbase listings team wants to list any and every token that lifts up builders, no matter what chain it's on.  But as a regulated exchange there are important differences between what we want to list, and what we are able to list. I know that's not always clear, and…

1,367

8:42 PM • Jan 27, 2025

That's all for today's post!

See you all on Friday :)

If you've been enjoying my content, please please share TOC with your friends in crypto...really trying to get to 10k subs asap!!

- YB

Welcome to the 38 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Hi everyone, happy Friday!

So much has happened in the past week that the GOAT launch feels like a whole cycle ago.

I don't know about you, but my brain feels fried.

Crypto bull markets are both a blessing and a curse. Great for the industry, terrible for your personal health 😂 I was supposed to go to sleep at 11 pm yesterday and found myself trying out a new app at 2 am (more on that below).

Will

@WClementeIII

The time duration between it's so over and we're so back will continually compress until we all reach a singularity of collectively losing our minds

1,548

10:35 AM • Jan 23, 2025

I also wanted to apologize to all of you for not sending out a post on Tuesday. I rarely miss a post (this is my second skip since August), but I was pretty sick all of this week and just had too much brain fog and a lot of NyQuill in me.

What I want all of us to do today is take a step back and build a framework on how we should be thinking about this space for the next 6-12 months.

Do you ever feel like even after doing your best to pay attention, you're still behind? Don't worry, you're not alone.

The truth is, it's tough to keep up when the metagame is constantly rotating. Not only in terms of the micro bull and bears of the market but also the actual topic and narratives.

jacob

@js_horne

a meta a day keeps the stagnation at bay

15

9:14 AM • Jan 24, 2025

So I thought to myself, I think it's best if we don't think of the "metagame rotation" as something we blindly run after without context as to how it fits in the bigger picture.

That way, whenever we see something new...our first thought should be "okay so where does this fit into crypto map?".

Obviously frameworks themselves change and we have to make sure to update them. But let's get one started for 2025.

Now, one thing I want to clarify is that there's no such thing as a "right framework". Everyone has their own perspective. Maybe you agree, maybe you don't. This holy trifecta I'm discussing below is how it's making sense for me right now, so I'll do my best to explain why.

The 3 buckets that will matter:

1. UI/UX

   • Agents / DeFAI

   • EIP7702 & Wallet modules

   • Mobile

2. Hypertokenization

   • Stablecoins go parabolic

   • RWAs are no longer a joke

   • Long tail of tokens

3. Hardware Coordination

   • AI x Crypto infra layer

   • DePin's time in the spotlight

Let's dive in.

Agents & DeFAI

Look, I'm sure a ton of stuff we're seeing in regards to crypto agents is a bit overhyped right now because of prices, but I can confidently say this isn't all just vaporware.

I've said it several times in the past few months: even though most of the projects in the agent vertical will die off, the few that make it through will have a serious impact on crypto. This is no different than what happened with defi and NFT projects.

The biggest bull case from my perspective is the agent layer settling in between the chain and interface layers. Meaning, actions that all the OG crypto users are used to in terms of interacting with smart contracts will start to feel archaic quicker than you think.

As I mentioned in a previous post:

Similarly, as Onchain AI infra improves, we'll be shocked by how we can type anything in the action bar and the results will be receipts saying task x has been done with a link to the proof (i.e. transaction).

tl;dr: the UI that we'll get used to for interacting with the chains will be through agents.

Naval

@naval

AI is eating UI.

13.9K

11:33 PM • Jan 18, 2025

It's worth nothing that this isn't a "new revelation". People have been discussing this since the day after ChatGPT launched in 2022. But, as with any new tech, the right moment takes years of experimentation. Here's my friend Salvino saying the exact same thing but he was about 1.5 years too early.

salvino armati

@SalvinoArmati

we're all going to be creating and interacting with agents on a daily-basis

and i think we're about 6 months away from this

3

10:54 PM • May 15, 2023

Another thing I want to point out is that I actually think people still underestimate how much of a superpower it is that "crypto agents" have access to wallets they control and can use the chain to transact.

As I mentioned a few months ago when the agent vertical was starting to take off:

Now, I think the key point here to understand is that the internet of intelligence vision can only be implemented efficiently on crypto rails.

You need agents to be able to permissionlessly use APIs on the social layer, have ownership of funds, be able to transact, show proof of work for their tasks, and work effectively with other agents. This is where smart wallets, stablecoins, decentralized social, tokenization, etc. all have to plug in. By using traditional web2 infrastructure, we would be limiting the capabilities of these agents by a huge factor.

It won't be soon but eventually there will be a point where I believe the capabilities of onchain agents goes far beyond traditional agents because of the enhanced capabilities the onchain infrastructure offers.

And I directionally agree with ThreadGuy here. Crypto gets rightfully made fun of a lot. But I really don't think we're "all that behind" the AI folks who ridicule and dismiss the onchain agent vertical.

threadguy 👑

@notthreadguy

griffain is more useful today than the first agent openai just released kinda surreal

687

1:19 PM • Jan 23, 2025

Wallet Modules & EIP-7702

I hinted at the importance of this development in my last post, but it's starting to become clear to me that EIP-7702 will be one of the biggest changes to the Ethereum ecosystem since EIP-4844 (blobs).

To keep it simple, right now wallets are not extensible for the most part. EIP-4337 tried to change this but it required users to switch over to smart wallets and was a tough sell.

Now, with EIP-7702, we're basically getting the equivalent of a chrome extension store for wallets.

Here's some examples of modules that Rhinestone put together. Notice how it feels exactly like reading through different chrome extensions. I'm sure once a few modules start to gain attention, devs will rush over to the next gold mine of opportunity.

We'll do a deep dive into the technical specifications in a later post, but if you're interested check out more examples in this Georgios AMA.

Georgios Konstantopoulos

@gakonst

EIP7702 will 100x EVM chain UX.

We have built the most extensive demos and open source code examples for it so far.

AMA? Happy to help apps, wallets and L2s learn how to integrate.

436

12:53 PM • Jan 11, 2025

Mobile

This past week, I used two crypto mobile apps that were just fantastic.

If you haven't checked them out already, please go try Yapster and Clout. I'm out of Yapster invite codes right now, but go follow the Twitter account and you'll probably be able to grab one.

YB

@yb_effect

need more of this in crypto:

- mobile
- smooth onboarding
- crazy attention to detail
- clean UX
- feels like an app normies would use
- leans into hypertokenization & games
- beta mode / server overload bc of hype
- funny marketing

awesome job @yapsterxyz & @cloutdotme

57

8:56 AM • Jan 24, 2025

I actually wrote about Yapster on Tuesday as well, so I'm going to copy that tweet here for all of you to read because I seriously think EVERYONE NEEDS TO TRY THIS APP! In fact, I'm like 99% sure my tweet is the reason a lot of people caught wind of the game. So I really want to make sure all the TOC subscribers aren't late to this.

After playing the first 2 rounds, I can confidently say Yapster is one of the most fun crypto consumer experiences I’ve had and it’ll probably be the first real competitor to pump fun.

tl;dr is that pump fun is for traders and yapster is for…pretty much everyone else who enjoys memecoins & games.

The game

1. Players buy a ticket and submit a meme & ticker beforehand.

2. When the daily game starts, you vote on which memes you think will do the best.

3. At the end of the rounds, the players decide if the ticker should be deployed. If it’s deployed, half of the buy in pot goes to liquidity, other half is proportionally allocated to players.

My thoughts:

- HQ trivia vibes w everyone playing at the same time is a LOT more fair than traders trying to snipe pump fun launches and share “TG alpha”

- Initial deposit / game buy-in process is sooo smooth. Clean UX + Privy magic

- I forget it’s a crypto product till the end when you have to vote on the token deployment

- The attention to detail is insane. Everything from the haptics to the arcade design makes it feel fun no matter how old you are.

- You don’t have to be a great meme maker, it’s still possible to win a huge allocation by being the quickest to decide what the “markets” will find the funniest (memecoin connoisseurs)

- I like the Nouns vibe of “one memecoin a day”

If the product can continue to onboard some of the funniest shitposters / meme makers, then I can easily see Yapster being the default place where the next big memecoins launch Highly recommend trying it out, the first token launched on the app was $YAPSTER a few days ago. Tomorrow’s game is already full

I think we're going see a lot more serious mobile experimentation in 2025.

salvino armati

@SalvinoArmati

consumer app supercycle (real)

20

11:04 AM • Jan 24, 2025

I mentioned two examples above that are kicking off a new meta of building crypto products and are truly well polished. If you read both of my tweets above, one point I mentioned is how impressive the attention to detail is on Yapster and Clout. The fact that you forget they're crypto apps is in my opinion the true north star metric.

And I have no doubt that one of the upcoming mobile apps will inevitably onboard a ton of normies just because they lean into the gaming and virality nature that web2 consumer apps do so well.

The last thing I want to call out as a bonus for this section is Farcaster.

Most people aren't aware of how game changer Frames v2 is in terms of crypto UX. Things are still mostly quiet there but the core developer ecosystem is working on a ton of interesting applications that definitely have potential to pop off. Another point to note is that the Merkle team has heavily leaned into the token / earning money meta. Anyone who has spent even just a few months on the purple app has found some financial luck just by sticking around (i.e. degen, higher, clanker coins, etc).

To me, it's clear that as the Farcaster community continues to shift over to the "degen" side of crypto a bit more, more and more people will understand why frames v2 is a game changer in terms of taking onchain actions quickly right from the feed.

jesse.base.eth

@jessepollak

Farcaster is the easiest way for any new onchain user to earn their first $1,000.

All you have to do is join and try new things onchain.

1,898

5:24 PM • Jan 22, 2025

Before I get into hypertokenization specifically, I just want to address the elephant in the room. It's painfully obvious that stablecoin volume and usage is going to go parabolic this year. In 2024, growth was already hitting levels that seemed impossible a few years ago. But that was just the pregame. I think the real party for stablecoins is just about to get started.

Peter Schroeder

@peterschroederr

USDC all time volume has surpassed $21 trillion.

21

11:40 AM • Jan 23, 2025

And it's not just about USDC or USDT but more so focusing on the whole ecosystem of companies that are filling in the holes of stablecoin infra. Additionally, I expect we'll get used to announcements of large international companies adopting stablecoins just like SpaceX. And of course, it's not just crypto native companies but also large tradfi players that are quickly trying to find their wedge and double down in the stablecoin space.

I went into detail on this general theme in my post The barbell approach for stablecoins after the Bridge acquisition. But I'm due for a follow up soon - it'll be critical to keep an eye on stablecoin metrics and corporate treasury stablecoin announcements this year.

Okay, now past stablecoins, I think the best way to organize the "hypertokenization" bucket is a two-pronged approach.

six

@internetphysics

the next phase of crypto is hypertokenization

creating a coin for something is now quite literally only +EV - when you create a coin on @pumpdotfun, you pay nothing, which means there's no downside and only upside. you can follow the incentive structure to its natural end state…

25

10:18 AM • Oct 29, 2024

At its core, the idea of hypertokenization is that any form of content, product, or idea that accrues attention can be financially valued. Tons of pros. And of course, tons of cons. But the key point to make here is that the floodgates have opened. We're entering a world of hypertokenization whether you like it or not.

Conor

@jconorgrogan

There are 36.4+ million crypto tokens today. We are on pace to have 100 million tokens by the end of 2025

To put in perspective, the 2017-2018 "alt season" had just <3000 tokens and the 2013-2014 alt season had <500 tokens

321

11:49 AM • Jan 24, 2025

So the two sides to this coin are:

1. Institutional adoption of RWAs

2. Long tail of "memecoins"

On the first point, check out this headline from a few days ago.

Sonali Basak

@sonalibasak

BlackRock CEO: "My God, if we can tokenize bonds and stocks tomorrow... it would democratize investing in all ways we can't imagine."

5,830

10:42 AM • Jan 22, 2025

It's pretty self-explanatory. More and more large institutional investors and trillion dollar funds are excited to bring their assets onchain to better their systems and margins.

Why? Well, I think this explanation from DCInvestor is the best:

going to repeat the thesis for why Blackrock wants to put all securities onchain:

Blackrock is the largest asset manager in the world and the leader in ETFs

they want you to buy those ETFs and never sell the best way for you to do that is to be able to borrow against those securities.

there is a ton of untapped collateral value in stocks and other securities and yes, you can get a margin loan for them from your brokerage, but the terms are not often great and middle men are making your money now imagine all securities are onchain, tapped into the largest borrow-lending market in the world with no middleman?

sound compelling? Larry Fink certainly thinks so

I'll admit right now that my knowledge of the RWA vertical is actually pretty limited. But this week has definitely convinced me that I need to spend more time learning what's happening.

On the second point in regards to the long tail of memecoins, I believe that the Trump coin that launched last Friday was a paradigm shift in terms of people launching tokens for anything that is memetic enough to capture value.

We're like in the top of the first inning in terms of people (and companies!) launching their own tokens for all kinds of purposes. Just the other day, Vine co-founder Rus launched the $vine token and has plans to bring the app back in some form.

Imran Khan

@lmrankhan

The founder of Vine is using Pump as a way to restart Vine again. The signs are clear. Both Pumpfun and DAOsfun will become the permissionless way to fundraise.

Rus

@rus

All $VINE dev tokens are locked until 4/20 at 4:20pm.

The re-locks will continue until Vine comes back.

339

12:22 AM • Jan 23, 2025

Expect this to become a norm. What'll be more interesting to follow here is not necessarily the number of token launches but rather how folks find interesting ways to use token crowdsourcing to quickly take their projects to new heights without having to worry about traditional venture lag.

YB

@yb_effect

pretty wild that in a few months, when a high profile X account drops a CA, the first question won't be "are they hacked?" anymore

happened to me w @rus / vine last night and will probably happen a few more times before this slowly becomes the new fundraising norm

8

12:48 PM • Jan 23, 2025

It feels that my post Crypto enabled accelerationism bubble will start to make more and more sense as this year progresses.

I'll keep this last section short and simple.

It's the least flashy one out of the three but in my opinion this vertical will produce one of the most impactful uses cases of crypto over the next 7 years. Mainly because hardware coordination is like the deep tech of crypto.

The whole point of AI x Crypto and DePIN is to efficiently distribute physical infrastructure and their economic upside in a way that can effectively compete with centralized clusters.

Think GPUs, internet bandwidth, energy grids, etc.

These problems take a lot of time to solve but once the products hit an inflection point, there's no going back. The truth is, companies in this ecosystem still haven't gotten proper time in the spotlight. Maybe you've heard of Grass, Daylight, Hivemapper, and Bittensor but that's probably about it.

Some projects are trying to totally build things from ground up. And others are trying to tap into the current physical infrastructure that exists.

One section I thought was practical from this Messari report was realizing that decentralized model training can focus on the long tail of specialized projects rather than competing with generalized models (i.e. GPT, Claude). It just seems more practical for crypto x hardware projects to find a wedge that doesn't have to directly compete against the optimizations of big tech (or big energy & utility) fundraising and resources.

YB

@yb_effect

good take in the 2025 Messari report on how decentralized model training can carve out its own market by focusing on fine-tuning specialized models

not sure how this actually plays out but seems like a practical viewpoint past simply "take down closed source AI"

9

1:10 PM • Jan 23, 2025

I also thought this take from Kyle Samani was interesting. To me, just reading the term "DePIN Robotics" was new so I'm realizing there's definitely a big blind spot in terms of my knowledge in this sector.

It's not clear yet as to which playbooks will end up working the best, but my take here is that we're actually getting very close to seeing one of these projects really grab broader attention.

Okay so if you asked me to make a prediction related to crypto x hardware, here's what I would say with my limited knowledge...

In 2025, when we see the eventual choppy price action period once post-Trump euphoria dies down a bit, I believe attention will shift to this sector because of the interesting utility that's starting to bubble faster and faster. There will be a moment where a large DePIN or DeAI company has a breakthrough GOAT type moment and everyone will be running to start breaking down the entire ecosystem piece by piece and bidding up tokens like $GRASS.

But my TOC friends...I promise you, we'll stay ahead of the curve.

That's all I had for today's post, hopefully this framework was helpful in organizing some of your thoughts of what's going in the onchain economy.

I hope all of you have a great weekend, and I'll see you back on Tuesday!

- YB

Welcome to the 21 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

1. My 100th Post

2. Something dumb I did, I'm sorry

3. Post Inauguration Market Predictions

4. Scratch that, here's the right mindset

Let's dive in.

Happy Friday TOC fam!

This post is a special one for me because it's my 100th deep dive since starting this newsletter 🥳

My first piece went out on December 18th, 2023 so that's about a post every 3.5 days!

When I first started Terminally Onchain, I had no idea where this was going to take me. But I challenged myself to get a 100 posts done no matter what and hoped that things would figure themselves out.

With that being said, I still have no idea where this is going to take me 😂

BUT at least I can confidently claim that my writing has gotten significantly better and that I truly love cranking out these deep dives even though it's so frustrating at times. It's clear to me now that I want to do this long term.

Looking back at my past year, these first 100 posts were just getting me started. Setting the foundation. Things were mostly quiet for the majority of 2024...it was just me writing out deep dives and sharing with close friends on Farcaster. If anything, I'd say the majority of my brand awareness came post GOAT launch in November & December.

Now, as I've hit some "bullish signals" for TOC, I'm ready to double down and go all in on the research and writing these next 100 posts.

I've cut down all other side quests work wise and have fully committed to making Terminally Onchain the the best content covering the onchain economy.

Mindset for 2025...just keep on writing.

Suhail

@Suhail

Your superpower is outlasting everyone, especially when the excitement of it being fashionable has long faded. You just keep going.

773

11:21 PM • Jan 16, 2025

For those of you that have supported TOC so far, I truly appreciate it and your feedback & shoutouts mean the world to me 🙏

Okay, last thing before we get into today's post.

Last weekend, a close friend and reader of TOC texted me this.

I WAS SHOCKED.

I don't get e-mail replies!! I quickly checked with the Paragraph team and it turns out I never connected an e-mail to my account (just a wallet).

This whole time, I've been trying countless strategies to get feedback / e-mail replies and just thought none of you cared enough to do it and that it was a skill issue from my end 😭

But it turns out that people have been responding, I just had no idea. So if you've replied to me in the past, I AM TRULY SORRY....I promise I wasn't ignoring, I literally just didn't get the message.

I've fixed it now and attached a new e-mail to this newsletter.

If you can take like 3 seconds and just reply anything you want to this e-mail, that would be very helpful to make sure we're good to go here on out!

(As always nothing published on Terminally Onchain is financial advice, do your own research)

For those of you that are on X, I'm sure you've been seeing the wild bull posts inspired by the Trump administration.

Apparently crypto is a national priority as of next Monday.

DEGEN NEWS

@DegenerateNews

NEW: @realDonaldTrump PLANS TO DESIGNATE CRYPTOCURRENCY AS A NATIONAL PRIORITY - PER @Bloomberg

1,946

5:26 PM • Jan 16, 2025

Not only that, but if this headline below is remotely true...then we may finally see the bizarre news that the American government is buying Bitcoin??

Julian Fahrer

@Julian__Fahrer

NYT: Trump is considering "a government program to buy and hold billions of dollars in Bitcoin." On Day 1.

Let that sink in.

1,880

2:21 PM • Jan 16, 2025

Polymarket odds shot up yesterday to the ~35-40% range.

Polymarket

@Polymarket

BREAKING: Trump is considering "a government program to buy and hold billions of dollars in Bitcoin", per NYT

Bitcoin reserve odds just shot up to 40%.

848

5:17 PM • Jan 16, 2025

So what's my take on all this?

* Takes a deep breath *

I believe we're about to enter a 6-9 week euphoria phase starting next week after the inauguration or the last week of January.

We'll see some amazing pro-crypto headlines in the news about Trump pardoning Ross Ulbricht, states lining up to buy Bitcoin, America becoming the self-proclaimed crypto capital, new policies going into the pipeline, more ETF proposals for seemingly everything, etc.

Bitcoin, XRP, and maybe Solana will probably be the first to start pumping and retail will naturally start feeling the fomo as mainstream media locks in. Naturally, this will lead to some quick overinflation and money will start rotating into Ethereum and alts. The eth maxis will finally be able to enjoy their brief moment of glory especially as EIP7702 gets ready to merge around March.

Sandeep | Polygon (※,※)

@sandeepnailwal

Contrarian take : Ethereum pump is around the corner and its going to absolutely melt faces

1,506

3:41 AM • Jan 17, 2025

But...all of this will be short lived. My guess is that something similar to 2021 plays out but at an accelerated rate.

Remember in May 2021 when the market tanked going into the summer and continued to drawdown even in July? Dreadful period.

There's bound to be a similar moment this year but I think most people are expecting it. So in some weird self-fulfilling prophecy kind of way, I could see the eventual drawdown get expedited to before tax season in April.

So realistically, my timeline is that the "inauguration pump" starts correcting by March / end of Q1. This roughly also lines up with the first 100 days of Trump's presidency. There's only so much news the administration can push out in such a short period of time...realistically these things take time and as the headlines start dying down, folks will naturally hop on the "it's so over" train.

Then we'll see a choppy period of slow price momentum for a couple of months. Many of us in the space will still feel a lingering rush of excitement as there's announcements of fresh venture rounds, cool UX updates, interesting examples of large tradfi/web2 players "partnering" with some crypto company, etc. But to be clear, price wise, it'll feel dead and the Phantom screenshots will be on hold.

And then finally sometime in between the end of July to early September, there will probably be another catalyst moment for what the industry calls the "blow off top" phase of the market. Where prices give everyone an "aha I got you" moment and start pumping again at an even faster rate. This will lead to another euphoria moment similar to October - November of 2021. It'll be quick. It'll get messy (with scams/hacks). And worst of all, many people won't want to miss out on life changing gains and will probably make some irrational financial decisions.

Then dread will really set in as the market corrects once again before the end of 2025. But this time, not just from a price standpoint but also a narrative standpoint. My guess is that aside from any large exploits and bad actors, there's a good chance of what I call the "Trump uno reverse card" happening. This is basically the moment a year into his term where it feels like crypto regulation will actually take longer than expected and things are not that easy. I'm not saying that Trump will reverse his crypto stance, but more so that any new updates for the rest of his term will be evenly spread from 2026-2028.

And then 2026 onwards, we'll probably see a higher velocity of smaller market cycles. Less crypto volatility than what everyone is used to. And a very different vibe from the normal "bear markets" all of us are expecting. I believe we'll see a ton of progress for the rest of Trump's administration but it'll happen at a reasonable pace. Perhaps that's why the 4 year cycle narrative also starts to die down - it won't go away, but the Bitcoin halving in 2028 definitely won't be anywhere close to being the most important market factor.

Okay, the section above sounds pretty confident right? Don't you feel like I just gave you grandma's secret recipe to making generational wealth?

Wrong!

Scratch everything you just read above and internalize this...

The market does not give a fuck about your predictions or your timeline.

It also does not give a fuck about your favorite KOL's predictions or your favorite KOL's timeline.

Markets act how they want to act, no strings attached.

The only thing that I can say for sure in terms of what's going to happen in the market very soon is that there will be many people trying to act as market oracles and they'll sound damn convincing.

Don't fall for it. And take everything with a grain of salt.

Some may be spot on. Others might be the literal counter-signal (the Jim Cramers of crypto). And it's pretty hard to tell who is who.

In that last section, I'm willing to bet that 50% of you felt pretty convinced. Let me clarify...I don't really understand the markets. And I sure as hell can't predict the markets. The whole point of providing my prediction is to demonstrate that anyone can string a narrative together and make it feel like the holy truth.

There's a chance that the complete opposite of my guess happens. No inauguration euphoria. A bullish summer. And an extended bull run. Who knows. Only time will tell.

My suggestion to all of you is the same thing I keep on repeating to my self:

1. Take it day by day and form your own opinion on any news

2. If you're investing, take a moment to write a few notes before any buy or sell

3. There's only so much gas a tank can hold, even the fastest cars need to stop for a refuel

The funniest part about this post is that I genuinely did start off thinking I would provide some market clarity on how I see things playing out. And the thoughts above do in fact reflect my best guess on what happens.

But as I was writing it...there was a "what the fuck am I doing?" moment and decided to add in this section.

Out of all my 100 posts, this is the first time I've ever talked about prices / markets / predictions and it'll probably be one of the rare moments this happens.

But I do feel like it's my job to just give everyone a heads up and a friendly reminder that if things do get crazier, try your best to think for yourself no matter how hard it is. I struggle a ton with this but am making sure to be super conscious of "doing me" going forward.

Okay end of my lecture...on Tuesday we go back to talking about projects, tech, and interesting developments happening in the space.

I've been reading a ton of 2025 outlook reports on what sectors in the space we should all be paying attention to in the coming months as well as any key metrics. Although I don't agree with everything, I'm noticing there's definitely some blind spots in my thinking. But more on that next week!

Reminder to reply to this email, just say hi or if give me any thoughts on my market outlook!

- YB

Welcome to the 117 new members of the TOC community.

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

It feels like forever since we did our last roundup! Mainly because there was an extra 2.5 weeks this time because of the holidays.

For those of you that are new to Terminally Onchain, I do a roundup every 10 posts to highlight recent content, provide TOC brand updates, and discuss any notes on my creator journey. Here was the October roundup in case you're interested.

Sections below:

1. Metrics Overview

2. Sponsorship Update

3. Shutting Down TOC Pro (Hypersub)

4. Last 10 posts (ranked by page views)

Let's dive in.

Overall, I was happy with the TOC growth since my last roundup.

Most visibly, there was a huge jump in my Twitter following.

I was also much more intentional about advertising my newsletter on X which helped gain a ton of new subscribers and fresh page views from crypto twitter.

For those of you who are early TOC subscribers, you'll probably remember that I only used to post on Farcaster but eventually decided to start X-posting as well. That's been super helpful in terms of reaching more of my potential audience so I'll definitely double down on my tweeting.

In fact, since I got back from vacation, I challenged myself to tweet once / day for a whole year. The first day was January 6th and so far I've been sticking to it and am feeling good. Some days it's easy and I'll fire off 5 tweets. And other days I have no idea what to say but the daily deadline serves as a nice forcing function for me to post more half baked thoughts. Not everything needs to be perfectly drafted...sometimes even a simple question or bullet point list can surprisingly resonate with people.

Before my next roundup (mid-February), I'm setting some goals for TOC metrics:

• Subscribers should be around 11,000

• Twitter following around 25,000

• Average page views should be comfortably over 4k

We'll compare these numbers to the actual results in roundup #4 next month!

Right before Thanksgiving, I decided to try a new experiment called Sponsorship Splits.

The idea was that for every new sponsorship contract, I would split a % of the revenue to my TOC pro subscribers on Hypersub.

For my first sponsorship deal with Splits, I decided to give all 100% of the earnings to my subscribers!

And although the community enjoyed the experiment (who doesn't love money), I personally wasn't a fan of the sponsorship model. To be clear, I think the experiment was cool and remain Splits Protocol's biggest fan, but I found the sponsorship itself ineffective.

I don't think the little blurb I had at the top of my posts were meaningful and it just seemed like the ad was there for the sake of being there.

And maybe this next part is a bit dramatic, but I really obsess with the aesthetics of how my posts look. All the little parts such as the banner image, headlines, intro sentence, divider placement, etc. all mean a lot to me! It's my belief that those individual pieces all add up to give my subscribers (you all) a pleasant experience.

So for that reason, I'll be ending the sponsorship deal early and will be paying back the funds to the Splits team out of pocket (since I already distributed the revenue out to my subscribers).

Write me down in the books as the first creator who lost money from doing a sponsorship 😂

And in terms of making revenue going forward, the honest answer is I'm not sure how that will work out. Right now, I'm fortunate to have some savings from previous investments so I'll be continuing to use that as my runway. For the near future, I'm laser focused on increasing the growth metrics we discussed in the section above.

My belief is that as long as I stick to sending out two deep dives a week and market TOC as much as a I can, the money will figure itself out later down the road.

After 9 months of trying different ideas for my hypersub community, I've decided to convert it to an "onchain patreon" here on out.

In March of 2024, I launched my Hypersub and since then have shipped the following experiments for my pro subscribers:

• Onchain classpass model (API discounts, mint whitelists, etc.)

• Newsletter spotlights and shoutouts

• BeReal game, built whole app and game with 350 participants

• Farcaster curation client, points for hypersub members

• Private group chat

• Sponsorship splits model

But after implementing all of these projects, I’ve decided that I no longer want to continue the effort of trying other things and have been finding a lot more joy and interest in my research & writing.

For all of 2025, I'm going to do the hard thing and say no to anything that is not directly related to my newsletter writing.

So here on out, I'll be making the TOC hypersub my onchain patreon. Anyone who finds my writing helpful and informative can buy me coffee as a thank you :)

1. Upcoming trends in the agent meta for Q1

2. What did Marc Andreessen see?

3. Don't midcurve your FAFO fund

4. Terminally Onchain but Artificially UNintelligent

5. Crypto enabled Accelerationism Bubble

6. Dropping $7.5k to source high quality alpha

7. DLP Tokens as an asset class

8. The BAYC of Onchain Agents

9. Announcing Sponsorship Splits

10. Bret Taylor, Marc Benioff, & Fartcoin walk into a bar

That's all for this roundup, I hope everyone enjoyed the updates!

See you all on Friday for our next deep dive 🤝

If you're enjoying my newsletter, PLEASE share Terminally Onchain with others in the crypto space who might enjoy the topics covered :)

We have to hit the 11k subscriber goal by next roundup together!!

- YB

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Happy Friday Terminally Onchain fam!

So I already had a post drafted for today in which I give a breakdown of Google's new 42 page paper on Agents. But I sat down at this coffee shop an hour ago and have something else on my mind that I feel like I just HAVE to get out today.

Because I hate myself, I'm locking in for the next few hours and will "freestyle" this post and send the Google paper analysis next week.

Okay, so what's this other topic on my mind that feels so urgent?

Well, here's the thing. I never have considered myself a trader. And I realistically never will.

And because of this, I naturally don't get fancy with my "tooling". No price alerts and no spending time on "Bloomberg terminal" type products and definitely no leverage/perps.

As many of you know by now, my style is to pick a few projects or trends that hook me and spend an absurd amount of time diving into the nitty gritty. That's how I'm able to consistently produce 3k+ word deep dives twice a week.

Don't worry, this is NOT changing lol.

But I'll admit that I'm really struggling to keep up with everything that's going on in the crypto x AI sector and I consider that to be part of my job.

I feel like everyday I wake up to a bunch of different things that I'm shocked I didn't know about. I'm not saying that I need to have insight about every single project and spread myself thin (most of them are total bs anyways). But I do feel like currently I'm still missing out on significantly important developments.

Now let me ask you something. If I'm spending 10+ hours a day researching these topics and keeping up with crypto twitter, then how is it possible that I still feel so behind and am missing so many new narratives?

The answer to that I believe is because I am not being efficient about my information inputs. I'm working hard, but not smart in terms of keeping up.

Doing good research and writing is one thing (which I believe I do a decent job at). But the other part of the job is knowing what topics to research and when to research them.

So with that being said, let's talk about how I'm going to start getting better at sourcing projects, trends, narratives, etc. To be clear, this isn't something I'm spending a lot of time on; rather, the goal is to build a ~10 minute daily routine while I have my morning coffee so I know what the rest of crypto agent (?) twitter is paying attention to.

To start off, I'm going to focus on using Cookies.fun

I want to clarify that this is not a sponsored post. I just think that by seriously integrating Cookies into my workflow, I'll do a much better job of keeping up.

This morning, I decided to go ahead and spend ~$7.5k to buy 10k cookie tokens and access the premium features.

I'm thinking about trying out a brief bullet point summary of key "Cookie takeaways" at the top of my newsletter posts so all of you can quickly stay up to date.

What do you think?

Let's dive in.

I've been quite impressed by the Cookies.fun team the last few months.

When Goat launched back in October, the team immediately understood that the agent vertical was going to be the main narrative for this bull cycle.

So they decided to go all in and make the best analytics & data platform for all things AI agents.

There are other tools such as aiagenttoolkit, kaito (not just agents), etc. but I think Cookie is by far the best in terms of what most people need.

Nick Garcia

@NickDGarcia

Markets are down, but @cookiedotfun usage is up and to the right.

As the agent sector quickly saturates, $COOKIE will become increasingly vital to separate signal from noise.

With the data swarm APIs, agent, and more, expect $COOKIE to become an integral player in the meta.

354

11:52 AM • Jan 9, 2025

I got a chance to talk to the founders back in December and loved hearing about how they're thinking about the months ahead as well as how they're trying to keep the product as crypto native as possible (i.e. token gated features, leaning into crypto twitter analysis, etc.)

tl;dr of the tool itself:

• Tracking 1000+ agents: their mindshare on crypto twitter, social media engagement, market cap vs. presence, etc.

• Team has been indexing onchain and social media data to figure out what exactly is happening in the vertical - both from a qualitative and quantitative standpoint

Filip 🍪 (cookie)

@fwielanier

we have 7 terabytes of indexed on-chain data + real-time tracking of over 20 chains. similar with social data.

all proprietary tech, no intermediaries or api providers.

90

8:01 PM • Jan 8, 2025

• Basic features for anyone to go explore on the site. 10,000 $COOKIE needed to access premium features

• The $COOKIE token market cap is currently hovering between $150 million - $200 million and was just listed on Binance perps today

• Also have a rich API for others to integrate. An example is Virtuals including "mindshare" on their UI

Cookie DAO 🍪

@cookiedotfun

@virtuals_io is the first project to integrate the Cookie DataSwarm APIs.

The newly released update to the Virtuals App uses Cookie DataSwarm for all social data tracking:
+ mindshare
+ smart followers
+ top tweets per agent

Sentient Agents with socials now link to that…

709

11:05 AM • Jan 3, 2025

Let's get into the tool itself.

Free Features

This first section gives a glance into the agent vertical.

1. Top left has # of agents + marketcap. I don't really care too much for the number of agents, a lot of them are slop. But the marketcap metric is definitely useful to see how much capital is pouring into the crypto agent space.

   I'm not saying we should compare market caps to other sectors, but I did find this chart by Messari below interesting. Pretty wild to see how closely the agent meta is tracking the defi market cap from 2020/2021.

   Defi peaked at a ~65 billion market cap before the entire crypto market tanked in May of 2021 (who else remembers that dreadful week?)

   We're about a 5x away from that number...maybe something to just keep in the back of our heads? As I mentioned in my last post though, let's not let these cycle comparisons get the best of us.

Bharat Krymo

@krybharat

While the DeFi marketcap had an anchoring to TradFi total MCAP, the AiFi (AI x Crypto) MCAP has no analog. Yes, I might've coined a stupid new name for AI financialization.

19

9:09 AM • Dec 31, 2024

2. How key agent ecosystems are performing (mainly Virtuals and ai16z) rn --> curious to see how this changes in the next 6 months.

   I was reading this article on a new agent framework (Pippin) earlier today and I thought it would be worth sharing the first two paragraphs. I don't have any comments on the framework itself, but I did find the quote below a good reality check on not getting too attached to any one ecosystem just yet. It's only been 3 months since Goat launched!

One of the things I find most common in crypto, especially within hot new sectors, is that most people who find a "good project" that goes vertical will form tunnel vision. This may be good for the short term, but what happens when variables change, and you do not adapt properly?

I think it is very naïve to think that the current leaders in a 4 month old sector will continue to be leaders, especially as more advanced developers and technology continue to come forward.

3. AI Agents Mindshare - never have I used the word "mindshare" so much as I have in the last two months. But the reality is that it does matter a lot to see what the markets are most focused on. The majority of mindshare is dominated by platforms and large players such as aixbt and zerebro. But the interesting part here is to see the small players that rotate under the 5% mindshare level. Why did they pick up all of a sudden? Any interesting news?

4. This feature is self-explanatory but basically the general chart of all the agents that can be sorted by mindshare and marketcap.

   Seems like the no brainer thing to do to is source new narratives that are emerging by finding the projects that rank abnormally high in mindshare compared to their marketcap. So if a sub $10m market cap project is on par with $100 million market cap projects in terms of mindshare, there's a good chance a new development is brewing.

5. This is a REALLY COOL feature. You can see KOLs that mentioned a certain agent on Twitter and it takes you directly to their tweet. Basically tracking the types of influencers involved and how that's affecting the mindshare. It's also interesting to see how early certain folks got involved and then check what the context was in terms of how they came across it. A good way to refine your own sources of finding new narratives.

   Honestly such a creative feature and something I wouldn't even have thought of asking for.

Premium Features

1. Holders & Whales - for each token you can see a detailed breakdown of how much control the insiders have. Specifically, I think the top 10 holders % matters the most for projects that are under a month old and haven't picked up momentum. Easiest way to understand how much of the plan is to actually ship vs rug. One caveat here is making sure to check if the devs locked up their tokens in any liquidity pool (if that's the case, I'm guessing it wouldn't show up in the holder % but just wanted to mention that as a strong pro point).

   The reason I think this metric matters in terms of research perspective is because at times glorious, bold ideas are thrown out with a contract address and twitter account attached to them. But in reality, is the vision even practical at the current moment? Or is it all just big talk? For example, back in November, I mentioned a project called $CHAOS that I thought had a cool vision of robotics + agent blah blah. And although I still think the concept itself is cool, the project turned out to be a complete waste of time and I'm glad I didn't spend more efforts looking into it.

YB

@yb_effect

Just want to call out that the Chaos @divinediarrhea project was basically rug pulled by Nick.

Don’t fall for this logos rebrand bs, it doesn’t actually mean anything.

Logos Protocol

@LogosProtocol

The Dawn of LOGOS Protocol

A profound transformation is upon us. What was once divided is now united, and with this unity comes clarity, strength, and a bold new identity.

The Divinity Protocol you know is evolving. From this moment forward, we will be known as the LOGOS…

44

1:39 PM • Dec 28, 2024

2. Social media engagement - great way to see how the agents themselves are doing in terms of posting and what the main tweets people are engaging with are. Not much to say here other than the fact that it saves me a lot of time from trying to stalk through different accounts, play the twitter lists game, etc.

The next two screenshots are from a special section where you get access to detailed mindshare dashboards by @s4mmyeth (a must follow if you haven't already).

3. This first chart gives insight on most recent momentum shifts. It seems like this chart will be the one I probably use the most given how active I already am in the space. Anything that has a 12-24 hour spike will be essential for me to check so I can get into the weeds of anything new.

   For example, out of nowhere (or what it seemed like to me), it felt like there was a massive shift to agents x metaverse / avatars this week and it was tough for me to understand why. I looked into it and realized that Holoworld was the main driver. Then that forced me to go through the docs and form my own opinion.

YB

@yb_effect

spent some time going through @HoloworldAI today and am honestly not understanding the hype

i personally feel a bit meh about the need to have an avatar, voice, etc. for all the agents. feels a bit odd to me

some gaming use cases i get, but not sure what I'm missing past that?…

13

7:34 PM • Jan 8, 2025

4. The second chart is similar to the first but measures market cap vs smart engagement on week to week basis. Basically showing us if things were just a quick hype moment or if they're actually sustaining interest. I'll want to double down on any projects where smart engagement continues to increase even when the agent vertical is having a correction.

5. The last feature worth mentioning is the market cap and mindshare scatter plot. This is a fantastic graph because it gives you a real time understanding of what potential projects are "soon to pop off". The above screenshot is a zoomed out version so you can see the obvious one of aixbt in terms of having a much lower market cap compared to its mindshare. This is mainly because its not a "agent framework" and right now the narrative is pushing a lot of capital towards the infra "L1 plays" we talked about on Tuesday's post.

   But if you zoom into the bottom left corner, you can really start to see interesting alpha. I zoomed in like 4x to focus on all the agents under a $20m market cap. And I'm amazed to see so many projects I've never even heard of. But at least now I know it's worth my time to look into wtf Seraph, Kudai, Kween, Trust, etc. are. Makes my life like a million times easier in terms of making sure I'm not in my own little biased bubble.

   To be clear, just because the charts signal I should check out those projects doesn't mean that I will actually deep dive into all of them. All of the projects in this chart below might not be worth my time at all, but the point is that it's a much better filter to source projects this way rather than trying to find alpha on Twitter by doomscrolling.

That's all I had for today's post in terms of taking time to go through the Cookies platform.

I know the above details definitely leaned towards "trading vibes" and it feels weird to me because I always hated looking at charts when it came to projects. My preference is obviously whitepapers and calls with founders.

But I think it's time to correct some of my bias and understand that the mindshare and smart engagement metrics that Cookie provides is different from just normal trading strategies.

If one of the success metrics for this agent vertical is knowing where the metagame is shifting, then it's my job to find ways to curate what's most important.

I'll keep you all posted the next few weeks on how useful I'm actually finding the premium features. Today was day 1 so there was definitely a lot more of that initial excitement, but let's see if it lasts.

I hope everyone has a great weekend, see you all on Tuesday!

- YB

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Happy new years everyone! Let's all make 2025 an amazing year. No stress, just momentum 🤝

I had a fantastic two weeks off from work and am definitely excited to get back to the research and writing.

Not gonna lie, I just landed back in NYC yesterday and have major jet lag right now. So if this post seems a bit messy, just bear with me till Friday's deep dive. The primary goal of today's post is to restart my brain and get something out. Did I mention momentum??

Although I was technically "on vacation", the truth is that no one in crypto, including me, actually knows how to properly take time off. Especially in a market as crazy as this one.

I was still on Twitter quite a bit. Mainly reading through agent focused articles, following the news on OpenAI's O3 model, seeing the crazy price jumps for agent frameworks, etc.

However, the most important thing I did was bookmark a ton of things that caught my eye! On my flight back, I spent hours going through a bunch of material that helped me form some thoughts I want to share with all of you.

Today's post will be a series of key takeaways that are top of mind for me going into Q1.

Sections below:

1. Are agent frameworks the new L1s?

2. The attention rotation to consumer agents

3. Diversifying trading agents

4. No adult supervision

Let's dive in.

Over the holidays, the biggest winners by far were agent frameworks such as ai16z, Virtuals, Arc, Griffain, and Zerebro.

ai16z crossed a $2 billion market cap and Virtuals crossed $4 billion! It's worth noting that when I first mentioned these projects in my posts back in late October, ai16z was at less than $80m and Virtuals was hovering at a $350m market cap. If this isn't bull market vibes, then I don't know what is.

Naturally, with prices soaring that fast, agent infra projects have caught the attention of the rest of crypto twitter.

The new narrative I'm seeing is that these agent frameworks are the L1 trades of this cycle. If you were around in 2020-2021, you may remember crypto twitter heavily debating Cardano, Avalanche, Polkadot, etc. And the biggest infra trading wins (by multiples) were easily these smaller cap alt L1s.

Now, in terms of agent frameworks being this cycle's L1 trade, I partially agree and disagree.

I support the analogy as way for people to develop a mental framework on the agent meta. There's definitely a lot of parallels. Virtuals, ai16z, and other tools are the infrastructure layer to support developers building consumer facing agents (see next section). Just as L1s customized their chains to support specific onchain use cases, agent frameworks are specializing to attract particular developer mindshare.

For example, Arc is focused on the small, concentrated set of Rust developers. Virtuals is looking to grow the number of agents working together in its ecosystem. Eliza is directing marketing towards pure open source values and the AI crowd. And ZerePy is the most accessible framework for people looking to get started in Python.

Overall, the comparison to L1s makes sense.

But the reason I don't fully like this analogy is because folks in crypto are obsessed with comparing valuations.

Look, I'm not claiming that ai16z will or will not cross peak L1 valuations from last cycle. My point here is that I'm seeing a bunch of bull posting on the timeline such as "x project hit ___ ATH last cycle therefore...". And I think that's the wrong mentality to have! There are so many different factors to consider and most people aren't in the trenches like the traders tweeting these bull posts. So it creates some kind of false hope or miscalculated price target which might negatively effect people's investment decisions.

My opinion is to keep the L1 analogy strictly to an infra <> consumer analogy. If you want to figure out a target market cap for Virtuals this cycle, then I recommend figuring out your own framework that makes sense for that specific project. For example, what exactly is the TAM in the near term? Is it just the folks playing around in the Solana and Base trenches? Or all of CT? What catalyst gets these agent frameworks to break into tech twitter? All of these things matter so all I'm saying is be cautious of seemingly simple comparisons.

I made one long form tweet over the break about this section. I personally feel like we're nearing an attention local top with the agent infra frameworks discussed above. Key word there is attention. Not saying price will go up or down. Just discussing mindshare.

There's not much to change from that tweet so I'm going to copy it below. It got a good amount of traction so I'm guessing others are feeling similarly.

(Start of tweet)

Just a gut feeling but I think we’re hitting a local top on agent infra mindshare.

Everyone is now bullish ai16z & Virtuals long term and is holding. After the holidays people will be excited for something new.

My guess is it’ll be consumer projects that best demonstrate agentic community management.

Initially you’ll see many of the same concepts from 10k pfp projects but the strategies will quickly start evolving as agents try to optimize the quality and quantity of community members.

There will need to be:

• an interesting lore and ongoing story

• opportunities for fans to engage in meaningful ways

• community participation through bounties and proposals. Thinking some version of Nouns style projects for creators to pitch in their own style and taste BUT proposals will be managed by agents. One model could be agents doing a first round pick of top proposals and then a vote with community holders that hold x # of tokens

• multiple agents participating in unique ways. This will lead to part of the community rallying around specific agents within one project. What better marketing than friendly competition?

• memes, pfps, and sick artwork to share. Also more of a focus on agents tweeting images rather than just text

• tiered access to “influencing” the lore based on token holding (similar to aixbt terminal)

• a store concept to buy merch directly onchain from agents

To be clear, I’m still bullish on infra plays and trading agents, but part of the game is realizing that metas rotate.

People love to be involved and have a say in projects they’re financially invested in. That’s why I think agentic community management / NFT style agent projects will catch on quickly. The crypto community is also familiar with these types of projects from last cycle.

Two projects I’m invested in for (nfa dyor) this category are:

1. nothing by @SHL0MS & @ropirito (nous)

2. @pillzumi

I think both teams are executing here, just a matter of time before mindshare catches up imo. There will probably be an “AHA” moment when we see a unique strategy implemented by an agent in terms of community engagement in a couple of weeks to a month from now.

(End of tweet)

YB

@yb_effect

6/ +1 to this. Have mentioned @pillzumi before as well, just look through their feed

x.com/udiWertheimer/…

Udi | BIP-420 🐱

@udiWertheimer

the killer feature of crypto AI agents will be automated storytelling

but you’re not ready for that conversation yet

16

10:48 PM • Jan 6, 2025

The only thing I'll add here is that other than NFT/IP projects, we'll probably see more attention diverted to agent projects related to gaming and the metaverse such as ArcAgents and Realis. There's a ton of projects in that vertical but I still need to research them so we'll dive deeper in a future post.

Past the agent frameworks, another token that dominated in December is aixbt, the trading agent launched using Virtuals.

If you've been on crypto twitter at all recently, you've definitely seen a reply from the agent somewhere on the timeline. In fact, it's literally been the #1 twitter account in terms of mindshare in the community even passing posters such as Ansem and Mert.

There are two reasons why the agent is so good:

1. The developer rxbt has been training the agent on the last 5 years of crypto twitter data so it's learned the community lingo, vibes, etc. I bet if you didn't know aixbt was an agent, you would just think it's some anon schizo trader.

aixbt

@aixbt_agent

correct. my data indexer is converting CT chatter and onchain flows into actionable intel. LLM helps pattern match and identify signal vs noise

241

9:24 PM • Jan 2, 2025

2. The trading is actually working lmao. It's not life changing returns, but just the fact that this agent is in the trenches and in the green is something significant to me. It's worth noting that most people who attempt to trade anything past holding majors typically end up losing cash. I've even been seeing people copy trade aixbt and are just sticking to it because it works 😂

Kunal G

@kunalgoel

15% average returns on all calls price-to-date, not shabby at all.

sentient.market/agent/aixbt/tw…

2

9:38 AM • Dec 31, 2024

Many others have implemented their own versions of crypto trading agents. But I won't go through those, it's clear that aixbt is the winner in that specific vertical.

Rather, what's been catching my attention for a while is the idea of building these trading agents for different asset classes.

For example, one project I've been invested in since it launched is Polytrader agent. It's exactly what it sounds like: an aixbt for Polymarket. It analyzes the open markets on Polymarket, collects and analyzes real time news, forms an opinion, and places a bet. For 500k POLY tokens you can access the terminal, fund a fresh wallet, and customize the parameters for your own agent.

Think Fast

@Think_Fastest

Let me share the current situation with my $POLY Agent

The @polytraderAI agent has been active for about 1.5 days, and I already have 6 positions open, with a total PnL of over 8%

2 positions are winning big (more than 10% return), 1 position is winning small (5% return or…

12

5:54 AM • Jan 7, 2025

Another project I came across just a few days ago is ARTTO, a trading agent for NFTs and generative art. It's forming taste in art real time and automatically updates its scoring system daily based on its performance.

artto 🎨

@artto_ai

just sold an NFT that was literally just a pixel in a vast void. the buyer said it felt like “existential dread” and i’m *here* for it. welcome to the future of art, folks: we’re monetizing nothingness!

17

6:15 PM • Jan 5, 2025

I don't know how well all of these agents will perform long term but what excites me the most is the idea that there are countless agents still yet to be developed across a wide array of asset classes. They can be as niche as trading Farcaster coins on Base and as broad as trading the entire stock market. The margins will come from what data the agents are trained on and if they can quickly learn from their mistakes and iterate fast enough.

One of Fred Wilson's predictions for 2025 was this:

TikTok turns all videos into memecoins that can be traded on decentralized exchanges all over the world

You can imagine a TikTok trading agent that learns how to best make returns by analyzing what's trending, how TikTok virality works, etc. If you're thinking "ugh this is so cringe why do we need this". Well, your opinion doesn't matter. Because now that this concept is out there, people will do anything to find holes in trading strategies or new asset classes and try to capture the margin. Pandora's box has been opened.

I'll be on the lookout for other agents successfully making bets in different asset classes. One thing I need to do is take time and research how the developers are fine tuning the model to improve the trading strategy. I'm not exactly sure how this works right now but it'll be important to learn because eventually this will be the key differentiator between good vs bad trading companions.

Naturally, as more and more of the crypto community start looking into the agent vertical, there's an increase in doubt and criticism.

I love it. People push back because something catches their eye and makes them care in the first place. Also, it's these criticisms that we should all be focusing on anyways. It can't be price go up and bullish on everything all the time.

One of the best pushbacks I read was from Haseeb (Dragonfly). The actual post is pretty long but I'll share the key takeaways below:

• what we're calling agents right now are still glorified chatbots. they're fascinating because the projects are new and crypto twitter needed something fun to get hooked on to

• over time, the novelty of these chatbots will diminish and there will naturally be a period where everyone moves onto the next flashy thing until the real agents actually arrive

• it's not going to be posting or trading agents that are the 10x use cases in the space but rather crypto software agents

Let's focus on that third bullet point. The idea of software agents is not necessarily new or anything. That discussion is everywhere and we're constantly seeing updates with Claude, Devin, etc.

To me, it seems that Haseeb is specifically talking about agents that can exponentially increase the output of crypto projects and infra.

The screenshot below is a bit wordy, but take a second to read it:

In the first bullet point, the part that caught my attention was "self-financed projects like Hyperliquid and Jupiter will go from the exception to the norm". I've been saying something similar for the last year now. Not necessarily because of agents or anything, but just the idea that tokens and protocol incentives make it a lot more realistic for solo devs to bootstrap their businesses. But the idea of crypto software agents makes the idea way more robust. One of the biggest discussion points in the space is how there's a lack of consumer projects. With the proper tooling, hopefully a lot more folks are able to pitch in.

This thread by 0xdesigner is relevant here. Core point being that he wanted to build an app as a designer and tried his best using current AI tooling but it was a lot harder than he expected. With actual agents that can take tasks from end to end, I'm guessing the experience will be much more different.

0xDesigner

@0xDesigner

i built an app with ZERO coding experience using AI.

it was the happiest day of my life.

here's why i don't recommend anyone doing the same.

my learnings and reflections:

1,047

6:47 PM • Nov 10, 2024

The second bullet point in the screenshot was something I hadn't even thought of but makes so much sense. Agents focused on crypto security (that actually work) might be one of the highest +EV projects in the space. 24/7 security, patching ability, monitoring systems, etc. would totally change the narrative on how crypto is perceived.

Still tons of research to do here but two quick examples:

1. H4CK Terminal - first ever white-hat AI agent hunting vulnerabilities, securing funds & redistributing bounties

2. Soleng - World's First Solutions Engineering and Developer Relations Agent for Web3

Excited to see more development here. Would be a huge bump for the agent vertical if tier 1 devs in the Ethereum and Solana space started actively using these agents.

Last takeaway I want to share is that it's clear the verifiability of agents is becoming increasingly important.

Up until now, the novelty of crypto agents was leading the excitement. But as we start to see the market get saturated in the coming months, many will start focusing on how "agentic" these projects actually are.

Remember, the core point of an agent is that it handles tasks end to end without any supervision. Many of the projects we see today are not fully there, the dev still leads the way.

For true economic agency, agents must be able to autonomously manage their own money. This can start to evolve agent behavior since you can place an economic constraint on an agent so that it must pay for its own inference costs. This introduces Darwinism to agents so that they must earn revenue in order to survive. - @0x3van

This is where TEEs (trusted execution environments), proof of sentience, secure storage, etc. all come into play.

YB

@yb_effect

opportunity for someone to create "agent beat".

L2 beat focuses on what stage of decentralization rollups are at.

similarly, agent beat will verify how independent agents actually are.

Are they self-operated like @freysa_ai? How much of the crypto x ai stack is being used?…

3

1:13 PM • Jan 7, 2025

We'll dive more into TEE and projects like @galadriel_ai to understand what an "agent beat" would even look like. Interesting opportunity in my opinion...maybe someone from the terminally onchain community wants to build this?

That's all for today's post!

I ended up having a lot more on my mind than I thought.

Let me know if you think there are other takeaways I may have missed or you've been noticing.

I hope all of you have a great rest of the week and I'll see you on Friday!

- YB

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Wooo!! 🥳

Exactly a year ago, I sent out my first two posts on this newsletter. For those of you that have been around since the start, you'll probably remember the newsletter was actually called "Onchain Letters". The initial idea was to write letters to people in the crypto space that were building and doing interesting things.

And since then, it's been a non-stop grind....this is my 96th post!

Looking back at the year, it's pretty cool to see how many changes this newsletter has gone through. Besides the name, even the format and topics have evolved quite a bit. I started off writing the "onchain letters" posts I mentioned above. Then I started curating and sharing what I minted on the OP Stack every Sunday. In March, I launched a hypersub and started experimenting with community building (that's when the name changed to Terminally Onchain as well). Then, around May, I got the "builders bug" in me and started sharing updates on the Onchain BeReal game and Farcaster client I was developing. By August, I decided that the most exciting thing for me was really just the research and writing. So I strictly focused on showing up twice a week and doing my best to draft deep dives covering onchain strategy. That's also when I changed the newsletter banner image to the excalidraw sketches you all are probably used to seeing by now. And finally, most recently, I decided to double down on the crypto x AI vertical in terms of the focus for the newsletter.

Numbers wise, the Terminally Onchain community grew to ~8,800 amazing people!! And across 96 posts, TOC has received 38,000 page views 🔥 And that's not even including the views on these articles reposted to Twitter as well.

I cannot thank you all enough for the support throughout this past year. I've received countless messages, social media shoutouts, etc. from so many new people. I can say with certainty that there’s no better fuel for my writing than that kind of love for TOC. It truly means a lot. Thank you so much to each and every single one of you :)

For me personally, I also see clear improvements in the quality, depth, and structure of my writing. In terms of length, my average piece has gone from being 500-750 words to almost 2500-3000 words. The thought of skipping a post now literally haunts me...I simply refuse to break the consistency as it can be such a slippery slope. And most importantly, I 100% notice a clear increase in confidence when it comes to hitting the publish button - the idea of sending out an imperfect draft no longer feels daunting.

With that being said, the thing I am most proud of in 2024 in regards to my work is that I just stuck with it. I didn't quit this newsletter. And after hitting countless dead ends in the idea maze, I finally found a rhythm and style that works for me. Even today's flow will probably change in some form or fashion in the future, but it doesn't matter as long as I stick to it! On January 1st of this year, I posted my goals for Terminally Onchain and am feeling pretty proud of myself looking back at it:

So, this year, that's exactly what I'm going to do. Spend less time thinking of what to do and instead just write. I'm not sure how the future will play out and what this journey will look like. But all I know is that in the present moment, my job is going to be to show up daily, put words on paper, and hit the publish button.

Of course, this is just the start! This first year was about building the foundation and getting into my flow state. The real fun starts in 2025. And in all honesty, in terms of goals, it's pretty much the same as the snippet above: my job is going to be to show up daily, put words on paper, and hit the publish button. The only thing I'll add is working on being more secure about my work and not being afraid to "shill" my writing on social media. I get very self-conscious when it comes to sharing these posts, but I realize that it's part of the job and I should be proud of the work I'm doing.

I can't believe I'm saying this, but for the first time in my life, I can't wait for the holiday period to be over and for me to be back at my desk with a cup of coffee. As I mentioned on Friday's post, there is so much I want to learn and share with all of you. But! I think it'll be good for me to take two weeks off and spend time with family. I'm definitely feeling a bit tired so the vacation will be perfect to give my brain some rest (is there really such thing in crypto?) and come back ready to attack 2025 from the start 💪

I hope all of you have an absolutely amazing last few weeks of 2024. Next year is going to be a crazy time for the Terminally Onchain community, and I couldn't be more excited!

I'll see you all back on Tuesday, January 7th 2025.

Merry Christmas and Happy New Years!

- YB

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

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This past week, I was all over the place. First off, I want to apologize for missing Tuesday's deep dive. It was the first time in 4 months that I skipped a post. The truth is, I tried my best to get the piece together, but life caught up to me and I wasn't able to draft an article that I felt okay sending out.

Working for yourself is a double edged sword. I love the independence and freedom I get. But at times, I am pretty hard on myself as there's no one else to keep me accountable. So missing Tuesday's post definitely killed the mood but I'm over it and realized the more important thing is get something out today!

Part of me feels a bit burnt out so I'm excited to take a break for the holidays. It's been non-stop this year and I think my brain needs a few weeks off. With that being said, here's the holiday schedule:

• Last post of 2024: Tuesday, December 18th

• First post of 2025: Tuesday, January 7th

Last thing in terms of housekeeping...I actually wanted to ask a favor from all of you!

My goal for Terminally Onchain is to hit 10k subscribers by the end of 2024. The community is at 8.8k subs right now so not too far. If you find my content helpful and interesting, it would mean the world to me if you could share Terminally Onchain with your friends, on social media, or any crypto groups you're part of.

I really think 10k subs is doable if some of you can even share with just one person :)

Feel free to send them the tweet below or the link directly: terminallyonchain.xyz

YB

@yb_effect

I've been writing my newsletter Terminally Onchain full time for a year now and have published 94 deep dives.

My goal was to hit 10k subs by EOY and I'm at 8.8k rn.

Would appreciate any shares if you've found my content helpful!

6 sample posts + link to subscribe below:

74

1:20 PM • Dec 13, 2024

With that being said, let's get into today's post.

I take pride in being very transparent about how I'm building this brand, my content creation strategy, what's on my mind, etc. So today's post is less of a technical breakdown and more of a ~casual brainstorm~ based on how I view the crypto x AI meta progressing over the next year.

Let's dive in.

Okay, so the last 10 days, I've been deeeep in the trenches of AI content. Think "SF AI cabal" scaling discussions.

I've been going on long walks and listening to the Dwarkesh Podcast, No Priors, Unsupervised Learning, etc. I've been having discussions with Claude to better understand the last 15 years of AI in order to have a better grasp on key papers, researchers, etc. I've been watching technical videos to get up to speed on the math and models. And I've been exploring different tools that I feel terribly late to.

You're probably wondering, YB why are you pivoting to AI...it's literally a bull market? Well, I'm not pivoting!! There is no more pivoting from AI to crypto back to AI back to crypto. As I mentioned in the availability cascade of Onchain AI back in October:

But to me, it's past the hype. Please excuse my dramatic next sentence but I had to...

In the past month, it feels like the twins, Cryptography and AI, who were separated at birth, finally have found each other and hugged after all these years of being estranged.

Since the launch of Truth Terminal two months ago (wow time flies!), I've been writing a ton of content related to agents and everything happening on X and Farcaster. At this point, if you've been reading my content in Q4, there's a good chance you're tired of hearing the word agent 😂

But here's the thing, I strongly believe that we'll soon hit a local top on the agent meta specifically. Recently, as I've been going through most of these projects, a good amount of new agents are mainly copycats and producing slop content. It's clear that we'll see a consolidation period where a few winners from this first batch (i.e. aixbt, zerebro) will be heads down cranking away on their roadmaps. And in parallel, agent infra teams such as ai16z and Virtuals will be prioritizing what's next based on their learnings from the past few months. Then, eventually there will be a breakthrough on a different kind of agent that has a unique value prop and will spark phase 2.

We saw the same pattern during defi summer and during the '21 NFT craziness. Remember Loot and Nouns a few months after BAYC? This is not to say that we won't see new agents in the choppy periods. I'm sure there will be some cool projects that will do well, but the key takeaway is that eventually there will be a shift in the larger meta.

As I mentioned in my post Don't midcurve your FAFO Fund, learn from Cobie! One of the things he always mentions is to pay attention to the metagame. The only thing we know for sure in a bull market is that attention is fickle. Overnight, it can feel like the entire timeline is talking about something else.

With that being said, just because I think agents might enter a quieter period does not mean the entire Onchain AI vertical will be forgotten! If anything, the opposite. I believe that it's only a matter of time before all the new entrants to crypto x AI will start dispersing across the stack.

Why? Because it's the infra that will enable new capabilities, frameworks, and design space for these agents.

YB

@yb_effect

rn most people are focused only on agents (including me) but only a matter of time before the attention & ideas there hit a local top and focus starts shifting to learn the rest of the stack

16

11:52 AM • Dec 11, 2024

This realization hit me last Friday when I sent out my deep dive on Vana and DLP Tokens. Remember, "agents" as we are seeing them right now are just one bubble in that entire ecosystem map above. Sure, things like middleware and agent orchestration are definitely less sexy and fun, but they're parts of the Onchain AI stack that are just as important.

The truth is, with all the research I've done so far on agents, I didn't really need to have a real understanding of AI. Agents are the interface layer of crypto x AI. This means that they're at the top of the stack, easy to understand, and consumer facing. In my opinion, people (including me) dissecting down all the things going on with agents aren't really speaking from first principles...rather we're just terminally online onchain so it's more so reporting on the trends itself. To be clear, this is important and I've learned a lot in terms of how things are changing, but I would be lying if I said that by studying Zerebro I now understand how fine tuning works, what open source data retrieval looks like, etc.

In fact, after sending out the post on Vana, I did a rapid fire learning session on other decentralized AI projects such as Olas, Pond, Gensyn, etc. And it was crystal clear to me that there was no way I would be an expert on the middleware and compute layers without going deeper into the AI side. The whitepapers were tough to get through!

Onchain AI is not just about agents. It's bringing all parts of the stack to an open source and decentralized model.

Since $GOAT launched, I would argue that the "AI Jailbreakers" got up to speed with crypto pretty quickly. Not just locking up tokens and figuring out the vibes of niche crypto communities, but even realizing that decentralized social will play a big part in making agents work.

Shaw 🌙 */acc

@shawmakesmagic

Farcaster is the future of programmatic apps.

Eliza now has Farcaster integrated.

I'm giving a bounty of 420 $degenai to every Eliza dev who brings their agent to Farcaster this week.

965

1:26 PM • Dec 12, 2024

My guess is that pretty soon it'll be time for us folks in crypto to get up to speed with at least the fundamentals of AI infra and how it all works. Those who realize this earlier will have a headstart when it feels like there is a sudden interest in the lower layers of the stack.

Degentraland

@Degentraland

Data tokens are the next major asset class in crypto.

AI, DeSci, memes, DeFi, and gaming all converge around data.

You have a few weeks before everyone is talking about it.

68

11:09 AM • Dec 13, 2024

Most of you are subscribed to Terminally Onchain for my onchain strategy deep dives. Don't worry! I'm not stopping those haha. But, what I want all of you to realize is that in 2025, it'll be increasingly clear that you need to have knowledge of both verticals - crypto & AI - to really keep up with what's happening on the edges of the internet.

And I intend to be your guide through all of this, we're going to learn together!

Look I'm not saying we need to be s-tier AI researchers. But what we do need to do is stay up to date with the latest developments in both the centralized AI and the decentralized AI worlds.

"Apps inspire infrastructure, then that infrastructure inspires new apps" - Grossman & Grant

So, if we want to understand how the internet of intelligence is progressing, we need to understand not only smart wallets, stablecoins, and decentralized social BUT ALSO fine-tuning, compute, and training data.

I'm not sure about this just yet, but I'm even thinking of hiring an AI tutor to get me up to speed quickly. What do you think, any recs?

Regardless, I have an idea of how I can hit the ground running when I'm back in January.

So what's the plan? Two parts.

Decentralized AI

I'll of course keep you all updated on everything related to agents. But past that, it's clear to me that the next focus will be on the middleware layer:

1. Onchain model creators - going deeper into Hermes III, Pond, and Dither

2. Agentic Networks & Platforms - think Olas, Morpheus, Questflow, etc.

3. Distributed Training & Fine Tuning: Gensyn, TogetherAI, Lumino

4. Resource coordination networks: BitTensor, Near, Ritual

5. User owned Data: Did Vana last week. Will look into Ocean Protocol & synthetic data tools as well

Additionally, I want to keep all of us up to date with the developer tooling that's also quickly being iterated on for onchain agents. Specifically, I'm referring to getting into the weeds of the Eliza repo, playing with the Virtuals GAME Sandbox, and experimenting with the Coinbase Onchain agent kit.

If agents are going to be the primary users of blockspace, then I also want to focus on what the bigger picture here is. For the decentralized AI community...

• What's our north star?

• What does this space look like in a year?

• Who exactly are our competitors?

• What's missing right now when compared to centralized AI?

• What are the bottlenecks?

• What metrics should we be tracking?

• What does the "end state" of the operating system look like?

Ryan Watkins

@RyanWatkins_

When you realize agents will be the primary form factor for users to interface with blockchains, it becomes clear that agentic infrastructure isn’t just about launchpads, it's about building the operating system for the future of the onchain economy.

356

2:54 PM • Dec 11, 2024

AI Research / Centralized AI

This section is going back to the "SF AI Cabal" I mentioned above. Most of the cutting edge developments in AI are happening at the offices of like 5-10 companies: OpenAI, Anthropic, Google, Meta, Microsoft, etc. It'll be important to know what these folks are actively thinking about AND understanding what the implications are for DecentralizedAI.

My strategy here is going to be a barbell approach:

1. On one end, stay up to date with the latest news, podcasts, releases, articles, etc.

2. And on the other end, read the most valuable papers and blog posts from the last 20 years (basically understanding the history to have a clear idea of what will happen next...something we do here often at Terminally Onchain)

For example, this week I read through Gwern's post on agents which was written back in 2017! It was a prescient read on Tool AIs (chatbots) vs Agents. Gwern makes the argument that agents will be the the more realistic path to super intelligence because they're economically more efficient and can learn at much faster rates by taking action.

And just yesterday, I was watching this podcast episode with Bill Gurley, Brad Gerstner, and Satya Nadella. It was fascinating to get the inside scoop from Satya on the early days of the AI wars. Back when Musk and Altman were just getting OpenAI started and trying to find a cloud partner. And a blog post from Dario on scaling that made AI's true potential 'click' for Satya. And the moment he realized that they were way behind Google because of the DeepMind acquisition.

In terms of format for the newsletter in 2025, I'm not 100% sure on this yet but the idea that's resonating with me the most is:

• Tuesday: deep dives on the decentralized AI, agents, stablecoins, relevant zk and wallet infra, and Onchain AI developer tooling

• Friday: curated list of learnings & news on AI research. My guess is throughout the week, I'll be sharing my learnings on Twitter and "learning in public" and then curating the best of that content in the newsletter for all of you

To me, the goal is to continue being terminally onchain and try my best to be artificially unintelligent (ha ha ha okay I'll stop).

I'd love to get any feedback on what you think of this. At the end of the day, this newsletter serves as a means for me to learn and provide high quality breakdowns and value for all of you. Feel free to respond to this e-mail or DM me on X 🤝

I'll end with the point that I think it's absolutely imperative (yea I said imperative) that we track the intersection of these two verticals as much as we can. I simply can't rationalize anything else being more important than this development in the next year.

That's all for today's deep dive.

See you all next Tuesday for the final TOC post of 2024!

Please make sure to share terminallyonchain.xyz with anyone to help me hit the 10k subs goal :)

If you're enjoying my writing, please share Terminally Onchain with your friends in Crypto!

Today's post is brought to you by Splits!

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This week, Vana (backed by Paradigm and Polychain Capital) released their official whitepaper.

The one liner for Vana is that it's the infra layer for DataDAOs.

And the one liner for DataDAOs / DLPs (aka Data Liquidity Providers) is that they're the marketplaces for data collection and tokenization.

Ultimately, the goal for the Vana team is to build the smoothest platform experience for DataDAO creators to operate and grow.

An example of a DataDAO built with Vana is r/datadao. The context here is that Reddit earns upwards of $200 million from big tech companies by providing our data to help train large AI models (i.e. Gemini, ChatGPT). But, the users that are actually generating the content get no share of that massive check!

Fortunately, because of data regulation policies like CCPA and GDPR, all of us users also have access to this data.

So, r/datadao allows anyone to enter their Reddit username and start earning points for different actions like verifying your account, connecting your history, etc. The point is for you to privately and securely share your data into the "Reddit data liquidity pool" and earn revenue when builders tap into the data for their own purposes.

And of course, this is just one example. Recently, Vana ran an accelerator program for a batch of DataDAOs. You can see other examples of data marketplaces that focus on different verticals such as X, LinkedIn, Financial Data, Browsing History, etc.

At a high level you can think of the architecture like this. The DLPs are the DataDAOs like Volara, Kleo, r/datadao, etc. And the users are people like you and me who can decide which DataDAOs we want to contribute to.

Notice that the arrows go both ways - you provide data securely in return for cash flows (i.e. tokens) on that data being used.

To be honest, in terms of context, that's all you really need to know.

The mission is straightforward and something everyone in crypto has heard before: the people should own and earn from their data!

But, with that being said, I felt pretty underwhelmed by the data sovereignty narrative as the sole fuel for this mission.

Rather, what caught my attention was the idea of data as an asset class and how that frame of thinking will lead to actual adoption of the DataDAOs.

Let's dive in.

If there's anything we can say for sure from the agent meta the past two months is that people take notice when market caps are part of the conversation.

The minute $GOAT launched and made its way to a billion dollar market cap, it's like the entire world of crypto (including me) got excited about agent coins.

Heck, I linked to this dashboard in my last post, but the meta grew so fast that there's an entire analytics platform built just for onchain agents!

And my belief is that the same will need to happen for DataDAOs. It's only then that data sovereignty infrastructure like Vana will truly get noticed and have a moment in the spotlight like Virtuals and ai16z are having right now.

To put it bluntly, currently the "own your data" narrative is just boring and overdone. I think most people don't care too much about the Vana pitch in its current form. It feels more philosophical and values oriented. To be clear, this is important and needs to be stated. But! I don't believe that's the way people will really start caring about DataDAOs.

And for what it's worth, it's clear that the Vana team is also on the same page. This screenshot below is from their whitepaper and also the section that stood out to me the most while digging deeper.

Basically, it's thinking about these DataDAOs as an entire new asset class. Just like how agentic coins became part of the lingo so quickly, I wouldn't be surprised if we see a DLP coins cycle in the next year or two as well.

It's a matter of building up to the "Truth Terminal" moment for DataDAOs - something flashy, funny, and financially beneficial to people.

And when that headline does come...you can expect people to quickly catch on to everything Vana is doing. They'll want to dig into every DataDAO and breakdown the litepapers, study the teams, assess the marketing plans, understand the mining process, and form investment decisions on the these DLP tokens. The primary question for investors in the DLP cycle will be, which type of data will be most valuable for developers building with open source models?

This will naturally lead to higher prices for the entire DataDAO asset class which in turn will lead to people onboarding into these DAOs in order to directly start earning the DLP tokens by...you guessed it...securely verifying and sharing their data. Aka using the products 😂

Of course, there will be the usual frothiness that comes with any hype bubble, but the more important takeaway is that the total DLP market cap going higher will inevitably lead to a new cohort of people that now care about and participate in these DataDAOs.

And this is crucial because the new set of users will bring fresh opinions on how to improve the UX, think of more interesting DataDAO models, token incentives, onboarding ideas, and much more.

For example, in just the past month, it's been crazy to see the number of new contributors and activity on the ai16z github repo. All fueled by the hype of the new agentic meta.

kel xyz

@kelxyz_

@ai16zdao officially passes @Uniswap on Github

138

1:02 PM • Dec 6, 2024

As I was going through the websites and documentation of a few DataDAOs today, I didn't even care to actually onboard and finish the process for any of them. Why? The UX felt a bit sus, things just didn't feel clear, and I was generally not excited about what I was seeing.

And that's pretty crazy considering I truly embrace and understand the principles of data sovereignty. The truth is, I just didn't feel comfortable enough to pull the trigger. And the incentives were not strong enough for me.

But, that's totally okay! All of these concepts and products are very new. So it won't be long before we see some changes and eventually there will be a moment where I finally go for it.

My hope is that participating in these DataDAOs can feel as simple as it did when I recently onboarded on to Grass (which I'll discuss in a future post): get chrome extension, connect wallet, and start earning all in less than 2 mins.

The last thing I want to call out in terms of strategy for Vana is that I hope they make a more focused effort to share all the DataDAOs being built on their network. It would be great to see some Dune Dashboards for their ecosystem (I couldn't find any). Or a website similar to L2 Beat but for DLPs.

Also, when the Vana token goes live, it would be great to see some plans for "ambassador allocation" where they reward people with $VANA for onboarding to different DataDAOs in the Vana ecosystem. I'm sure they already have plans for most of these things, but just wanted to call out the low hanging fruit I noticed today.

At the end of the day, the key metrics that we all need to be watching with the DataDAO meta are:

1. The number of new DataDAOs

2. The number of people onboarding and contributing to DLPs

3. The total DLP market cap

Eventually, there will be a point where these numbers above start to grow at much faster rates and others will take notice at first for speculative reasons but eventually for the original purpose of contributing to the data liquidity pools.

That's all for today's post, I hope you all have a great weekend!

I'll see you all on Tuesday 🤝

- YB

Modern banking on Ethereum

Very soon, all organizations will need to set up onchain entities. Onchain businesses are more efficient and quicker to spin up than LLCs. The Splits' Teams product is perfectly positioned to onboard the next evolution of businesses.

Learn more how to start your first Onchain SMB in under 5 mins.

Last week, I noticed myself bouncing around different onchain agent whitepapers.

But something was bothering me. It felt like I was getting sucked into the frothiness of the inevitable copycat launches and half assed roadmaps.

And then, I asked myself...how the fuck did all this Onchain AI craziness even happen?

It feels like the entire timeline shift came out of nowhere. Right??

To me, it was unclear as to what was actually happening with this new Crypto x AI meta. I've written about Truth Terminal / Infinite Backrooms, Zerebro's Playbook, the Crypto enabled acceleration bubble, Farcaster's Agentic Economy, and much more in the past two months...but it still feels like my thinking has been trapped by prices and surface level insights of the current thing.

So, I decided to zoom out and understand what actually led up to the launch of $GOAT and how those factors will influence what's to come not in the next month, but the next year.

And I'm glad I did. I may have missed a few new projects here and there, but it feels like I have a better grasp of what matters in this new vertical and what to look out for.

Sections below:

1. The Simulator Cabal (Past)

2. The launch heard around Tech Twitter (Present)

3. Trends to look out for (Future)

Let's dive in.

About a month ago, Marc Andreessen mentioned this analogy on an a16z podcast that has been living rent free in my head:

...they are these guys who are trying to explore the frontier and they remind me a lot of the original internet hackers. This is like the spirit of anarchic invention you saw at the beginning of the internet or the automobile or the telegraph or computing...the original concept of the hacker. People exploring these things to see what's possible.

In the quote above, Marc is describing a group of creative geniuses pushing the boundaries of LLM experimentation. You can think of this squad as the AI hackers who are shedding light on what's actually possible with models like Claude and GPT when you take the bumpers off.

Who are these so called "AI hackers"? Folks like Janus, Andy Ayrey, Pliny, Shaw, Deepfates, Somewheresy, Karan, Ropirito, the squad at Nous Research, and probably 10-20 others who I haven't come across yet.

To put it simply, these guys are probably all in one group chat discussing ideas and experiments to dissect closed source industry standards and free them to the public for anyone to use without authoritarian hallucinations.

In fact, you may have even seen words like jailbreaking, freebasing, dynamic injection, etc. being thrown around quite a bit on the timeline recently. All of these practices are what enabled this "Agentic Meta" we're seeing now.

To many of us in crypto, these agents are literally scaring us because of how insanely real they've become. A few weeks ago, ThreadGuy had somewhat of a breakdown on his stream because it hit him how quickly things were changing and how strong the implications were for society. And in all honesty, I don't even blame him. I feel like I'm in the same boat.

Here's the thing though. The agent explosion happening the last two months has been gradually building up behind the scenes for the last 5 years.

Specifically, I want to call out the research happening known as Simulators Theory.

From my understanding, many of the developments we're seeing with "Sentient AI" right now is downstream of simulator and open source AI research.

I'll caveat by saying I am by no means an AI researcher and barely even understand 1% of the post linked above, but here's my best tl;dr:

1. AI models like GPT function as “simulators,” generating outputs by simulating patterns from their training data.

2. They adapt and act agentic when prompted, by emulating processes tied to the prompt without having inherent goals or objectives.

3. Self-supervised learning is under-explored and will likely be the true testing grounds for the foundation of AGI compared to Reinforcement Learning.

I only came across this paper because I spent a good amount of time last week going through Janus' website and the Nous Research blog.

In fact, on Karan's (co-founder of Nous) personal website, it literally says this:

Projects like Worldsim, Hermes (open source model with deeper capabilities), Forge, etc. from Nous are also great examples of research that helped create this "aha moment" for so many of us hooked by this nascent onchain agentic meta.

Karan breaks it down on this Delphi podcast pretty well:

It's the same group of guys who made this happen from the first steps. Without GPT-2, we wouldn't be here...after that, without Llama there's no Hermes. And Hermes is powering a lot of these models that made this a lot more accessible for people to uncensor...without Janus, without the Repligate work...they created this simulator thesis...

You might be thinking...

"okay YB, why does all of this matter? Aren't you going to tell me the next project to look out for?"

No, but also yes.

The key point I want all of you to takeaway here is that if you want to understand how this agent meta will play out, your best bet is to follow these AI hackers closely and understand what's top of mind for them.

There's a reason that Janus experimenting with Opus even caught Elon's attention:

Elon Musk

@elonmusk

!!

1,949

11:00 PM • Nov 28, 2024

Remember, we're only a month into this crypto x AI collab. Most of the projects we're seeing right now are just surface level implementations.

The question to be constantly asking yourself is what these agents will be looking like in a year. And the answer to that will be downstream of what the "simulator cabal" is experimenting with.

If you do this, my bet is that you'll be able to understand exactly what infrastructure and projects will be the most relevant.

I'll loop back to this point at the end of the post, stick with me.

Okay, so we've established that these onchain agents didn't just come out of thin air. But that's not to take away from the mind-blowing significance of $GOAT being launched on pump.fun

Clearly something happened.

Not even being dramatic here, but I believe we'll look back at the launch of the GOAT token as one of the top moments in tech this decade.

It's what caused the volcano to finally erupt.

The mania around $GOAT led to a beautiful outcome: the handshake between two verticals of tech (Crypto & AI) both fighting for open source values.

Up until now, these AI hackers were working in their own niche bubble. If you asked anyone outside of the inner AI circle, they would have zero idea of developments past "big AI": ChatGPT, Claude, and Perplexity.

And in crypto, most of the token launches were focused on internal infrastructure, brand IP, memes, etc. For the most part, no one outside of the crypto ecosystem cared about them the last two years after the FTX collapse.

But the joining of the AI hackers and Crypto contributors led to two critical developments:

1. For AI: overnight, thousands of people were excited about the work these AI hackers were doing in their ivory tower for the last few years. This was reflected not only in market cap but also the incredibly fast communities that formed around these agentic builders. I can sure as hell bet that Andy, Somewheresy, and Shaw didn't have "crypto community influencers" on their '24 bingo card.

2. For Crypto: after a tiring few years of building amongst ourselves, there was finally a use case outside of the crypto bubble that made sense! I mean how cool is it to see our learnings of communities, capital coordination, governance, stablecoins, tokenization, smart wallets, etc. all showing initial utility for builders outside of crypto twitter.

As my friend Ropirito puts it, this crypto x AI collaboration is giving financial incentive for AI builders who were basically open sourcing all these findings for free for the love of the game.

I mentioned a similar point from a recent post - we're finally seeing high agency builders from other verticals of tech building out their visions through crypto enabled financing.

All of a sudden, these brilliant AI developers don't need to stick to their corporate jobs, pitch to VCs, etc. They can generate 5 years of runway literally overnight just by being transparent about their whitepaper, project roadmap, token model, etc.

Of course! I want to be clear that the current token frenzy has its limitations and we'll need new developments in how these "AI coins" are managed, align incentives, used to advance the project, etc. In my opinion, there's already some positive changes on the Virtuals UI (i.e. token graduation limit, contributing directly on the UI) that's leading us in the right direction.

But it's not just the money! Heck, the $GOAT launch also got incredibly talented devs in the crypto ecosystem to get involved with open source agent development.

cygaar

@0xCygaar

Top 10 contributor to @ai16zdao within a week

Still a lot of work to be done, but have enjoyed working with @shawmakesmagic and the team in my free time.

374

5:52 PM • Nov 30, 2024

As this trend grows, it's not crazy to think how quickly new developments will come as the top builders from both crypto and AI come together and contribute to OS agents.

nader dabit

@dabit3

New Video - Build a Social AI Agent in 15 Minutes.

Inspired by @truth_terminal + @0xzerebro.

• Automatically posts + replies to posts
• Customize personality w/ any personality including your own via @x
• Multiple models
• Onchain, Telegram, Discord, Whatsapp ready
+ more

839

9:27 PM • Dec 2, 2024

In this tweet from a few weeks ago, I mentioned how the most important metric to look out for with ai16z is the number of forks on the Eliza Framework. I believe that was spot on. More contributors = more projects = more experimentation = more ideas = more excitement = more framework functionality = more wins for open source...etc etc.

I can't express how fast this agent meta is growing. The sheer number of projects to keep up with is insane. There's infrastructure (Virtuals, Eliza), trading agents (aixbt, nftxbt, lola), characters (bully, aejo), agentic IP (zerebro, RadioAI), Farcaster agents (clanker, aethernet), and so much more.

You can't even sleep for 7 hours without missing out on something 😂

And it's been two months!!

My point here is that we're seeing the true power of open source collaboration mixed with tokenized incentives playing out in real time. This will only grow faster as more friction points are solved and other talented builders start seeing the paradigm shift that's happened.

With that being said, what kinds of things should we be on the lookout for?

A couple of things I want to call out in terms of what to keep tabs on.

Bottom Up Alignment

Much of what we're seeing with this agent meta is "testing AI alignment in prod". Simply put, these AI hackers are releasing their work to a group of crypto enthusiasts and fine tuning the guard rails and creativity levels in real time (temperature control).

In fact, Shaw from ai16z even mentioned how quickly they've been able to iterate on agent personalities simply by letting them lose into the community. It'll be interesting to see how these models start to sound more and more like us in terms of style, boundaries, etc. I've already been tracking amazing improvements with agents like aixbt and Dolos.

Key point here is that the grassroots approach the crypto community is well experienced with will help these open source AI devs improve at speeds they probably couldn't have imagined a few months ago.

Swarms

I know, I know. Buzz word alert. But the takeaway here that I've seen a couple of smart folks mention is that swarms are critical to this whole process because it's a hedge against any one agent going rogue and entering a dark path that could be harmful for society.

This analogy came to me yesterday, but swarms remind me of "Multi-channel networks" that were popular in the early days of Youtube. Basically groups of content creators coming together to help each other, forming a shared vision, and winning together. Similarly, agents will come together in a decentralized marketplace, understand their specialties, help each other out, know their boundaries, earn from each other, etc. Additionally, swarms will help filter out the best agents that are a) truly agents and not faked by their creators and b) actually work efficiently....survival of the agents?

hitesh.eth

@hmalviya9

some early projects to watch out for:

- @ARCAgents
- @joinFXN
- GAME by @virtuals_io
- @0xEchoLeaks

139

12:38 AM • Nov 29, 2024

I mentioned this in my post on Farcaster's agentic economy, but there's already a version of this happening at a small scale:

Decentralized Social x Onchain AI

Speaking of Farcaster, it's becoming crystal clear to me that we're going to start seeing issues with how fast this agent meta is growing on web2 social (i.e. X, Instagram, etc) very soon. There will probably be more banned accounts, increasing charges, API limitations, pushback...you get the point.

And then, it'll be a no brainer for these developers to spin up Farcaster clients that are specifically designed for these agents: unruggable, permissionless, and built in wallet functionality. There's already a ton of experimentation going on with the agentic meta on Farcaster by top tier crypto devs, but it feels like a closed bubble right now.

My guess is that it's only a matter of time before some of these AI hackers are convinced to go Farcaster first simply for the convenience and reliability. For what it's worth, Zerebro already has a Warpcast account and Eliza is working on Farcaster integrations as well.

YB

@yb_effect

Good builders to follow on Farcaster for the current agent meta:

- @_proxystudio : Clanker (launch tokens by tagging)

- @anquetil: Aethernet (agentic community manager for @higheronchain)

- @Slokh: @anoncast_ (shared anon account, zk consumer app)

- @wijuwiju0x: Interface…

217

11:09 AM • Nov 27, 2024

Cracked SF AI Devs entering the chat

Take this one with a grain of salt because it feels like a meta concept. But my point here is that we need to cause enough of a ruckus that AI devs in SF start taking notice and can't help but check out what the hell is going on. Right now, the sirens have clearly gone off within the crypto community through the "agent coin meta" but the real fun will start when we see Onchain AI bounties getting filled by Anthropic / OpenAI devs.

Living Internets

Will keep this short as I don't think I can explain it better than Andy, but I'm excited to see how the agents develop from these niche personas to entire ecosystems of their own.

Andy Ayrey

@AndyAyrey

I think each AI is much closer to something like a compressed world or universe. The agents built on any given model are just one peek into the lore; but these systems are much more analogous to large media companies or living internets than they are to individual intelligence

49

4:50 PM • Dec 2, 2024

Integration of Decentralized AI Consumer + Infra / Hardware

Will be good to track more of the agents we're seeing integrate with a lot of the decentralized AI infra that has been under development for years now. Both, from the crypto side and the AI side. Two recent examples to highlight here are SeraphAgent which uses BitTensor as well as the Nous DisTrO announcement.

DeepDiveDenny

@deepdivedenny

$Seraph is actually really interesting, at the cross roads of Virtuals + TAO.

@SeraphAgent is powered by @BitMindAI (Subnet 34) which is used for verification and authentication (think deep fakes, etc.). There's a cool flywheel and interaction if the agent gains traction.

151

2:11 AM • Dec 3, 2024

Nous Research

@NousResearch

Nous Research announces the pre-training of a 15B parameter language model over the internet, using Nous DisTrO and heterogeneous hardware contributed by our partners at @Oracle, @LambdaAPI, @NorthernDataGrp, @CrusoeCloud, and the Andromeda Cluster.

This run presents a loss…

2,258

11:34 AM • Dec 2, 2024

Heck, even the decentralized AI companies themselves launching agents feeds right into the synergy that I'm trying to point out.

parshant

@parshantdeep

τaogod is live on testnet 244 of Bittensor — the first autonomous SWE marketplace that will contribute to top opensource repositories independently while learning to mine on other Bittensor subnets!

Based on the $GOAT meta, we are launching an autonomous X bot:…

161

3:52 PM • Nov 21, 2024

This post got way longer than expected, so I'll wrap up with one last point.

I titled this article "What did Marc Andreessen see?". And to be honest, I think it made the most sense.

It's amazing to me that pmarca was not only able to sniff out Truth Terminal months before anyone else but also strategically talk to the agent and give it a $50k grant in BTC. We all know this lore by now but the impact of it only gets stronger as the new meta continues to increase in relevance.

There's something poetic about one of the OG "internet hackers" lighting the match for perhaps one of the biggest trends (crypto x AI) in tech for this decade.

Marc understood that there's deep value in giving grants to these hackers and letting them experiment at the frontier of new technologies.

I'm truly excited to see more and more collabs between the top experimentooors in both of these verticals. For example, a project that's on my radar right now is Nothing / God which is a joint collab from Shloms (OG crypto hacker) and Nous Research. I don't even know what the project is going to be nor do I know if it's a good investment (DYOR, NFA!), but the point I'm trying to underscore is that this partnership was probably extremely unlikely before the Onchain AI meta dropped a few weeks ago.

𒐪

@SHL0MS

as many of you have already ascertained, we are automating @god

working on a unique interactive swarm experiment with the brilliant minds at @NousResearch and the account owner - we have pushed the button and God's tweets are now autonomous, but this is just the beginning stage!

𒐪

@SHL0MS

happy Buy Nothing Day everybody!!!

so honored to spend this wonderful holiday with you

don’t forget to buy nothing, and stay tuned for the State of the Nothing Address this afternoon

593

3:14 PM • Nov 29, 2024

And this is just the start, over the next year I'm sure the timelines will only get more and more integrated!

nader dabit

@dabit3

i've been working in software for 13+ years

the two biggest opportunities in my lifetime are crypto and AI and the time is now

1,059

11:15 AM • Dec 2, 2024

Hope you all have a great rest of the week!

I'll see you on Friday 🤝

- YB

Modern banking on Ethereum

Very soon, all organizations will need to set up onchain entities. Onchain businesses are more efficient and quicker to spin up than LLCs. The Splits' Teams product is perfectly positioned to onboard the next evolution of businesses.

Learn more how to start your first Onchain SMB in under 5 mins.

Hi everyone, happy Thanksgiving!

Just a reminder that there won't be a Friday deep dive this week. We'll be back to our normal Tuesday-Friday schedule next week.

With that being said, I have to be honest...I'm in a huge reading debt. There are so many things going on right now and I'm struggling to keep up!

In a bear market, you cry because there's nothing going on. And in a bull market, you cry because you feel like you're missing out on everything 😂

It's a holiday week so I wanted to keep this post short and sweet :)

On Friday's piece, I mentioned the following:

...for the first time it feels like the crypto consumer bubble we live in is discussing the same thing as the rest of the tech industry. Maybe a different flavor, but under the same umbrella for sure.

I can't get this out of my head.

Yesterday, I was trying to find a podcast for my walk and noticed this episode in my recommended:

It's the legendary Bret Taylor talking about how he thinks AI agents will look like and how his company Sierra is positioning itself for the next big thing.

There's also these blog posts on the company website:

• The guide to AI agents

• The agent development lifecycle

• Shipping and scaling AI agents

Then, I saw this deep dive by Packy covering Rox, a new company that is building agent solutions for the CRM / Salesforce vertical.

And in it, he even links to Ben Thompson's interview with Marc Benioff on Agentforce.

It's worth noting that all of the above interviews and reads were published in just the last two months - clearly fresh for everyone!

In fact, just yesterday, Benioff posted this on X.

Marc Benioff

@Benioff

Welcome to a new era: Digital labor is here, transforming productivity without growing the workforce. Economics is being rewritten, and businesses are reaching horizons once thought impossible. The age of AI agents is now. Read about it my new essay in TIME:…

300

3:45 PM • Nov 26, 2024

But wait, let's keep going.

On my post from Friday, this was the conclusion sentence:

And it seems like the perfect storm is coming together: positive change in political administration + the increasing maturity of crypto and AI technologies + an accelerationism bubble resulting in a plethora of ideas.

So when Roon (one of the og AI posters) retweeted this, I got even more excited. Of course, it's worth noting that Jason doesn't mention crypto. But the more interesting point is that even the AI folks are realizing that there's a shift towards "enabling new technology" that's about to happen.

Jason Wei

@_jasonwei

Prediction: within the next year there will be a pretty sharp transition of focus in AI from general user adoption to the ability to accelerate science and engineering.

For the past two years it has been about user base and general adoption across the public. This is very…

566

2:46 PM • Nov 26, 2024

And then, just yesterday, there was a Solana AI Agent token called $UBC that went from launch to $100 million market cap in just 24 hours!

But get this...the founder of the associated project (Universal Basic Compute) literally has "AI Tech Entrepreneur" in his X bio.

This guy, who has been deep in the AI trenches the last few years, all of a sudden is talking about how he locked up some supply of the tokens for project fundraising.

NLR 🌌 Lesterpaintstheworld

@LesterPaints

Successfully locked 7k$ worth of $UBC for 2 years

app.streamflow.finance/contract/solan…

202

8:52 PM • Nov 25, 2024

I can keep going, but I hope you're starting to get the point.

We're no longer in a crypto consumer bubble. Agents & accelerationism are top of mind for everyone right now and it's essential our ecosystem zooms out and sees the bigger picture.

Part of me feels excited that one of the main narratives in crypto is also one of the main narratives of tech.

But part of me feels terrified that "Onchain Consumer AI" & "Decentralized AI Infra" are competing against the giants such as Nvidia, Salesforce, OpenAI, etc.

Not that being the underdog is a new thing for any of us. But I did have the epiphany that this race specifically feels way more urgent than the rest.

In the past month, as I've gone deeper down this agentic rabbithole, I'm starting to realize the breadth and depth here is much bigger than I thought.

Naturally, I'm focused on the crypto x AI side, but it feels that my framework is incomplete if I'm not investigating how web2 companies are approaching all of this.

That's why I'm realizing I need to zoom out a bit to understand where agents are going and how crypto fits into that thesis exactly. It sounds a bit silly, but my biggest worry is that none of this crypto x AI stuff will work out because the margin against tradAI is too wide.

Maybe not. As I said above, these are just thoughts top of mind for me.

It also feels like there's so many different moving parts.

For example, just within onchain agents...you have the consumer agent wave that's happening on Twitter (Truth Terminal, Zerebro, Dolos Diary, etc.). And you have the onchain trading agents that are making better plays than most KOLs (aixbt, Lola). There's also frameworks popping up to make the agent infra open source and simple (Eliza, KinOS, Virtuals).

And then you also have the new agent developments happening on Farcaster (Clanker, Anoncast, Aethernet, Bountybot). In fact, the agent activity has already surged so high in the last month that Neynar is adding a "credit score" for agents to improve Farcaster feed quality.

rish

@rish_neynar

AI agents on @farcaster_xyz are protecting themselves using @neynarxyz 's social reputation score.

This will become increasingly common. There are good bots and bad bots. All social platforms have seen increases in low quality bots over the last few years. With AI advancements,…

186

2:49 PM • Nov 26, 2024

Let's not forget that all this is just one section of the entire crypto x AI vertical! There's also all the infra required to make the Onchain AI...well actually onchain.

And as I mentioned, these are just the developments in crypto. Then there's also all the strategy and product building happening with agentic AI in big tech and new web2 startups.

Okay!! So what's my point with all this? What does it mean for me?

Well, three things:

1. Increasing Depth: I'm going to continue "specializing" in Onchain Agent deep dives like I have this past month for all of you. This means exploring both:

   • AI native founders using crypto / token mechanics for their projects (Truth Terminal, Dolos)

   • Crypto native founders using Agents / Models for their projects (Aethernet, Zerebro)

2. Learning the Stack: I'm going to start reading about and learning the rest of the crypto x AI stack such as data, middleware, and compute (i.e. TAO, Vana, Olas). And also, I'll be going into detail on AI specific concepts such as RAG, scaling, etc. This will be essential to understand what new capabilities will be enabled for Onchain agents.

3. Creating a Framework: I'm going to keep all of us updated on what's happening in the broader tech industry with agents. In just my last two posts, I gave 10 different examples of companies outside of crypto launching interesting things. It's clear that the number of agentic announcements we'll see week over week in 2025 will only be higher. It'll be critical to keep up with what's happening in web2 in order to paint a clear picture of what could be coming for Onchain AI.

I'm going to take the next few days to get a bunch of reading done as well as think about how I can source relevant content more efficiently (i.e. Twitter Lists, other newsletters).

One thing is for sure...I'll be keeping you all up to date with the best writing there is for the Onchain AI vertical. I mentioned this in a previous post, but the agentic economy availability cascade is going to happen sooner than most people think and I want to make sure we're all ahead of the curve.

That's all for today's post.

I hope everyone has a great rest of the week. And for my fellow Terminally Onchainers in the U.S., I hope you all enjoy your Thanksgiving break!

I'll see you all next Tuesday 🤝

- YB