I know — you're probably sick and tired of seeing New Year predictions. Or, maybe you enjoy them. I don't know. People do like making (and reading!) predictions. It's kind of part of our nature.

I don't usually write prediction posts, but this year feels different.

AI is here. ChatGPT is used by, what feels like, virtually...everyone. Claude is too, and the exciting updates keep coming. We even have robots now—Waymo self-driving cars are already on the road.

If you’ve watched Stranger Things, you might remember from one of the earlier seasons where the residents of Hawkins, Indiana first discover the Demogorgon —a monster wreaking havoc and threatening to destroy the world. Once the resident heroes realize what’s truly happening, they know they can’t just tell people the full truth. No one would believe them. They’d sound absolutely insane! So instead, they create a palatable explanation that fits into people's existing mental models: there’s a chemical leak in the water.

I think about that analogy a lot when it comes to crypto predictions.

If I said outright that crypto and AI will aggressively eat jobs across every industry—from law to healthcare to e-commerce, manufacturing, and logistics—that software developers will be replaced and that Uber and truck drivers may disappear in a few years, that robots will become commonplace… I’d sound crazy! Even if it’s already happening.

So instead, I will make the shift to AI palatable.

What excites me about AI isn’t the moonshot, science-fiction version of the future (though that’s coming too). It’s the incremental change—the "slow at first, then everything all at once" way that AI will transform the products, apps, and tools I already use every day.

Since this is a crypto newsletter, this post will focus on crypto predictions—and, importantly, the growing interplay between crypto and AI.

But before going further, it’s worth addressing two questions upfront: first, what gives me any credibility to make predictions like these; and second, the obvious one—isn’t crypto mostly speculation?

On the first point, I recently wrote a post trying to explain, in simple terms, what I actually do working in governance and DAOs—a question I’m often asked by family and friends. I don’t take for granted that I get to work at the ground level of crypto innovation. That proximity is what informs these predictions. I’m not claiming to know exactly how things will unfold, but I do have a strong intuition shaped by working directly with teams building the next wave of finance and AI.

Before getting into where crypto is headed, it’s worth acknowledging where it’s been. Most people associate crypto with speculation—trading, gambling, prediction markets, and volatile assets that feel closer to casinos than infrastructure. And honestly, that perception isn’t wrong.

Speculation was crypto’s first mass-adopted use case.

When Bitcoin launched, its intended purpose was peer-to-peer electronic cash and censorship-resistant money. But the first thing people could actually do with Bitcoin at scale was trade it. Payments require merchants, norms, and trust. Speculation only requires buyers. Volatility attracted attention, capital, and builders, and markets formed long before UX, regulation, or social understanding caught up.

With Ethereum, the narrative expanded—toward smart contracts, programmable money, and the idea of a “world computer.” Yet the pattern largely repeated. The applications that achieved mass adoption were not productivity tools or everyday consumer apps, but speculative primitives: ICOs, DeFi yield farming, and NFTs primarily treated as financial assets.

This pattern isn’t unique to crypto.

Railroads, oil, telecom, and even the internet itself all began with speculative excess. Capital rushed in before demand stabilized. Many projects failed. But the infrastructure survived.

We wouldn’t have Google, Amazon, or Facebook without the experimentation and capital flows of the dot-com era. Speculation paid for the rails of the internet, as the graphic below shows.

Crypto’s speculative era has served the same function. And now crypto has reached its post-speculation moment.

Crypto wallets today are still too technical (I wrote a comparison of top Ethereum wallets in my post here). Users manually choose chains, select tokens, approve permissions, and sign transactions. Wallets expose protocol complexity, which for new crypto users, can feel intimidating overwhelming.

If you’ve used crypto before, the below screenshot of an Ethereum wallet looks familiar. If you haven’t, it probably looks intimidating.

With natural language interfaces built into crypto wallets, you will be able to simply write, "send $500 to Rika for dinner." The wallet will pick the cheapest rail (stablecoin, chain, and route), handle gas abstraction, settle instantly, and show you a beautiful receipt.

This shift to natural language interfaces has already emerged in the NEAR ecosystem with NEAR Intents. So this isn’t a prediction—it’s already here. The real prediction is that NEAR Intents will continue to integrate with more partners and evolve into a self-custodial, decentralized alternative to Web2 incumbents like Stripe and PayPal, which are layering stablecoins onto existing Web2 payment flows.

Rather than simply plugging crypto into legacy rails, NEAR Intents re-architects the rail itself—treating payments as outcome-driven intents, analogous to natural language interfaces for AI, and drawing on the liquidity, vibrancy, and composability of the entire crypto ecosystem as its backend.

A similar abstraction is emerging in the Optimism ecosystem with Actions, which simplify how users interact with onchain apps by bundling multi-step DeFi workflows—like lending, swapping, or payments—into single, human-readable operations. Actions abstract application complexity, making Ethereum-native finance feel more like using a modern app than navigating protocols and transactions.

As people increasingly mistrust large companies like Google and Meta with their data, private AI conversations will become a must. Using trusted execution environments (TEEs) and similar privacy-preserving infrastructure, we’ll begin to see private AI contexts where user data is processed and stored locally, rather than harvested for centralized model training.

Once again, this shift has already started and NEAR is at the forefront.

In a recent announcement post, the Brave browser outlined how it is using Confidential LLM Computing on NEAR AI TEE-enabled Nvidia GPU's, to enable browser-based AI that can process sensitive data without exposing it to the platform itself.

My broader prediction is that privacy-native AI will reshape industries built on confidentiality—healthcare, therapy, and law—where trust, discretion, and data sovereignty are foundational.

That said, this shift will come with an important caveat.

Sam Altman, CEO of OpenAI, has publicly warned about the confidentiality risks of using AI in sensitive contexts. These concerns are acute in the therapy or legal realm, where therapist-client privilege, and attorney–client privilege, is paramount. Centralized AI platforms, by design, can be subpoenaed or otherwise compelled to disclose user conversations—an inherent risk of custodial data architectures.

That said, just as crypto regulation has gradually matured, AI regulation will likely follow a similar path. Over time, clearer legal frameworks and technical safeguards will likely emerge to better align AI systems with the privacy expectations of the industries that they serve.

It’s easy to look at crypto’s history and dismiss it as a story of speculation. And for a long time, that criticism was fair. But speculation was a phase, not the destination. Crypto speculation funded experimentation, attracted builders, and laid the groundwork for what’s coming next—just as it did during the early days of the Internet, oil and gas, and railroads.

What feels different now is that technical abstractions are finally catching up. AI and natural language interfaces will make wallets usable for the average person. NEAR Intents and Optimism Actions are turning complex DeFi transactions into simple interactions that will be as easy to use as ChatGPT. And privacy-native AI is beginning to emerge, not as a promise, but as an architectural choice—one that reflects growing discomfort with centralized data custody.

Taken together, these shifts point toward a future where crypto fades into the background and becomes infrastructure: quietly powering payments, coordination, and AI-driven systems without asking users to understand blockchains or protocols. The real breakthrough won’t be when people adopt crypto, but when they stop noticing it altogether.

In this post, I’ve focused on the financial use cases of crypto—many of which are already gaining real traction. But it’s important to remember that crypto’s impact extends far beyond finance. From scientific research to physical infrastructure networks, these broader applications are still early and will require more time to mature. How successfully crypto evolves in this next phase—as financial rails and payment infrastructure—will meaningfully shape the trajectory of these other use cases.

As always, stay curious, and feel free to message me with any questions or feedback.

I know — you're probably sick and tired of seeing New Year predictions. Or, maybe you enjoy them. I don't know. People do like making (and reading!) predictions. It's kind of part of our nature.

I don't usually write prediction posts, but this year feels different.

AI is here. ChatGPT is used by, what feels like, virtually...everyone. Claude is too, and the exciting updates keep coming. We even have robots now—Waymo self-driving cars are already on the road.

If you’ve watched Stranger Things, you might remember from one of the earlier seasons where the residents of Hawkins, Indiana first discover the Demogorgon —a monster wreaking havoc and threatening to destroy the world. Once the resident heroes realize what’s truly happening, they know they can’t just tell people the full truth. No one would believe them. They’d sound absolutely insane! So instead, they create a palatable explanation that fits into people's existing mental models: there’s a chemical leak in the water.

I think about that analogy a lot when it comes to crypto predictions.

If I said outright that crypto and AI will aggressively eat jobs across every industry—from law to healthcare to e-commerce, manufacturing, and logistics—that software developers will be replaced and that Uber and truck drivers may disappear in a few years, that robots will become commonplace… I’d sound crazy! Even if it’s already happening.

So instead, I will make the shift to AI palatable.

What excites me about AI isn’t the moonshot, science-fiction version of the future (though that’s coming too). It’s the incremental change—the "slow at first, then everything all at once" way that AI will transform the products, apps, and tools I already use every day.

Since this is a crypto newsletter, this post will focus on crypto predictions—and, importantly, the growing interplay between crypto and AI.

But before going further, it’s worth addressing two questions upfront: first, what gives me any credibility to make predictions like these; and second, the obvious one—isn’t crypto mostly speculation?

On the first point, I recently wrote a post trying to explain, in simple terms, what I actually do working in governance and DAOs—a question I’m often asked by family and friends. I don’t take for granted that I get to work at the ground level of crypto innovation. That proximity is what informs these predictions. I’m not claiming to know exactly how things will unfold, but I do have a strong intuition shaped by working directly with teams building the next wave of finance and AI.

Before getting into where crypto is headed, it’s worth acknowledging where it’s been. Most people associate crypto with speculation—trading, gambling, prediction markets, and volatile assets that feel closer to casinos than infrastructure. And honestly, that perception isn’t wrong.

Speculation was crypto’s first mass-adopted use case.

When Bitcoin launched, its intended purpose was peer-to-peer electronic cash and censorship-resistant money. But the first thing people could actually do with Bitcoin at scale was trade it. Payments require merchants, norms, and trust. Speculation only requires buyers. Volatility attracted attention, capital, and builders, and markets formed long before UX, regulation, or social understanding caught up.

With Ethereum, the narrative expanded—toward smart contracts, programmable money, and the idea of a “world computer.” Yet the pattern largely repeated. The applications that achieved mass adoption were not productivity tools or everyday consumer apps, but speculative primitives: ICOs, DeFi yield farming, and NFTs primarily treated as financial assets.

This pattern isn’t unique to crypto.

Railroads, oil, telecom, and even the internet itself all began with speculative excess. Capital rushed in before demand stabilized. Many projects failed. But the infrastructure survived.

We wouldn’t have Google, Amazon, or Facebook without the experimentation and capital flows of the dot-com era. Speculation paid for the rails of the internet, as the graphic below shows.

Crypto’s speculative era has served the same function. And now crypto has reached its post-speculation moment.

Crypto wallets today are still too technical (I wrote a comparison of top Ethereum wallets in my post here). Users manually choose chains, select tokens, approve permissions, and sign transactions. Wallets expose protocol complexity, which for new crypto users, can feel intimidating overwhelming.

If you’ve used crypto before, the below screenshot of an Ethereum wallet looks familiar. If you haven’t, it probably looks intimidating.

With natural language interfaces built into crypto wallets, you will be able to simply write, "send $500 to Rika for dinner." The wallet will pick the cheapest rail (stablecoin, chain, and route), handle gas abstraction, settle instantly, and show you a beautiful receipt.

This shift to natural language interfaces has already emerged in the NEAR ecosystem with NEAR Intents. So this isn’t a prediction—it’s already here. The real prediction is that NEAR Intents will continue to integrate with more partners and evolve into a self-custodial, decentralized alternative to Web2 incumbents like Stripe and PayPal, which are layering stablecoins onto existing Web2 payment flows.

Rather than simply plugging crypto into legacy rails, NEAR Intents re-architects the rail itself—treating payments as outcome-driven intents, analogous to natural language interfaces for AI, and drawing on the liquidity, vibrancy, and composability of the entire crypto ecosystem as its backend.

A similar abstraction is emerging in the Optimism ecosystem with Actions, which simplify how users interact with onchain apps by bundling multi-step DeFi workflows—like lending, swapping, or payments—into single, human-readable operations. Actions abstract application complexity, making Ethereum-native finance feel more like using a modern app than navigating protocols and transactions.

As people increasingly mistrust large companies like Google and Meta with their data, private AI conversations will become a must. Using trusted execution environments (TEEs) and similar privacy-preserving infrastructure, we’ll begin to see private AI contexts where user data is processed and stored locally, rather than harvested for centralized model training.

Once again, this shift has already started and NEAR is at the forefront.

In a recent announcement post, the Brave browser outlined how it is using Confidential LLM Computing on NEAR AI TEE-enabled Nvidia GPU's, to enable browser-based AI that can process sensitive data without exposing it to the platform itself.

My broader prediction is that privacy-native AI will reshape industries built on confidentiality—healthcare, therapy, and law—where trust, discretion, and data sovereignty are foundational.

That said, this shift will come with an important caveat.

Sam Altman, CEO of OpenAI, has publicly warned about the confidentiality risks of using AI in sensitive contexts. These concerns are acute in the therapy or legal realm, where therapist-client privilege, and attorney–client privilege, is paramount. Centralized AI platforms, by design, can be subpoenaed or otherwise compelled to disclose user conversations—an inherent risk of custodial data architectures.

That said, just as crypto regulation has gradually matured, AI regulation will likely follow a similar path. Over time, clearer legal frameworks and technical safeguards will likely emerge to better align AI systems with the privacy expectations of the industries that they serve.

It’s easy to look at crypto’s history and dismiss it as a story of speculation. And for a long time, that criticism was fair. But speculation was a phase, not the destination. Crypto speculation funded experimentation, attracted builders, and laid the groundwork for what’s coming next—just as it did during the early days of the Internet, oil and gas, and railroads.

What feels different now is that technical abstractions are finally catching up. AI and natural language interfaces will make wallets usable for the average person. NEAR Intents and Optimism Actions are turning complex DeFi transactions into simple interactions that will be as easy to use as ChatGPT. And privacy-native AI is beginning to emerge, not as a promise, but as an architectural choice—one that reflects growing discomfort with centralized data custody.

Taken together, these shifts point toward a future where crypto fades into the background and becomes infrastructure: quietly powering payments, coordination, and AI-driven systems without asking users to understand blockchains or protocols. The real breakthrough won’t be when people adopt crypto, but when they stop noticing it altogether.

In this post, I’ve focused on the financial use cases of crypto—many of which are already gaining real traction. But it’s important to remember that crypto’s impact extends far beyond finance. From scientific research to physical infrastructure networks, these broader applications are still early and will require more time to mature. How successfully crypto evolves in this next phase—as financial rails and payment infrastructure—will meaningfully shape the trajectory of these other use cases.

As always, stay curious, and feel free to message me with any questions or feedback.