We've effectively doubled human lifespan in a century.

But even this dramatic extension of human life feels insufficient when we think about what we're still losing. Einstein and Feynman died at 76 and 69, respectively, and Steve Jobs and Marie Curie both died at 56. My grandfather lost his fight with cancer before getting to see any of his great-grandchildren. My father-in-law passed away months before his oldest daughter's wedding.

We lose great minds before their work is done. Another few decades of Einstein could have revolutionized our understanding of fundamental physics, and Steve Jobs might have continued shaping technology in ways we can't even imagine without him. And we lose the precious moments that can never be recovered. Grandparents that should have been at graduations, parents that should have walked their children down the aisle.

Beyond the loss of individual life, our lifespans distort the very incentives that drive human progress. The largest challenges we face as a species require planning and sacrifice across decades. But when the average person won't live to see 2100, long-term thinking becomes nearly impossible. Why make hard sacrifices for distant challenges? Why invest in revolutionary but slow-moving scientific research?

So if we can extend both lifespan and healthspan - the years we live without the burden of major health issues - it's obvious that we should! We should strive to extend far past an 100-year average lifespan, and keep pushing indefinitely. Imagine a world where 120 or even 150 vibrant and fulfilling years of life is the norm; where our final decades are filled with energy, curiosity, purpose, and meaning.

And yet, there are those who believe we shouldn't pursue this goal at all.

Understanding opponents to longevity

Some people simply fear the deterioration of their minds and bodies in the later stages of life.

Their fear comes from a well-intentioned place. Perhaps they've seen a loved one go slowly into the darkness, struggling every day to push past the pain and immobility. It's a haunting experience to watch someone who once lived with vitality fade into a shadow of themselves. I've felt this pain personally. Watching it happen to someone you love can plant a deep fear of the same fate, which could be enough to want an earlier (but more dignified) death.

There's another kind of fear at play here; not the fear of aging itself, but of the future we might be aging into. Some opponents to longevity might simply be scared of what humanity will look like by then. This kind of view is especially prevalent in the doomerist, seemingly-progressive archetype frequently seen on Twitter. They fear that by 2100, we'll be enslaved by our AI overlords after the post-nuclear apocalypse of World War VII, and they just don't see the point of trying to make it that far.

(This is also weaponized as an argument against having children at all, which is an argument to address some other day)

Of course, there's also the appeal to religion. 'We shouldn't meddle with questions of God and life' - as though pursuing longevity is somehow interfering with the divine plan. But if God created us with the intellect, curiosity, and capability to extend our lives, shouldn't we use these tools? Ernest Thomas Walton, the first person to artificially split an atom, made this point effectively:

"One way to learn the mind of the Creator is to study His creation. We must pay God the compliment of studying His work of art and this should apply to all realms of human thought. A refusal to use our intelligence honestly is an act of contempt for Him who gave us that intelligence."

We already accept advancements in medicine, healthcare, and surgery to alleviate suffering and extend lives by a certain amount of years, so why draw the arbitrary moral line at longer extensions of life?

The strongest (or loudest?) cohort of anti-longevity advocates comes from bioethicists and philosophers, some of which argue that extending human lifespan is 'undesirable and morally unacceptable' and a 'narcissistic wish incompatible with devotion to posterity.' From the ivory towers of academia, they warn of the impending societal collapse: healthcare inequalities, social stagnation, loss of purpose. And to be fair, they're not entirely wrong about the challenges we will face.

Look at the world today. Our current 80-year lifespan already strains the fabric of society. Pension systems, designed for shorter retirements, struggle to remain solvent as the populace lives longer. Older generations wield disproportionate influence on policies that will impact generations to come. The technological divide between old and young continues to grow. Medicare is an ever-increasing burden on the United States. Add on the looming climate crisis, another problem the youngsters inherited but did not create, and we've got full-blown intergenerational tension. This is already breeding a growing sense of fatalism among the youth.

The march of progress

But since when does humanity let difficult problems stop us from pursuing progress? These aren't arguments against the pursuit of longevity; these are just the challenges we will have to solve along the way.

For those fearful of aging into bad health, I truly empathize with the feeling that human life should end gracefully, before our humanity gets brutally taken away from us by old age. This fear is rooted in our raw, existential human vulnerability, and I feel these fears deeply myself. But letting these fears push us to not pursue longer, healthier lives would be a disservice to our core human impulse to push the boundaries, innovate, and redefine what's possible.

Even the doom and gloom about our current aging society is a bit overblown. Young voters are turning out in record numbers, shifting the political landscape away from the older generation's preferences. Climate technology continues to improve, with younger generations leading the charge. Even the supposed technological divide is shrinking with better and more intuitive technology - my 85-year-old grandmother sends me more TikToks than my teenage cousins, and my mother has become a big fan of her newly-found digital friend, who she calls 'CharlesGPT.' The challenges of an aging population are real, but not insurmountable.

I like Nick Bostrom's perspective from his 2005 review paper, Recent Developments in the Ethics, Science, and Politics of Life Extension. He suggests that one of the reasons we accept our current bounds of mortality as a fact of life might just be Stockholm syndrome with death itself, a psychological defense mechanism preventing us from pursuing the research that could free us.

In other words, our own resigned acceptance of what we consider a normal lifespan might be what's keeping us from looking up at all.

So of course we should strive to live as long as possible! We split atoms, caught a spaceship using chopsticks, and taught rocks how to think. Longevity is our next frontier, and we'll handle the practical challenges as they come.

Life in 2100

I don't know exactly what 2100 will hold for humanity, or how we'll tackle each practical challenge ahead. But I do know that life on Earth has gotten unimaginably better for the average human since 1900. The tide of technological innovation and free market forces has lifted billions out of poverty, saved hundreds of millions of lives from preventable deaths, and avoided millions of infant deaths.

I'd like to think that we will, as a society, get past all of the potential Great Filters we are charging towards - runaway AI, nuclear war, civil unrest, climate change - and we will parade into the 22nd century as a more enlightened society.

The challenges we will face in our pursuit of longevity are not threats that we should fear. These challenges are an opportunity for us to evolve. And evolution doesn't mean losing our humanity; it means expanding what humanity can be.

The credible neutrality of the Ethereum Foundation has been compromised by this action. Below, I’ll make the argument that a credible commitment from the Ethereum Foundation towards dissolving the Foundation in the next few years may be the only path forward.

Context

The Ethereum Foundation has a set of stated principles:

• ‘We attempt to subtract our power and resist the natural tendency of organizations to grow and accumulate power.’

• ‘Whenever possible, we remove ourselves from the equation, so that Ethereum flourishes with the support of a broad community of infinite gardeners, not just the EF.’

• ‘We do not try to control or force the natural processes of the ecosystem, but we do try to help the community preserve its values, and in doing so help Ethereum to maintain its soul.’

If your first thought when reading this blog post’s title was ‘dissolving the Ethereum Foundation is a ridiculous notion’, I have a few questions for you:

• Is the Ethereum Foundation today abiding by these stated principles?

• Is the Ethereum Foundation today genuinely credibly-neutral?

• Can we reduce the dependence and influence of the Ethereum Foundation, whether this year or next year or in the next decade?

• If not, why not?

If we want Ethereum to be the world’s computer, or the global settlement layer, or whatever your favorite phrase for Ethereum’s 100 year vision is, we need to begin to release ourselves of the power and influence that the EF maintains in the ecosystem, and we need to allow the ecosystem to drive Ethereum forward for the next century.

Intellectual honesty is a core value of mine.

Credible neutrality is a core value of Ethereum’s.

In this case, both of these values have been infringed upon.

Let me just present a few snippets from the disclosures of these 2 researchers (emphasis added is mine):

The advisorship comes with a significant EIGEN token incentive which could easily be worth more than the combined value of all my other assets (mostly ETH). We're talking millions of dollars of tokens vesting over 3 years. 2) I pledge to reinject all advisorship proceeds towards worthy projects within the Ethereum ecosystem

-Justin Drake


I do receive a significant amount of tokens from this position. I do not believe that they will change or influence my positions on how the core protocol should be developed, but I believe that the community should know about this, so that they can keep me accountable. I think Eigenlayer will be a major benefit to Ethereum, if it is done by someone with high integrity. I trust the current leaders are intending to do that, and I am planning to hold them accountable for it.

-Dankrad Feist

In both of these disclosures, the researchers describe a huge economic incentive that they are receiving. I respect that they have made this economic incentive explicit, although I wonder whether they would have made this disclosure if not for Cobie’s original tweet and ongoing backlash from the ‘social layer’.

However, in both of these disclosures, the researchers - who are clearly well-versed in game theory and economic incentives, given their body of work - claim that they have the discipline to avoid having their positions influenced.

Economic incentives are quite literally the single most important force-driving behavior in this industry and in all of human behavior.

How ridiculous is the notion that these 2 specific researchers are somehow immune from these incredibly powerful incentives?

I truly believe that Dankrad and Justin, in their heart of hearts, think that they are stronger than the economic incentives. I don’t know them personally, but by every account, they seem to be very nice people. I very much doubt that they are greedy or malicious individuals, and I don’t mean to imply that here at all. It is possible that maybe they are just the strongest, most-disciplined people in the world.

But what I can’t understand is how they could believe that the credible neutrality of Ethereum itself wouldn’t be compromised by these advisory roles.

I’m sympathetic to the idea that advisory shares could work IF the advisory was disclosed immediately (rather than after public backlash) and IF the intent was stated publicly and IF the proceeds were also distributed in some part to organizations making Ethereum more robust… however, that’s not how this all played out. Instead, it played out in a way that shows meaningful corruption of the ecosystem’s core values.

Credible Neutrality

Which brings me to the Ethereum Foundation, and the concept of credible neutrality.

Vitalik has previously referred to credible neutrality as a guiding principle (emphasis added is mine):

when building mechanisms that decide high-stakes outcomes, it’s very important for those mechanisms to be credibly neutral.

Essentially, a mechanism is credibly neutral if just by looking at the mechanism’s design, it is easy to see that the mechanism does not discriminate for or against any specific people…

That is, it is not just enough for a mechanism to not be designed to favor specific people or outcomes over others; it’s also crucially important for a mechanism to be able to convince a large and diverse group of people that the mechanism at least makes that basic effort to be fair.

Here is where these two EF researchers have failed. Despite their pleas to the contrary, it’s easy to see that these relationships with Eigenlayer have compromised their ability (and much more importantly, the Ethereum Foundation’s ability) to remain credibly neutral.

A few examples that demonstrate where credible neutrality has been compromised:

• March 2023 (just as Eigenlayer appears to have approached Justin about advisory, per his own timeline) - Justin implicitly proposes Eigenlayer specifically as a possible based rollups solution.

• July 2023 - The Bankless ‘Restaking Alignment’ podcast, where both Dankrad and Justin appear to ‘debate restaking’.

• December 2023 - Justin Drake’s talk at the Restaking Summit (sponsored by Eigenlayer! Posted on Youtube by Eigenlayer!) where he promises to ‘flesh out some of the incentive distortions that restaking brings to the table’.

• April 2024 - The Ethereum Sequencing and Preconfirmation Calls, where the EF (represented by Justin) fund various groups to do research on L2 preconfirmations… with re-staking as a soft requirement.

These are not just random, low-level Ethereum Foundation employees. For better or for worse, these are employees that speak for the EF in public discourse and meaningfully influence protocol decisions. Don’t take my word for it - check out what the team lead of Geth (the most widely-adopted Ethereum client) has to say about their influence.

And of course, the significance of Eigenlayer in this whole situation is important. Eigenlayer is not merely an application on top of Ethereum - it has the potential to meaningfully influence everything from protocol economics to the integrity of Proof of Stake consensus itself (as described by Justin in the ‘Restaking Alignment’ podcast above, which appears to have been before he received advisory shares from Eigenlayer).

A call to action

I love Ethereum. Ethereum is the only thing that keeps me in this industry. I write this post with the hope that I can play one small part in making Ethereum the foundational infrastructure for the next century of human progress.

The EF has done incredible things, from funding PSE to Devcon to the Summer of Protocols to a million other projects. Some of my favorite people in crypto work at the EF, and it would be impossible to say enough good things about the EF’s work over the last decade. I truly express my gratitude to the people who have spent the last 10 years working on Ethereum and making it what it is today, including Dankrad and Justin, who have had no small part in making Ethereum great.

But it’s time to follow the EF’s guiding philosophy of long term thinking, subtraction, and stewardship of values.

I want to be clear and tangible with my call-to-action here. In my eyes, a positive outcome would be:

• For the Ethereum Foundation to commit to a multi-year timeline to ossify the protocol and dissolve the Foundation, or

• If the EF continues to exist, for the EF to develop a Constitution that holds the organization to certain principles that it cannot break. Allowing its key decision makers to take massive advisory shares is equivalent to Supreme Court Justices having a massive equity stake in the companies on which they adjudicate.

I’m not sure what the EF will do about the treasury (burn it?), or how All Core Devs continues to operate (Protocol Guild?), or any of the answers to the 100 open questions about the exact mechanisms that will need to be followed to dissolve the EF. Hopefully this is the start of a 5 or 10-year timeline and ongoing discourse towards dissolving the Ethereum Foundation, rather than a request to immediately dissolve.

But It’s clear to me that the only way to ‘help Ethereum maintain its soul’ and ‘resist the natural tendency of organizations to grow and accumulate power’ is to disband the Ethereum Foundation and allow credible neutrality to flourish again.

Thank you to several people who have provided thoughts and feedback for this post. I will avoid calling you out by name explicitly for your own sake, but you know who you are and I greatly appreciate it.

All views are my own and do not reflect the opinion of anyone else.

Here is a simple decision-making framework that I used to commit myself to startup life, and some words of encouragement for those of you considering doing the same.

First, the general premise:

• Startups will require a ton of challenging work to be successful.

• Startups will have minimal infrastructure in place, at least in the early days (e.g., no HR department for recruiting, no Finance team for managing reimbursements)

• Startup employees take lower salaries in exchange for higher upside.

• Startup employees own a portion of the company, and the fundamental bet is that the startup will be worth much more in the future.

I’ll refer to the ‘other option’ here as Big Tech, although any other industry could be retrofitted into this framework (like biotech startups vs. Big Pharma, or consumer startups vs. the big consumer brands).

• In Big Tech, you’ll have higher salaries, more perks, and job security.

• In Big Tech, you’ll have less stress, pressure, and responsibility.

• In Big Tech, you won’t have to do much context-switching — you’ll be able to focus just on your work, since other parts of the organization will already be built out to support your work.

I don’t think the premise is necessarily true for all of the points above. In fact, I think several of these points are outdated or misrepresented. But let’s consider these the foundational arguments for each side of the table.

From here, we’ll outline a simple equation for measuring the trade-offs.

On one side of this equation, we have the costs and benefits of startup life.

On the other side, we have the costs and benefits of Big Tech life.

On the startup side of the equation, you’re joining for the equity that you’ll own in the business. What could that equity be worth in a positive scenario, and how likely is it to reach a point where you can actually turn that equity into cash?

Some questions you could reasonably ask yourself:

• What is the likelihood of success for this startup? (Very difficult to quantify!)

• What valuation would the startup have to reach for me to consider it successful?

• How much more money will this company need to raise in the future, and how does that impact my ownership?

• How much do I own of the company in this hypothetical?

• How much am I getting paid while we build the company?

With these answers in hand, we could imagine doing the math to get to an expected value of working at a startup. Multiply your ownership in a startup by the probability of the company’s success, then multiply that by the valuation of the company in a successful outcome, and poof! You get a reasonable expected value of your equity at a startup.

But there’s a metric fuckton of uncertainty here — the macroeconomic climate at any point in the future, the probabilities of success, and even the task of guessing what a company might be worth in the future. Being too specific with these numbers can make us feel deceivingly certain about something that should have no degree of certainty whatsoever.

The idea here is not to be overly precise, given this uncertainty, but instead to develop a mental model for evaluating the potential costs and benefits of joining a startup versus working in a traditional, large enterprise. We are refining a mental model by thinking through the various inputs into the above formula.

This has been strictly financial so far, but one of the main tipping points for my own calculus is that I believe the abstract value in working for a startup matters, and it matters a lot.

Being incentivized in the day-to-day work — actually feeling like your work is driving value in the business! — makes work much more fulfilling, and ideally, the startup you are joining has been targeted (by you) to align with your belief system, so that you can feel satisfied working towards the startup’s mission.

The opportunity to ‘wear different hats’ every day in a startup — to deal with uncertainty, tackle miscellaneous challenges, work your brain muscles day-in and day-out — is a useful practice for developing actual tangible skills. These skills are useful in almost any role outside of Startup Land, and the benefit of finding comfort in the uncertainty and actually getting good at these skills is highly underrated.

In fact, having less stress, pressure, and responsibility is a bad thing! It’s healthy to encounter stress, pressure, and responsibility on a semi-frequent basis. I personally want to expose myself to challenging situations, think through creative solutions, and strive to compete against others. Seeking out less responsibility is just not in my DNA.

A short digression here — I feel that a Matrix-like curtain has been forced over our eyes to make us think that work is supposed to be empty and dry. The Mondays through Fridays slowly passing us by, the boredom of a draining professional career sucking life out of us until we look up at 80 years old and wonder where the days have gone.

This does not have to be the way we live. You can choose the red pill and escape the rat race of middle management. You can rid yourself of Sunday scaries, replacing the anxiety of another long boring week with the supercharged motivation to go out and drive actual value to the company you work for and own a small piece of.

We can live fulfilling personal and professional lives; it doesn’t have to be either-or.

So these are the benefits of working at a startup. There are also costs.

The costs of working at a startup include: the inherent riskiness of startup life, the huge pay cuts that you need to take to join a startup, and also, what happens if the economy crashes?!

I firmly believe that each of these points is outdated or misinformed.

On layoffs — Big Tech (and large enterprises overall) have been ravaged by layoffs over the last few years. People who thought they had job security were suddenly called into meetings with faceless HR representatives to hear that ‘the company is going another direction,’ a wake-up call for those that assumed that working at a big company meant you could effectively hide in the crowd of 100,000 employees.

And many startup salaries no longer require a life of living in a garage and eating a Ramen diet. There’s more money in the startup ecosystem, and startups have come around to the idea that hiring and retaining employees will require more than just the allure of company equity. Even perks like health insurance, 401(k)’s, corporate credit cards, and disability insurance are easily accessible to most startups today, simply by using the crop of other startups that have been built over the past decade to enable this — companies like Deel and Mercury and Sequoia One.

With respect to the economy, I’ll simply quote from a Paul Graham post from 2008:

October 2008

The economic situation is apparently so grim that some experts fear we may be in for a stretch as bad as the mid seventies.

When Microsoft and Apple were founded.

As those examples suggest, a recession may not be such a bad time to start a startup. I'm not claiming it's a particularly good time either. The truth is more boring: the state of the economy doesn't matter much either way.

(A small but meaningful side note — Within just 12 months of this PG blog post, in the midst of the deepest recession since the 1920’s, Paul Graham and Y Combinator invested in Stripe, Airbnb, PagerDuty, and Heroku, which cumulatively account for somewhere around $200 billion dollars of equity value today.)

So to recap:

In this framework, you try to guesstimate what your equity might be worth in a successful outcome, discounted by some large percentage to account for probability of failure, and you add back in all of the abstract benefits — the feeling of having ‘skin in the game’, working on a mission you believe in, and the genuine development of useful, varied problem-solving skills.

Then you subtract out your own perception of startup costs; the presumed riskiness, the less frilly benefits, any macroeconomic concerns that you might hold.

My core argument is that the explicit benefits of working at a startup are clear. In the small chance that the company succeeds, you’ll probably get very rich, but it’s the implicit, often-under discussed benefits of working at a startup that are underrated in this calculation.

And the costs of working at a startup — the instability, the low salaries, the Ramen diets — are vastly overrated in today’s startup culture, given the amount of capital and brainpower that has been redirected towards startups over the last few decades.

Meanwhile, the benefits of Big Tech are also clear. High salaries, good perks, and good work-life balance are alluring. But how large is the cost of being one small cog in a 100,000 employee machine? How draining is it to work without caring about the company mission, and without being able to see any of your work drive tangible value for the business?

Ultimately, this framework relies on deciding which side of the equation is worth more to you. I’ll leave it to the reader to do the Big Tech side of the calculation for themselves. Of course, the specifics matter here, but readers can impart their own judgements and their own situations into the calculus.

For me, the math is clear. I’ll bet on myself.

I’ll bet on my ability to act as venture capitalist with my own salary, time, and effort, by picking the right companies to work on, and I’ll bet on my ability to influence meaningful change at the companies that I join to help us get a little bit closer to that desired successful outcome.

To be clear, this is a gamble — one big, concentrated bet into the companies I join — but it’s different from betting on a sporting event or a roulette spin. This is a gamble I can reasonably influence by contributing meaningful, high-quality work to the company. It’s a gamble, but with my time, money, effort, career, and life.

I’m okay with the stakes; the stakes empower me to be the best version of myself in my day-to-day.

If you’re considering a switch into startups, let me leave you with some words of advice and encouragement.

• Do the hard work of deeply introspecting and reflecting on what kind of work you want to do for the next decade of your life. Use this exercise as your guiding light when searching for startups.

• Spend time learning about the startup landscape in the industry of your choosing. You could join the biggest, ‘least-startup’ startup in that industry — OpenAI, for example — or you could join the 2-person team coming at the titans of industry. Even amongst startups there are huge variations in team size, type of work you’d be doing, and the upside you can expect to get, so think deeply about what your risk tolerance is and what kind of work you want to be doing.

• Follow startup funding announcements! Daily newsletters like StrictlyVC or Axios Pro Rata are good for this. As a general rule, companies that have just fundraised will be the most likely to be hiring in the immediate term, but don’t confuse these funding announcements for success. Venture funding predates success — the work is still ahead for venture backed companies.

• It's important to acknowledge that both the startup landscape and the BigTradCompany landscape have thousands of different companies, each with varying levels of risk, reward, and work-life balance. It’s okay to decide that you value Big Tech life more than startup life! Just make sure you’re making that decision after careful consideration, rather than just because of typical life inertia.

• Read all of Paul Graham’s startup blog posts, like:

  • Why to start a startup in a bad economy

  • What startups are really like

  • Startups in 13 sentences

If you’re considering joining a startup and want to talk through it, DM me on Twitter. I’d be happy to help you think through it. And if you’ve enjoyed reading this, I encourage you to subscribe to my Mirror profile to get an e-mail every ~6 months when I write a new post.

I’m grateful to be spending my professional time working with great people on a project that is building towards a better, Ethereum-enabled digital future.

But the never-ending assault of scammers, spammers, spewers and grifters in crypto is frankly just exhausting.  This piece is about reminding myself what it is that I love about crypto, by exploring some of the projects that inspire me today.

0xSplits

0xSplits is a project developing true hyperstructures – protocols that run for free, forever, without maintenance, interruption, or intermediaries.

If that sounds like crypto marketing babble, look at what they’ve built so far:

• Splits – a smart contract that splits all incoming ETH & ERC20 tokens among recipients, according to predefined ownership shares;

• Swapper – a smart contract that swaps all incoming tokens into a predefined output token, so the recipient can control which tokens to receive, regardless of what tokens are sent (e.g., someone can send PEPE but the sender will just receive it as ETH);

• Waterfall – a smart contract that pays out a specific amount of either ETH or ERC20 tokens, according to a predefined order of recipients based on certain tranches.

These are all already deployed to Ethereum – 0xSplits calls them ‘public goods’. They’re immutable, fee-less, onchain, and composable. They’re programmable, censorship-resistant money legos, uncontrollable by an early incumbent or an overenthusiastic regulator. 0xSplits is building onchain financial instruments to power a non-custodial financial future.

In a vacuum, each 0xSplits product looks like a cool little tool with some primitive functionality. But with just a tiny bit of imagination, the 0xSplits suite of public goods starts to look like some foundational building blocks of traditional finance (but onchain, composable, censorship-resistant, etc.).

Waterfall? Sounds a lot like distributions for liquidity events in venture capital, or      liquidation preferences in a bankruptcy.

Splits? Could replace some of the (absurd) administrative functions that happen in      TradFi today, like when a back-office employee manually types in the different      recipients of some funds distribution into an Excel sheet labelled      FundsFlow_v94_FINAL.csv (yes, this still happens today, in the year of our lord,      2023).

Swapper? Those pesky foreign exchange fees that your credit card charges for      international transactions could be resolved with near-zero overhead on their part.      (Unfortunately, this might eat into the $4B+ in “Card Fees” that Wells Fargo earned      last year, so it’s unlikely to get adopted by TradFi any time soon).

When these little money legos get stacked on top of each other, useful onchain financial tools emerge. Combine a Splits with a Swapper and out comes Diversifier, automatic tax withholding for crypto income. Put a Waterfall on top of a couple of Splits and get Recoup, an onchain venture fund. At some point, a completely non-custodial ‘banking, reimagined’ consumer product will appear out of 0xSplits, and everyone will wonder why we didn’t see it coming.

And 0xSplits is doing it without shoving a governance token down your throat and calling it product-market-fit.

They also happen to be powering some of the other projects in crypto that inspire me…

Protocol Guild

... like Protocol Guild!

Protocol Guild is a collective of Ethereum contributors, made up of individuals from the various client teams that get lumped together under the “All Core Devs” moniker. Protocol Guild uses a 0xSplits contract to distribute incoming public goods funding that supports their ongoing development of the various clients that make up Ethereum’s decentralized consensus and execution layers.

What I admire about this group is the thoughtful, tactical consideration of how to fight off Moloch.

“Moloch refers to a situation where individual rational actors, competing for resources or status, end up in a collectively suboptimal outcome due to their self-interested behavior.” (link)

Basically, Moloch is the danger of ineffective incentive design, slowly creeping in to destroy whatever system you *thought* was built to be everlasting. The Ethereum core devs are arguably the most thoughtful collective in the world as it relates to mechanism design and designing Moloch-resistant systems.

Protocol Guild is an experiment to align the incentives of these core developers pushing forward the base Ethereum protocol with the incentives of thousands of distributed developers across the world that build applications on top of Ethereum. The question of “How can we give core protocol contributors exposure to the broader success of projects built on top of Ethereum without letting Moloch into the house?” is an incredibly difficult one, and to be frank, the jury is still out on whether Protocol Guild is the right approach. But with a dose of cautious optimism, Protocol Guild seems to be working, and it’s powered by a 0xSplits contract.

Something about the combination of crypto and game theory really inspires me. Ideas like the ‘infinite garden’ and the ‘Dark Forest’, derived by taking the (figurative) limit of a situation and analyzing what the incentives look like at the limit, is true long-term thinking.

And the longest-term thinkers are the teams that make up Protocol Guild.

Nouns

The Nouns project is awesome. They’re dealing with their own set of problems right now (is that Moloch rearing his ugly head again?), but Nouns as an experimental project, iterating onchain at the forefront of art, community, and distribution, is a glimmer of hope in an unfortunate sea of broken projects.

For Nouns, everything happens onchain. The auction mechanism happens every 24 hours, forever (or for as long as the Ethereum blockchain continues to run, which hopefully is a very very very very long time), and the art for each new Noun is generated randomly based on Ethereum block hashes. Nouns are even stored onchain, a rarity amongst thousands of IPFS pointers for other NFT pfp projects.

Nouns also does everything in public, including open funding rounds supporting ecosystem-wide projects. They fund some stupid stuff (Nouns Condoms? A giant pizza?), but they do so while fully embracing the silly absurdity of this whole dang life thing that we’re all doing together.

Oh yeah - Nouns has also used 0xSplits to experiment with new models of creative commons art and has supported Protocol Guild in a big way. Good vibes.

SongCamp and Camp Chaos

Matthew Chaim is the artist leading Songcamp. I don’t personally know Matthew, but his music is criminally underrated, and the Songcamp model Matthew is experimenting with is captivating. For more on Songcamp, check out this podcast Matthew did.

TL;DR on Songcamp’s most interesting project, Camp Chaos – an 8-week experiment where 77 creatives (musicians, producers, visual artists, etc.) came together in what Matthew describes as ‘a songwriting camp smushed together with a web3 hackathon’.

The output of Camp Chaos was 45 brand new songs, along with generative cover artwork for the accompanying NFT ‘packs’ and a bunch of content to supplement the Camp lore. The basic idea is to re-think how music gets created, and to re-imagine how the value generated by music can be distributed across a wide set of participating individuals.

(As you can imagine, Camp Chaos uses 0xSplits to help power the value transfer flowing through the whole thing)

The Songcamp team talks about “economics as a canvas”, which I think speaks for itself as a captivating approach to trying new things.

One year later, the headless beast that is Camp Chaos performed live in concert at NFT NYC, and followed that show up with live shows in Toronto and Detroit. Within 10 minutes of the NFT ‘packs’ initial launch, $400,000 worth had been sold.

Ultimately, only about half of the total packs up for sale were sold, and difficulties releasing the music to traditional music distributors showcases how far we have left to go before we see the fall of the Imperial Music Regime. But the ingenuity of the Camp Chaos approach is itself worth applauding and admiring.

I guess what I’m trying to say is that I’m still here in crypto because I admire experimentation and long-term thinking.

By default, people just do things the way they have always been done, either because there has never been a different way to do them, or because that’s just the way those that came before them had been taught.

But crypto opened the door for an entirely new space for experimentation, an opportunity to rebuild the antiquated legacy systems. Everything from finance to art, from gaming to music – in some corner of the cryptosphere, someone is experimenting with a new approach to a legacy system, powered by the credibly-neutral, censorship-resistant Ethereum that inspired us to try.

With so many opportunities to do a quick scammy cash grab in crypto, those among us that live out the ideals of Ethereum in the best way possible should be celebrated. I admire those that continue to drive us forward to re-imagine what finance or art or governance can look like with the help of global coordination technology.

It’s the people at 0xSplits and Songcamp and Nouns, the better angels of our nature, that keep me hopeful about crypto.

Thank you to Sina Habibian, David Banks, Lisa Cuesta-Bunin, Abram Dawson, and Will Minshew for your feedback on this post.

I thought Kipping was smart and thoughtful, but the conversation just didn’t hit. Nothing stood out as particularly interesting, at least for the first few hours.

But about 3 hours in, Kipping drops an awe-inspiring, optimistic, and just plain cool perspective on the Fermi Paradox. He talks about the growth of artificial intelligence and the incredible novelty of this moment — like, right now — in time. His theory is hopeful, thought-provoking, and tucked deep into a 4 hour long podcast, so I’m summarizing his ideas here.

Kipping is a member of the Department of Astronomy at Columbia University, studying ‘exsolar planetary systems’. He also runs an educational YouTube channel called Cool Worlds.

Fermi Paradox

Some of the build-up to the interesting bits of the Lex Fridman conversation revolves around the Fermi Paradox. The Fermi Paradox (not technically a paradox, but I won’t argue semantics) is summarized as:

… where is everybody?

We know that the universe is 14 billion years old, and we know that there are something like 300 million planets in our galaxy alone. And our galaxy is just one of several trillion (trillion!) galaxies in the observable universe.

We also aren’t sure that the observable universe is the whole picture — why would the entirety of the universe just be the portion that we can see from our non-special point on the interstellar map? — but even if this is everything… it’s a lot.

The Drake Equation formalizes this probabilistic argument about alien civilizations, but the Fermi Paradox basically just asks the question — where is everybody? 

I mean, it’s hard to imagine that these stupid freakin’ ape creatures tucked away in a corner of the Andromeda Galaxy are the only things out there. How could we be?

But still, we see and hear nothing. No hints of life anywhere, no signals from the outer reaches of the galaxy, nothing to suggest that there’s anyone (or anything) out there. Except us. 

And while little green men visiting Earth in UFOs is still a fringe-y topic, some of the popular theories exploring the Fermi Paradox — where the hell is everybody!! — are compelling, or at the very least, thought-provoking.

Great Filter

One theory is that there’s a Great Filter that civilizations inevitably face at some point during the civilization’s expansion.

The filter could be ‘in front’ of us in time, like “every civilization that advances technologically beyond a certain point blows itself up with nuclear weapons” or “every civilization consumes too many resources for their preferred natural environment and that environment then changes beyond repair.“

This is not an impossible theory to believe… but it’s pretty depressing, and life is too short for depressing theories.

Or the Great Alien Coffee Filter (trademark pending) could be ‘behind us’, in the sense that every other civilization out in the stars has been caught by the filter, but somehow, we slipped past.

Maybe the filter behind us is the transition from single-celled bacteria to multi-cellular organisms. In that case, the universe could be scattered with hundreds of billions of planets filled with measly bacteria and slime, but only one lonely planet was lucky enough to mutate past single-cellularity into Darwinian complexity.

Or maybe the filter is ‘consciousness’, broadly defined — self-reflection, mental-awareness. An entire species battling internally over the true nature of the universe, with an innate ambition to try and figure out the answers. Inevitably, this ambition leads to exploration and expansion. Somehow, we’d be the only ones to have reached this stage. 

Maybe there’s gaseous monkeys or silicon giraffes on a planet far away, but without the intelligence or irrational conquistador spirit that humans possess, they’re all just slowly roaming their planet, munching on alien grass, instead of cruising through the stars. Aliens, but not the kind we’d be really excited about.

At least in this case, we made it past the Great Filter! Good for us.

This is obviously all just semi-coherent speculation. Maybe civilizations like ours are incredibly rare but, given the size of the universe, they’re still completely ubiquitous, and we just haven’t seen them yet. They could be smart and exploratory but just haven’t made it to our corner of the galaxy yet, or maybe these types of civilizations only happen once every hundred billion years and we’re just the first ones to the party, right now.

Kipping’s Theory

But about 3 hours into the Lex Fridman podcast, Kipping shares a different theory about the Fermi Paradox:

“You go back for the last 4.5 billion years, the planet was dumb, essentially. If you go back the last few thousand years, there was a civilization but it wasn’t really producing any techno-signatures. Then over the last maybe 100 years, there’s been something that might be detectable from afar.

But, we’re approaching this cusp where we might imagine… I mean, we’re thinking of years or decades with AI development typically when we’re talking about this. But as an astronomer, I have to think on much larger time scales, centuries, millennia, millions of years.

So if this wave [of AI development] continues over that timescale, which is still the blink of the eye on a cosmic time scale, that implies that everything will be AI out there, if this is a common behavior.

That’s intriguing because it implies that we are special in terms of our moment of time as a civilization.  It’s normally something we’re adverse to as astronomers. We normally like this ‘Mediocrity Principle’ — we’re not special, we’re a typical part of the universe, the Cosmological Principle — but in a temporal sense, we may be in a unique location. And, perhaps, that’s part of the solution to the Fermi Paradox in fact.

If it is true that planets go through basically these three phases; 1) dumb life for the vast majority, 2) a brief period of biological intelligence, and 3) an extended period of artificial intelligence that they transition to; 

Then we would be at a unique and special moment in galactic history that would be of particular interest for any anthropologist out there in the galaxy. That has, for me, recently been throwing the Fermi Paradox a bit on its head. And this idea of the Zoo Hypothesis, that we might be monitored, which for a long time has been seen as a fringe idea even amongst the SETI (Search for Extraterrestrial Intelligence) community, but if we live in this truly transitional period, it adds a lot of impetus to that idea.”

At this point, Lex Fridman — who I greatly respect as a podcaster, scientist, and as a person who puts great energy out into the world on a daily basis — makes the cardinal sin of podcasting, and interrupts a guest deep into the sharing of a profound insight.

But the idea Kipping describes deserves further analysis. (To be fair, David is not necessarily endorsing this idea, just speculating on its implications).

A special slice of time

Kipping is suggesting that, in this specific solution to the Fermi Paradox, we, as biological, non-artificial intelligent beings, are at the most special moment possible.

Not the most special moment in human history, but at the most special moment in the history of our galaxy.

See, for the first 4 billion years on Earth, not much happened. Just a metric shit-ton of Earth slime and boring, single-celled organisms. 

A few hundred million years ago, the first multi-cellular organisms started making things a tiny bit more interesting.

Then, over the last few hundred thousand years, the apes that would eventually become humans started pounding rocks, making spears, and inventing the wheel.

Now, just a few hundred thousand years later, those same apes have developed to a point far down the exponential curve of technological advancement. Reusable rockets can land on small carriers in the middle of the ocean. CRISPR. Autonomous ride-sharing. Censorship-resistant decentralized blockchains. And a new class of sometimes-dumb but clearly-awesome large language models like ChatGPT.

And even if you subscribe to the belief that the ChatGPT-era of large language models isn’t close to reaching the holy grail of AGI (artificial general intelligence) – then just round up. Round up from “right now” to “in 5,000 years”.

5,000 years is the same as 5 years on the cosmic time scales — insignificantly small – and it feels safe to suggest that even 10,000 years out, we’ll have ironed out all the kinks. 

And then AI takes over.

Even if humans somehow manage to corral AI without blowing ourselves up, we probably aren’t going to enhance human longevity to the point where we can send humans outside of our solar system. Why would we build multi-generation spaceships, when we can just scatter a bunch of AI all over the place, and wait for them to report back?

So Kipping’s idea explicitly suggests just that – that we’re on the cusp of spreading artificial intelligence far and wide. 

We are in a unique, fleeting moment of biological intelligence in the Universe, right after billions of years of slime but right before artificial intelligence is omnipotent. We are right there. We live at the thin slice in history between the Boring Slime Age and the ChatGPT-X age. Forever. We will always have that. That uniqueness, that novelty, that tiny insignificant fact that makes us special.

And maybe that’s the answer to the Fermi Paradox. That we are truly a novelty in the universe, existing at the most special moment conceivably possible, and because of this, there is nobody else to talk to. 

We are the only ones. We are the only ones in the history of ever (!!) that will be able to experience the world before the unbounded expansion of artificial intelligence, but after all the boring times. How lucky are we?

By Josh Stark & Bruno Lulinski

In the Year in Ethereum 2021, we published a chart comparing the total transaction volume of the Ethereum and Bitcoin blockchains. Last year, Ethereum transferred approximately $11.6 trillion (ETH and ERC-20s), and Bitcoin transferred approximately $4.6 trillion (BTC and USDT).

After publishing, we saw a graph from Galaxy Digital claiming that in 2021 Bitcoin had settled $12.41 trillion USD:

Ark Invest also posted a chart with similar figures, showing Bitcoin settled $13.1 trillion:

What’s going on here? Figuring this out was a fun mystery to work through, and along the way we learned a lot about the nuances of how different sources define and report on-chain metrics.

TL;DR

• Different blockchain data providers sometimes use very similar terminology to describe completely different metrics

• Our lower figure from Coin Metrics excludes all UTXO change-related transactions and some internal transactions (e.g. within exchanges), which we believe is the best figure to use to compare to Ethereum

• The larger figures from Galaxy and Ark exclude only obvious or “naive” UTXO change transactions, and thus still include a significant amount of change & internal transactions

The first thing we did of course was to review and triple-check our work to ensure that we had not made an error or misrepresented any data.

Our graph was created using the following methodology, which is the same approach used for a similar graph in 2020:

• For Ethereum, we are including transaction volume from ETH and all ERC-20 assets which had a volume of greater than $500M.

  • This means we are under-counting Ethereum’s effective volume, since we’re missing the long-tail of ERC-20 activity, as well as other non ERC-20 assets like NFTs.

• For Bitcoin, we are including volume from BTC and also USDT on Omni.

• For all assets, we are using the “Adjusted Transfer Value” metric from Coin Metrics. Coin Metrics defines this as “The USD value of the sum of native units transferred that interval removing noise and certain artifacts”.

  • The reason we chose this metric is because we want to show and compare “real” economic value transfer on each network, removing as much non-meaningful activity as possible. This is especially important since elsewhere in the post we compare these figures to Visa’s total settlement for the year.

The calculation and data sources for this are documented in a google sheet here, which was linked in the original YiE 2021 post.

After reviewing, we were very sure we had not made any errors.

So, we had a mystery. Why are Coin Metrics and Galaxy/ARK’s data diverging so significantly on what should be comparable figures?

We reached out to Galaxy Digital, Coin Metrics, and ARK Invest to see if they could help shed light on what was going on here. We benefited from the help of Kyle Waters from Coin Metrics, Jacob Panek at AllianceDAO (formerly of Coin Metrics), Nishita Jain from ARK Invest, and Rafael Schultze-Kraft from Glassnode. Unfortunately Galaxy Digital never got back to us.

The first thing we wanted to understand was the Coin Metrics data we were relying on.

Coin Metrics has two relevant metrics here:

• “Transferred Value” (~$13T in 2021 for Bitcoin)

• “Adjusted Transfer Value” (~$4T) which we used in our chart

Both of these metrics remove “obvious change”. If you’re only familiar with how Ethereum and other EVM chains work, you might be unfamiliar with change outputs and the Bitcoin UTXO model.

Ethereum uses an “account” model, which is easy to understand intuitively: addresses are like accounts, and they own sums of assets like ETH and ERC-20s. In Bitcoin, addresses own discrete “Unspent Transaction Outputs” (UTXOs). So if you have 5 BTC, what you actually have might be a UTXO with 2 BTC, and a UTXO with 3 BTC, both controlled by your wallet.

Anytime you transfer Bitcoin, you are “using up” one of those UTXOs. So imagine you want to send only 0.5 BTC to someone. Your wallet will “spend” the whole 2 BTC UTXO, sending 0.5 to your recipient (creating a new UTXO of 0.5 BTC), and sending 1.5 BTC back to you in a new UTXO containing 1.5 BTC. Here’s a more in-depth explanation.

So, when measuring total transaction volume on Bitcoin, data sites typically filter out “change outputs” like the 1.5 BTC transfer in the example above, because no money is actually changing hands. It’s just something required by the UTXO model. Only the 0.5 represents “real” economic activity.

Some change transactions are very easy to identify. For instance, when a change output gets sent back to the same address that sent the transaction, this is “obvious change”. However sometimes people use different addresses to receive their change (this is generally a good security practice), meaning not all change will be captured by this heuristic.

So both figures provided by Coin Metrics remove obvious change. The Adjusted Transfer Value (ATV) metric that we used for our graph goes further, by using two additional heuristics to remove non-meaningful transactions:

• ATV removes transactions that are assumed to be change due to their use of round numbers. For example, if a UTXO is split into 2.0000 BTC and 0.195482 BTC, we might assume that the latter is change.

• ATV also removes “early spend” transactions. These are transactions that are sent, and then re-sent shortly afterwards, maybe multiple times. This is a common heuristic that is used to identify transactions that are internal (e.g. moving money around within an exchange), or related to the operation of an application like a mixer.

• ATV also makes several adjustments which apply to ETH and ERC-20s, like removing pass-through accounts, which arise from events like exchange deposits or flash loans.

Around the same time, we heard back from Nishita at ARK Invest. She shared that the $13T figure from the graph came from Glassnode, specifically their “change-adjusted volume” metric. This metric is defined by Glassnode as “The total amount of coins transferred on-chain, adjusted by change volume. Only successful transfers are counted”.

We then reached out to Glassnode to learn more about this metric. Rafael told us that Glassnode uses three different metrics for volume:

• Naive volume: ~$48 trillion for BTC in 2021

• Change-adjusted volume: ~$13 trillion for BTC in 2021

• Entity-adjusted: ~$3.3 trillion for BTC in 2021

At this point, the picture is starting to come together clearly:

• Coin Metrics and Glassnode each report a volume figure that adjusts for obvious change transactions, showing approximately $13 trillion 2021. However they label them differently: Coin Metrics calls this “Transfer Volume” and Glassnode labels this “Change-adjusted Volume”.

• Coin Metrics and Glassnode each report a volume figure that makes further adjustments, though they diverge on what adjustments they are making leading to different figures. Coin Metrics calls this “Adjusted Transfer Volume” and it removes even-amount change and early-spend transactions, which results in a figure of $4T. Glassnode uses proprietary methods to remove various transactions within clusters of accounts which are believed to be controlled by single entities, which results in a figure of $3.3T.

• These different metrics explain the discrepancy between our graph and ARK/Galaxy Digital’s graph. Our graph is showing the second figure, which adjusts all change and a lot of “internal” transactions ($4.6T). ARK/Galaxy are showing a mostly-unadjusted figure, which would still capture significant amounts of change and internal transactions ($13T).

• Both are true, they are just measuring different things.

Phew! Mystery solved.

In conclusion, here’s what we take away from this:

• The terms used across different blockchain data providers are not always consistent. In this case, “adjusted” and “unadjusted” were used to mean different things between Coin Metrics and Glassnode. If you’re using data from multiple sources, be very careful to learn the details of what your metrics are measuring.

• For the purposes of our chart comparing Ethereum and Bitcoin volume, we should continue to use metrics that remove as much change as possible from the Bitcoin data. Because Ethereum does not use a UTXO model, only by removing all change outputs are we making a fair comparison. Frankly, data that includes change outputs is not a very useful indicator of any kind of real economic activity or user adoption.

• That means we should use either Coin Metric’s adjusted transfer volume, or Glassnode’s entity adjusted volume. Unfortunately neither provider offers a metric that only removes as much change as possible, but does not make other adjustments (e.g. for intra-entity transactions). One challenge with this according to Coin Metrics is that there is a lot of overlap between these approaches - for instance, users withdrawing from an exchange, and the exchange receiving change back to their own address.

• Are volume metrics which do not exclude internal transactions useful? This really depends on your goal. Internal transactions obviously do not represent “real” economic activity, since they are just one person or one entity moving money between wallets they control. Sharing these figures without explaining that they include internal transactions can be very misleading, because readers might assume that these figures represent the “common sense” meaning of a transaction, which is between different persons or entities.

  • However, these transfers are still taking place on-chain, with fees being paid for them - they indicate something about the capacity of a network to settle value, and are useful for understanding fee market dynamics.

Further reading:

• Following our conversations, Coin Metrics published a report digging into some of the details of how they do this: https://coinmetrics.io/on-chain-volume/

• NYDIG also published a useful article  about the complexities of calculating transaction volume on Bitcoin’s blockchain and pointing out the differences between Glassnode and Coin Metrics transaction volume, as described above:

Decentralization is a concept that historically describes local governance structures where the responsibilities of planning and decision-making are not made by a centralized authority, but rather distributed throughout its membership.

Although the terms ‘centralization’ and ‘decentralization’ were not coined until the 19th century in relation to significant political upheaval across Europe, the concepts have existed since the very inception of society. In spite of the obvious benefits of decentralization regarding inclusivity, representation and personal freedom, human history has primarily been a study in centralized authority because of the benefits it provides in efficiency in making decisions and its ability to be effective over large geographic areas.  

However, recent technological advancements have allowed for decentralized principles to be utilized more effectively and many of the historical limitations are no longer applicable as robust mechanisms of governance utilizing decentralization are now available.  

In particular, blockchains have emerged as an opportunity for the development of new systems that more effectively embrace the benefits of decentralization as both a mechanism for member representative governance models and as a choice for users to access and develop application functionality within a decentralized economy.

While the historical definition of the term is still useful as a comparative measure to centralization, the term ‘decentralization’ itself has become synonymous with certain features of blockchain technology and a point of analysis in determining their technical, legal, economic and political function.  Although there is still no unified singular definition of decentralization, the utilization of the term within blockchain generally carries certain characteristics that trace back the original Bitcoin whitepaper. While the term decentralization is not explicitly found within the whitepaper, the ability to construct organizations and processes with “no central authority” absent a “trusted third party” for transaction or otherwise interacting with others has established a stand alone concept utilized within the industry.  Developments in the application of decentralized technology, regulatory actions, legal analysis, economic potential and political theory have provided additional context for what decentralization means as it pertains to public blockchains and the applications built on top of these blockchains.  

The goal of this paper is to help clarify why people in the broader crypto community organize around the concept of decentralization.  Although a unified comprehensive definition would undoubtedly provide more clarity than the current contextual definition, the reality is that decentralization within the blockchain is an evolving concept and at this time, its utilization must be examined situationally to determine how the underlying processes fit within its current application.  

In this summary paper, we will explain the different components of decentralization, the benefits of decentralized systems, examples of how different projects have approached the process of decentralizing, and good-faith critiques of decentralization. This paper will act as a TL;DR summarizing the concept of decentralization within its current usage, while providing linked resources throughout for those interested in digging deeper into specific areas.

This piece is not an attempt to reach an all-encompassing definition of the term ‘decentralization’ or an objective measure of project decentralization. Vitalik Buterin, co-founder of Ethereum, wrote a piece entitled “The Meaning of Decentralization'' that highlights the difficulty of precisely defining the term. 

Attempts at measuring decentralization include: Miles Jennings’ paper about the principles and models of decentralization, Balaji Srinivasan’s post about the Nakamoto Coefficient; a Beijing Jiaotong University paper using various metrics to gauge decentralization; and Ketsal’s post describing open standards for measuring blockchain decentralization.

“Blockchains are politically decentralized (no one controls them) and architecturally decentralized (no infrastructural central point of failure) but they are logically centralized (there is one commonly agreed state and the system behaves like a single computer).”

- The Meaning of Decentralization, Vitalik Buterin

“Having decentralization as an end goal often means aiming for a vague, and possibly moving, target.”

- Data Points to Measure Blockchain Network Centralization, Jenny Lueng / Josh Garcia

Decentralization Standards for Layer-1 Blockchains

The core value proposition of many blockchains, including Ethereum, is to act as a trustless infrastructure where developers can build immutable, decentralized applications. While other blockchains are working towards progressive decentralization, Ethereum’s first-mover advantage and wide adoption as the first smart contract platform — i.e, blockchains that natively enable smart contracts, allowing for a variety of composable applications to be built on top of the blockchain — makes it a natural benchmark for Layer 1 blockchain decentralization. 

Coinbase engineer Yuga Cohler went so far as to say that Ethereum’s upcoming transition to a Proof of Stake consensus mechanism will, if successful, “prove the viability of decentralization as a social organizing principle.”

Applications built on top of a Layer 1 blockchain inherit some of the decentralized attributes of the base layer, but just being built on top of a decentralized layer does not mean that applications are necessarily decentralized themselves. While the application inherits the immutability and censorship-resistance of the underlying base layer by default, each application makes design trade-offs that impact how decentralized the individual application is. In other words, the decentralized infrastructure layer provides a base where decentralized and centralized applications can work in conjunction, with each application and corresponding community making decisions as to what trade-offs to make to achieve their desired state of decentralization. 

Ethereum’s level of decentralization is not without critique. Liquid staking derivative centralization and majority client risks have frequently been discussed as potential centralization challenges for the Ethereum blockchain, and both of these critiques revolve around unintended centralized points of failure that could potentially arise in the future of the network. 

The specifics of these two concerns are outside the scope of this piece, but have been discussed at length elsewhere. For more information on liquid staking centralization, refer to this post on the risks of liquid staking derivatives by Ethereum researcher Danny Ryan and research from decentralized staking provider Lido. For more information on majority client risks, refer to this post by Ethereum researcher Dankrad Fiest and the Ethereum.org section on client diversity.

The Ethereum blockchain can be considered a “sufficiently decentralized” infrastructure to serve as the foundation for a discussion of decentralization. The Bitcoin blockchain would certainly qualify as “sufficiently decentralized” as well, but by design, Bitcoin has less functionality embedded into its protocol compared to Ethereum’s more flexible smart contract platform. 

The Bitcoin community largely prescribes to an ethos of “simpler is better”, where Bitcoin itself is an expression of decentralization, since simplicity creates less vulnerability than more complex protocols. This post won’t get into the details of that argument, besides recognizing that Bitcoin would qualify as “decentralized enough” and that Bitcoin has been building out the Lightning Network to support more decentralized applications built on top of the network. 

Ethereum possesses a more robust application ecosystem from which to discuss the varying levels of application decentralization, but Bitcoin’s achievement as the first decentralized blockchain paved the way for the entire industry. 

For more basic context on Ethereum specifically and blockchains overall, Bruno Lulinski, co-author of this paper, wrote A Simpler Guide to Ethereum that goes over an introduction to blockchains, DeFi, NFTs, the Ethereum community’s decision-making process, and the future of Ethereum scaling solutions. 

The Different Components of Decentralization

Decentralization is essential to the value proposition of several parts of the broader crypto ecosystem, so it makes sense to view the meaning of the term relative to the area in which it applies. The elements of decentralization are both discrete (i.e, “is the project decentralized in this specific area?”) and related (i.e, “how does decentralization in one component impact a project’s attained decentralization in another area?”). 

Since decentralization in the context of one component means something different from decentralization in the context of a different component (while at the same time sharing underlying activity that impacts the other categories), projects need to consider each component to be able to function as intended.

The components of decentralization are broken into three broad categories that relate the effectiveness of decentralized systems across three axes; technical, economic, and legal decentralization. 

As Miles Jennings stated in his in-depth piece discussing principles and models of decentralization, “The effectiveness of these decentralized web3 systems will depend upon their security, economies and parity of information” – each of which corresponds to one of the three listed components. 

• Technical decentralization – A global permissionless infrastructure layer and the applications built on top of it require credibly-decentralized technical underpinning. The underlying blockchain provides the execution layer for the on-chain components of the individual applications, but the applications themselves still require their own technical decentralization in the form of permissionless clients for interacting with the underlying smart contracts, user-owned data (and ease of data portability), and decentralized governance of the smart contracts by a broad group of participants in the form of a Decentralized Autonomous Organization (DAO). 

  Questions to ask when considering technical decentralization: How are these systems designed? How are upgrades made, if needed? What processes backstop the execution of upgrades (i.e, Compound’s 48 hour timelock)? What blockchain underpins the application, and what tradeoffs does that blockchain force onto the application? Can users easily ‘ragequit’ the system,  i.e, can users exit the system and use (or build) different methods of interacting with the core protocol?

  From the perspective of determining the decentralization of the blockchains themselves — how many clients are there, and what’s the distribution amongst clients used for miners/validators? How can individual participants verify the authenticity of the given blockchain, and how difficult is it for an individual to participate in that verification process? There are many more ways to consider the technical decentralization of blockchains.

  Ultimately, technical decentralization is the necessary foundation upon which economic and legal decentralization can occur.

• Economic decentralization – Public blockchains create the opportunity for a reimagining of the economic interaction between the developers of an application and the users and adjacent stakeholders around that application. In the ‘traditional’ pre-blockchain world, companies are incentivized to view their users as a source of value extraction, primarily in the form of user-generated content or the corresponding data of the end user, which is then transacted between the company and willing advertisers behind the scenes. 

  Blockchains allow for systems that are not reliant on central leadership, allowing for the balancing of incentives between developers of the application, contributors to the application, and users of the application. These economically-decentralized structures are basically a new generation of open-source software communities, but with embeddable, transparent economies. In an economically-decentralized ecosystem, contributors can participate in the value-creation of the application while receiving compensation for their contributions.

  Questions to ask when considering economic decentralization: How is the underlying token of the application designed and distributed? How was the airdrop designed, and what considerations were made by the early project developers to prevent centralized ownership of a majority of project tokens? How are early investors and project contributors compensated, and what do token lockups for all parties look like? How do distributions of the DAO treasury work, i.e, how are funds distributed to initiatives and/or working groups intended to further the project’s mission? 

• Legal decentralization – Beyond the technical mechanics and the economic benefits of decentralization are matters of regulation and legality, including taxation, liability, ownership, intellectual property, reporting and privacy.  Although U.S. securities law is an essential area of analysis in determining how decentralized systems may make use of digital assets, it is not the only area of law impacted by the decentralization made available through public blockchains. 

  Although decentralization exists in the current legal system - most obviously in the form of general partnerships - there is significant question as to how the default rules established for participation and responsibility can be fairly applied to decentralized systems that are exceedingly dissimilar from the activity giving rise to existing law. Going beyond the superficial similarity to existing rules and laws, the decentralized activities available through the blockchain represent significant changes in concepts like equity, ownership and control. These differences underscore a different relationship and responsibility than the activity giving rise to current laws and regulations and create significant uncertainty in how decentralized organizations that exist on the blockchain will be treated.  As these activities are capable of creating taxable events and acting in a way giving rise to litigation, it is expected that taxation and liability will soon be matters of equal prominence with securities law when considering legal decentralization.  

  Early projects necessitate some form of central leadership and planning to define the project’s purpose and provide crucial activation energy. These teams might retain some influence in the soon-to-be-decentralized project, but the level of influence retained could have a significant impact on whether the project is considered decentralized from the perspective of regulators and other government authorities. 

  Securities regulation stems largely from a desire to prevent information asymmetry amongst market participants.  While there is no defined standard for the concept of legal decentralization, the levels of influence that early project contributors retain in the decentralization process, as well as the transparency of information amongst participants, will be pivotal to determining whether a project is legally-decentralized.  

  Questions to ask when considering legal decentralization – how much influence does the early project team have, and where does that influence come from? Does their influence stem from outsized voting power retained in the supposedly-decentralized organization, or from their voice in communal decision-making processes? How much influence do early investors have? Can community members be held accountable by other community members, and does the project depend on the efforts of a central authority? Do different stakeholders have asymmetric information based on the structural design of the organization?

Many have written high-quality overviews on the topic of decentralization from the perspective of securities regulation:

• Scott Kupor has written about the key regulatory questions in crypto and has described considerations for determining whether a token is a security;

• David Kerr and Miles Jennings authored a legal framework for decentralized organizations;

• Stephen Wink and Shaun Musuka described the pursuit of sufficient decentralization as a clear path to avoiding securities regulation;

The benefits of decentralized systems

As discussed above, the term ‘decentralization’ is itself a reflection of the term ‘centralization’. Looking at the attributes that a decentralized system might have, like censorship-resistance and distributed decision-making, makes it easier to visualize the concept. 

Censorship-resistance

Censorship-resistance is the idea that no single governing authority can unilaterally make the decision to restrict another participant’s actions in a network. Historically, coordination between humans has relied on some levels of trust. 

Trading goods between two people requires the trust that both parties will actually deliver their goods to the other, and agreeing to some sort of truce or treaty between conflicting nations requires trust that the other party will continue to abide by the agreed-upon treaty. 

Immutable code deployed on decentralized public blockchains sets the foundation for censorship-resistant, privacy-preserving innovation. These censorship-resistant systems are not yet completely un-coercible, but they act as a necessary foil to the institutions and platforms we’ve come to rely on outside of crypto (world governments, social media platforms, etc.). If the infrastructure layers (the blockchains themselves) weren’t decentralized, it would be simple for a powerful government to shut it down — just find the party responsible for the network and coerce them.

Decentralization makes this difficult, as China’s Bitcoin ban demonstrated, because censoring sufficiently decentralized systems requires coordination outside of the scope of most governments; just a few months after the China Bitcoin mining ban, several underground mining operations emerged in China to fill the gap left behind by the ban. 

NFTs have been used by individuals to preserve information in the face of authoritarian governments as well – however, these NFTs still required anonymity from the individuals to avoid direct coercion from their government. Even democratic governments like Canada have recently expressed a willingness to exert powers of censorship by coercing financial institutions to financially censor some citizens. 

Other countries, like Ukraine, have effectively used the censorship-resistant quality of public blockchains to fund their defense when cross-border money transfer companies initially capped transfers of money to Ukraine (these caps for transfers to Ukraine were later relaxed).

Tech giants like Apple, Facebook, and Google have scaled to huge amounts of power and influence, throwing them (willingly or not) into public debate about the interactions that happen on their platforms (and the processes that guide their frequently-controversial decisions). Twitter is frequently used by governments to communicate directly with their constituents, and offers a great example of the benefits of decentralization –  in 2018, Twitter removed access to a variety of APIs that independent developers had used to build applications on top of Twitter. 

A decentralized system would be censorship-resistant to decisions like Twitter’s. In fact, transparent, unopinionated rules to participation are by themselves a flavor of censorship-resistance that blockchain-based applications naturally inherit, since by default, code deployed to public blockchains is open-source.

Even if Twitter’s former CEO, Jack Dorsey, had committed to an open protocol and long-term neutrality (as he later lamented), the promise of a censorship-resistant Twitter will always fall flat on long enough time horizons — it’s the natural game-theoretic conclusion. Open-sourcing code and permitting user ownership of private data are concepts that are fundamentally opposed to the business models of corporations built on closed protocols which rely on the data of their end users to generate financial returns for their shareholders.

Resilience to attacks and Decorrelation

Vitalik Buterin argues that decentralized systems are more resilient to attack and less likely to accidentally fail than their centralized counterparts. 

Critically, decentralized systems are generally more expensive to attack due to the absence of sensitive central points of failure for attackers to target — an attacker couldn’t just infiltrate the Ethereum Foundation and press a big red “HALT” button (since there is no big red button), and an attacker couldn’t overpower Buterin and force him to shut down the blockchain (since Buterin doesn’t have that type of centralized power, despite being the initial founder and specwriter). 

At the application level, trust assumptions, key management and security practices will differ, which means different levels of resilience to attacks. The Layer 1 blockchain’s resilience to attack will still provide a credibly-neutral, permissionless infrastructure for application developers to build from.

Decentralized networks also tend to breed duplicative systems, leading to more robust security. Tim Beiko, one of the lead coordinators for the Ethereum developer community, recently called this benefit of duplicative systems “uncorrelated failure modes” on Farcaster. The general idea is that multiple solutions, —  i.e, different client implementations, different approaches to a specific problem, or just different schools of thought — reduce the probability of catastrophic failure across the stack.

(Beiko technically uses “decorrelation” and “uncorrelated failure modes” as a replacement for the term “decentralization” in this context, because of the difficulty of quantifying decentralization. We are using “uncorrelated failure modes” as a benchmark for a sufficiently-decentralized system. Therefore, from our perspective, a decentralized system would necessarily have uncorrelated failure modes, but either way, the sentiment is the same.) 

An example of catastrophic failure at the hands of correlated risks is the 2008 Global Financial Crisis, where the risks created by the rise of collateralized debt obligations, credit default swaps, and frothy lending practices were improperly underwritten by ratings agencies. This highly-tangled web of risks led to correlated failures as homeowners defaulted, leading to lender defaults, leading to counterparty defaults, leading to havoc. 

Underwriting systemic correlated risks is difficult and, in complex interconnected systems, can lead to disaster. Decorrelation of systemic risks via the open borders of blockchains can help mitigate these risks and reduce the surface area of attack vectors. 

“If you had asked a normal person in 2007: “How would it affect your life if it turns out that investors have mispriced the super-senior risk in synthetic collateralized debt obligations built out of subprime mortgage tranches,” that person would have said “I have no idea what you are talking about, but I can’t imagine how that collection of words would affect me.” But it did.”

- Money Stuff, Matt Levine (May 12, 2022)

Transparent incentives and distributed decision-making

While a shareholder in a public company might successfully petition the board of directors to include a shareholder proposal in an annual proxy statement, boards have some leniency in which proposals they have to include for discussion, and many large tech companies (Facebook, Snap, and Google, for example) have dual-class share structures that give insiders a supermajority of voting power, denying any significant outcome from stakeholders. 

While not solely a tool for distributed-decision making, decentralized systems do enable governance transparency that has the potential to improve the equity and effectiveness of critical decision-making processes. There are good-faith critiques of distributed decision-making systems, including the necessarily-centralized focus required by early project teams, the tragedy of the commons, and the voter apathy that can manifest in these types of horizontally-distributed decision-making processes. 

Governance of these distributed decision-making systems is a complex topic in and of itself (which will be discussed in a future DAO Research Collective piece). However, proponents of decentralized systems argue that transparently-recorded actions are one of the main benefits of decentralized organizations. 

Critiques of decentralization

Despite occasionally being misconstrued as such, a decentralized economy built on public blockchains is not a replacement for all centralized entities. Instead, it is an expansion of structures that will allow decentralized and centralized organizations to interact in ways that previously were not technologically feasible or practical. Still, there are several good-faith critiques of decentralization in the context of public blockchains, which are addressed below. 

Only perfectly-horizontal structures can be decentralized

To some, the idea of decentralization means perfectly unhierarchial structures, completely unstructured and without guidance or leadership. Some critics of decentralization argue that any influence exerted in a decentralized system by a small number of participants proves that the system is centralized, or that any attempt at structure preserves centralization. 

This claim has been used to say that Ethereum isn’t decentralized. But as described throughout this piece, decentralization comes in various forms and must be viewed through specific frames of reference to distinguish between different types of decentralized systems. 

Kevin Owocki of Gitcoin discusses this in a Twitter thread where he points out that decentralization can refer to "decentralized governance via a permissionless token" rather than a "chaotic loose web of individuals".

In Anticapture, Spengrah writes that “conflating decentralization with permissionlessness is one of the most common mistakes in the DAO space.” Spengrah discusses the concept of anti-capture, a framework for how networks of humans can design systems resistant to governance capture by bad actors. Capture-resistance governance is a more reasonable goal for decision-making for projects that can’t be reduced to completely non-human programmatic functions. 

Not enough recourse for consumers

One concern about decentralization is that decentralized entities won’t provide recourse for consumers. The critique is that many (or most?) consumers will not care about self-custody of their assets, and many will be happy to claim ‘decentralization’ as a virtue of web3… until their Bored Ape gets stolen. If users lose their assets because of bad-faith actors or fat-finger mistakes, how will users get their assets back? How can that process work in a decentralized world?

In March 1933, as the U.S. recovered from the Great Depression of the late 1920s, President Franklin Roosevelt gave a speech regarding the banking crisis and the advent of the Federal Deposit Insurance Corporation, which insures depositors in banks for up to $250,000 in assets. His first sentence is demonstrative of the situation at the time:

“I want to talk for a few minutes with the people of the United States about banking -- with the comparatively few who understand the mechanics of banking but more particularly with the overwhelming majority who use banks for the making of deposits and the drawing of checks.”

At the time (and still to this day), many didn’t understand the inner workings of the banking system. In the near future, many still won’t understand or care about the mechanics of the underlying blockchains, but solutions will exist to fill the need of the consumer (in this case, wanting to own a Bored Ape or participate in a DAO) without the consumer needing to understand the specific mechanics of the system. Through the process of iteration, society learns and improves. The same will happen to crypto. 

Insurance will become more robust, and either the users or the protocols themselves (or both) will have programmatic insurance coverage for these types of damages. The user experience on wallets will improve (see Argent or Rainbow for a great wallet user experience), making it less onerous to self-custody, while still retaining the benefits of self-custody. 

The fear of losing a 24-word secret recovery phrase will become irrelevant in a world of social recovery wallets, and solutions will continue to spring up to fill the needs of users who want to enjoy the benefits of decentralized systems while still ensuring reasonable forms of recourse for potential assistance in difficult situations. Most importantly, centralized organizations will coordinate with decentralized organizations to provide these solutions in a way that preserves the benefits of decentralized systems while creating a user experience that fits the desires of their individual user base.

Centralized entities prove centralization

The centralized entities that exist in the crypto world — like Celsius, a centralized exchange — are often used as a demonstration of how the crypto world is not truly decentralizing. This claim appropriately targets the projects that claim decentralization as a selling point to attract users to what is a clearly centralized (by any definition) project, including many of the recent catastrophes in crypto (Luna and Celsius, for example). These should be critiqued as such. 

But as described in detail throughout this piece, decentralized systems are not just completely horizontally-distributed systems and instead, there are several individual components to consider when judging the level of decentralization of a project. Crucially, the critique that “centralized entities within the system prove centralization of the system” often ignores the idea of data portability. Mudit Gupta, Chief Information Security Officer of Polygon, called data portability "the ability to be decentralized."

Centralized systems can exist and create value for end users by making it easier to interact with permissionless blockchains, but ultimately, blockchains give users the ability to exit with their own data. If OpenSea, a centralized NFT marketplace, decides to censor a subset of the NFTs that are sold on their platform (by not displaying them on the OpenSea user interface), or if OpenSea decides to start charging higher fees to users, users can simply stop using OpenSea and move to another NFT marketplace. 

OpenSea doesn’t actually hold user NFTs — OpenSea is just a venue for displaying and transacting (importantly, a venue with lots of liquidity, which makes for a more efficient marketplace and better price discovery, but a venue nonetheless). 

(As a side note, OpenSea recently launched Seaport, a decentralized protocol to underpin their marketplace.) 

Traditional internet companies don’t give users the flexibility of data portability because they’re not incentivized to do so, but blockchain-based applications necessarily have data portability embedded into their operations. While centralized crypto companies can create efficiencies (like organizing liquidity, providing customer support, and standardizing user interfaces), the user’s ability to exit the system provides a check on any centralized entities' power over the system and ultimately, over its users.

Ineffective governance and potential plutocracy

The critique that decentralization will beget ineffective governance might be the most truthful critique of the ecosystem right now. As of early 2022, governance of decentralized organizations is largely ineffective across the board — participation is low, and pure coin-voting, as most decentralized organizations have trended towards, has a variety of embedded issues that might create more plutocratic systems than the prior status quo.

The DAO Research Collective’s Governance paper will touch on many of these issues, and Fred Ehrsam of Coinbase / Paradigm wrote a prescient 2017 piece on blockchain-based governance systems that highlights some of the benefits and issues of on-chain governance, as well as future approaches. Ultimately, it remains to be seen whether decentralized governance can be as effective (or more effective) than traditional centralized governance systems.

"Only by making technical systems that offer a variety of mechanisms for checking concentrations of power and by simultaneously building social ideologies constantly on the lookout for failure modes of these mechanisms can we hope to succeed where previous attempts at decentralizing authority have failed."

- Liberation through Radical Decentralization, Glen Weyl / Vitalik Buterin

Acknowledgements

Thank you to Connor Spelliscy, Jacob Robinson, and Mike Wawszczak for providing feedback on this paper, and thank you to all of the researchers whose work we relied on while drafting this paper. Finally, thank you to the DAO Research Collective for their support. 

Some of my smartest friends have started spending more time learning about Ethereum, and through that process, several of them have asked me similar questions, usually about specific definitions (like “what’s gas?”) or broad conceptual pieces (like “how does Uniswap work?”). These questions inspired me to put together A Simpler Guide to Ethereum.

How to Use this Guide

This guide is broken up into five main sections:

1. An entry-level “Ethereum 101” section,

2. a deeper look at some more complicated concepts in “Ethereum 201”,

3. a section about identity in the context of crypto,

4. a decentralized finance section, and finally,

5. a section on the future of Ethereum, specifically in terms of the transition to Proof-of-Stake (don’t worry if this doesn’t mean anything to you yet!).

In each section, I define various complicated terms and compile useful diagrams to explain some of Ethereum’s most important conceptual topics in plain English. I’ve also included additional resources for continued learning at the end of the guide.

You can use the different sections of this guide as a quick reference check when learning about Ethereum, or as a point of inspiration for further exploration, or as a link to send your friends that are newly interested in crypto. For example, you could CTRL+F “Uniswap” to learn more about decentralized exchanges, or you could search for “wallets” to learn a bit more about non-custodial wallet security.

In one of his famous blog posts, Vitalik Buterin (one of the co-founders of Ethereum) wrote: “sometimes incredibly un-nuanced gross oversimplifications are something we need to understand the world.” I hope that, by boiling down these complex topics to their atomic parts, this guide can be helpful to anyone learning about the world of Ethereum.

1) Ethereum 101 - the basics

Before we can understand Ethereum, we need to understand the basics. In this section, I’ll explain what a blockchain is, how blocks get added to the blockchain, how Ethereum works as a world computer, and how smart contracts work.

Blockchain - A blockchain is a public record of all of the transactions that a certain network of independent computers processes and maintains. Rather than manage this transaction database centrally (in the way that Amazon or Facebook hold their data), there is no single owner of the data, making it decentralized. The computers in the network follow a specified set of rules and mechanisms to help them maintain the record of all of these transactions.

These rules help the computers agree (or “reach consensus”) on all of the different actions that have happened on the network: Did Computer A send money to Computer B, and did Computer B send those funds to Computer C, and when was that? What happened last week? What happened six months ago?

Computers in the network are independent, so Computers D and E (and F and G…..) might not know Computers A or B or C. The blockchain’s set of rules means that the individual computers can reach an agreement on what has happened in the history of the blockchain without needing to independently verify the accuracy of the data being provided by the other computers. In other words, the computers can agree without needing to trust each other! This trustless consensus between the computers in the network is pivotally important.

There are a ton of different blockchains, and each follows its own set of rules to reach consensus. The Ethereum blockchain specifically serves as the infrastructure and design space for all kinds of cool, new applications in sectors like gaming, art, finance, and social media.

Consensus Mechanisms - When all of the individual computers in the blockchain agree with each other about what has happened in the network, this is referred to as “consensus.” The individual computers follow the blockchain’s set of rules to reach consensus, and the computers go through the whole process of reaching consensus every time transactions are added to the chain. Once the computers reach consensus, a ‘block’ of transactions gets added to the ‘chain’ and becomes part of the history of the network. The rough idea is that if the computers can agree every time something gets added to the blockchain, then they can agree on the entire history of the blockchain, since they’ve had to agree every step of the way.

Consensus is one of the concepts that underpins the entire world of blockchains. Being able to validate what has happened in the network without needing to trust the individual participants in the network is an incredibly difficult human problem to solve, and blockchains are the best way to solve this problem. There are many different sets of rules (or “consensus mechanisms”) that help the individual computers in a blockchain reach consensus, but I’ll focus on the two big ones:

Proof-of-Work (PoW) -  In Proof-of-Work, computers compete to solve really complex math problems. The network provides economic rewards to the first computer to solve the problem, which provides an incentive for the human behind the computer to keep the computers up and running (in other words, to ensure the network keeps processing transactions).

The process of competing to solve computationally-intensive math problems is called “mining”, as you may have heard before, and essentially, the process verifies that incoming transactions are legitimate and can be safely added to the blockchain. This is the set of rules that the Bitcoin blockchain and the current version of the Ethereum blockchain use.

PoW has its issues, mainly 1) the strongest (and most expensive) computers will end up solving the problems faster, so the rich will get richer and 2) solving hard math problems  on computers requires a lot of energy consumption, which has been one of the biggest critiques to blockchains overall.

Proof-of-Stake (PoS) - Rather than use heavy computation to reach consensus (like PoW), Proof-of-Stake uses the risk of punishment (and some economic incentives too) to incentivize participants.

In Proof-of-Stake, participants put up money (technically, they “stake” their money), and in exchange, the participants are entered into a process of random selection. The computer that gets randomly selected does the job of validating the next batch of incoming transactions. When that randomly-selected computer does the processing correctly (i.e, within the constraints of the Proof-of-Stake rules), the computer earns a reward.

If the participant that gets randomly selected by the network does something against the Proof-of-Stake rules, the money that that computer staked gets reduced (or “slashed”).

By randomly choosing computers to validate the transactions, PoS blockchains don’t ask all of the computers in the network to work on those difficult math problems at the same time. Skipping that heavy computation mitigates the two major problems of PoW. This is in part why Ethereum plans to use this set of rules to reach consensus when Ethereum’s next-generation blockchain is deployed, slated for later in 2022.

Nodes - For the Ethereum blockchain to work, participants in the network need to run a certain piece of software to help them interact with the Ethereum blockchain. I like to think of each node as an independent computer running “Ethereum software.” All else equal, having more nodes (participants in the network) is good for the concept of decentralization, but sometimes, maintaining nodes can be a bit of a hassle, so there are a few types of nodes with different purposes:

Full Nodes - Full nodes store full blockchain data and help verify the blocks that are getting added to the blockchain. Full nodes also provide proofs that show that past transactions are valid.

Light Nodes - Light nodes are a type of node with less functionalities than a full node, by design. Instead of storing full blockchain data, light nodes just store the much smaller ‘proofs’ of past transactions. These light nodes help more people participate in the network, since they store less stuff and are cheaper to run.

Archive Nodes - Archive nodes are the librarians / Wikipedia’s of the Ethereum world. They store everything that the full nodes keep, and more. Analytics tools and wallet providers might use an archive node to pull information from way back when.

Clients - This is the “Ethereum software” that helps computers (nodes) interact with Ethereum. Individual nodes can pick which type of client software they want to use, but having a few different types of clients is important for decentralization, in case one of these clients has some sort of bug or issue. There are two types of clients; execution clients and consensus clients, but that’s beyond the scope of this guide.

Today, there are a handful of Ethereum clients available, and the Ethereum community has recently been campaigning the largest node-running institutions to diversify the clients they run on their nodes. It’s important to note that anyone who wants to participate in Ethereum can build their own client, which means that users don’t have to trust a third-party entity to verify the blockchain for them.

State - The Ethereum blockchain’s state describes what the different account balances on the blockchain look like at any given point in time. Once something new happens to the blockchain (like a new block of transactions getting processed), then the state gets updated to accurately reflect what the blockchain looks like after those new transactions are included.

Ethereum’s state holds information about the different accounts and their account balances. In other words, once the blockchain validates new transactions, the state is updated to reflect the new account balances, using the information from the new transactions that were just added.

Sidebar - How do blocks get added to the blockchain?

One user might want to send some money to another person using the Ethereum blockchain. Once the transaction is initiated from the side of the first user, the transaction needs to be added to the chain of transactions before the receiving user has the funds.

When a transaction like this is being added to the Ethereum blockchain, the entire process of reaching consensus amongst the nodes needs to occur before that transaction can be added to the blockchain and become a part of the history of that blockchain.

In the diagram below, the transaction in question is the simple one described above - just one user sending funds to another user. This transaction gets bundled into a block and waits for the nodes to work together to reach consensus and add blocks to the blockchain.

From: Understanding Ethereum

Blockchains are really just a way for everyone to agree on what transactions have occurred in the history of the network, while the state is the updated account balances that have been getting updated every time new transactions happen.

From: Understanding the Ethereum Yellow Paper

Smart Contracts - Smart contracts are somewhat similar to digital versions of the traditional contracts that we are used to dealing with in the physical world. In a traditional contract (such as an employment contract or a lease for an apartment), two or more people make up a set of rules, then use lawyers and the legal system to enforce the rules in the contract.

In smart contracts, two or more people still set the rules, but instead of using the legal system for enforcement, the smart contract is written as programming code and posted to the blockchain (or “deployed” on the blockchain). Instead of having lawyers enforce the contract’s rules, the contract runs automatically based on what has been encoded into the code.

The sidebar above describes blocks getting added to the blockchain. Smart contracts are code that is deployed onto the blockchain via a transaction that gets included in a block. Smart contracts can then be 'called', or interacted with, by future transactions. A simple example would be if Person A and Person B wanted to bet on the price of Bitcoin in two years. Person A believes Bitcoin will be over $100k on 1/1/2032, while Person B believes Bitcoin will be below $100k on that date. Person A and Person B could set up a smart contract, place their funds into the smart contract, and set up a simple rule - if Bitcoin is above $100k on 1/1/2032, the smart contract releases funds to Person A, and if not, the smart contract releases funds to Person B. Simple, straightforward, and trustless.

Smart contracts allow anyone to trustlessly deploy code to a global computer, and they allow anyone to trustlessly verify what the code says (as long as they can read the code!). As a result, the existence of smart contract technology has opened up a massive opportunity for an emergent wave of decentralized applications that wouldn’t be possible without blockchains.

The biggest difference between Bitcoin and Ethereum is that Ethereum kicked off a wave of smart contract computing platforms, which are blockchains that enable smart contract code to be written and deployed directly on that blockchain. Josh Stark at the Ethereum Foundation wrote a piece about smart contracts that I recommend if you’d like to dig deeper into this concept.

Ether (ETH) - Ether is the native currency that powers the Ethereum blockchain. In Proof-of-Work, the rewards that go to the computers that solve the hard math problems are paid in ETH, and the capital that participants stake in Proof-of-Stake is denominated in ETH (technically, 32 ETH).

Ether is the name of the cryptocurrency, Ethereum is the name of the network.

Ethereum Virtual Machine (EVM) - the Ethereum Virtual Machine is the name for the ‘imaginary’ computer that’s made up of all the individual small computers that participate in the Ethereum network. This single big computer isn’t an actual ‘physical’ computer in the sense of being in one single location, but it works exactly how a really big (like, planet-wide) computer would work.

The state of the Ethereum blockchain lives on this computer, and the EVM also holds the rules for updating the state when the next block gets added to the blockchain. If someone on the Ethereum network wants to include smart contract code in one of their transactions, that code gets run on the EVM.

Sidebar - How does the EVM work?

While it’s probably unnecessary for a beginner to understand the intricacies about how the EVM works, the EVM is an important component of the Ethereum blockchain and gives you a sense for how decentralization operates at scale. The below diagram, while a little complex, paints a great picture. Let’s go step-by-step at what you’re looking at:

1. Before anything happens, we start with the state of the Ethereum blockchain at a given point in time. This is the box all the way to the left called “World state σ t.”

2. A transaction, like a transfer of ETH from one wallet to another, gets added to the Ethereum blockchain. This is the “Transaction of message call” box at the top of the diagram.

3. The state of Ethereum before the transaction (again, box on the left) plus the input data from the new transaction (box on the top), go to the EVM. Here, the EVM updates the new state.

4. Once the EVM updates the state, the new state (“World state σ t+1”) is stored.

From: Ethereum EVM Illustrated

Tokens - Tokens generally refer to some asset on a blockchain. Tokens can represent many different types of assets; for example, a token could be an asset that is supposed to act like a currency, or a token could be an asset that gives the holder the right to vote in a specific decision-making process (a ‘governance’ token), or a token could be something else entirely. Tokens are atomic units of value for different kinds of assets within the world of crypto.

Fungible Tokens - The term ‘fungible’ refers to some set of mutually interchangeable goods or objects.. This is not a crypto-native term; currency is typically referred to as fungible. For example, the $1 dollar bill in my pocket can be exchanged for the $1 dollar bill inside of your pocket, and both of those could be used to buy $1 of something. They’re worth the same. When applied to crypto concepts, fungibility refers to whether or not a crypto asset is interchangeable with another in its’ set. My ETH is fungible with your ETH.

Non-Fungible Tokens (NFTs) - Non-Fungible Tokens refer to any digital assets that are unique and are therefore not interchangeable.

While popularized through digital art and collectibles, NFTs can be any unique digital asset. It just so happens that digital art and collectibles are one of the first use cases for NFTs that have resonated with the broader public. NFTs have helped get a ton of people interested in crypto, but I think the rise of NFT projects like Bored Apes and NBATopShot have led the broader public to underestimate the other types of utility that are enabled by having unique digital assets on a trusted settlement layer like the Ethereum blockchain.

Conceptually, NFTs can also be used for a variety of other use cases outside of just digital collectibles. If a product or service needs to be able to verify the ownership and provable scarcity of a certain digital asset, NFTs on a public blockchain can help. For example, concert venues might use NFTs to represent tickets for a concert, or video game designers could turn hard-to-get in-game assets into NFTs so that users can transfer and trade them amongst themselves.

One twist to this concept - some assets can be both fungible and non-fungible, depending on the set that they’re being compared to. For example, if I have an antique $1 US Dollar bill from the 1800s that I keep in a glass case as a collectible. It’s clearly a different dollar bill (non-fungible!) than the dollar bill I have crumpled up at the bottom of a pocket in my pants.

Still, if I took that dollar bill out of the glass case and tried to spend it at Starbucks, they’d (probably?) accept it, because in some ways, it’s fungible with the other dollar bills, even though in other ways, it’s clearly different.

From: Graphical Guide to Understanding Uniswap

Ethereum 201 - a little deeper down the rabbit hole

In this section, I’ll explain why gas costs are so high, how composability works, and how users interact with applications built on Ethereum.

Gas - Every interaction with the Ethereum blockchain has a cost to it (gas), and that cost depends on how much computation it takes for the EVM to run that specific piece of code. Because each block in the blockchain only has room for a fixed number of transactions, the concept of ‘gas’ helps Ethereum allocate the scarce resource of ‘blockspace.’

More complex transactions may require more gas to complete. For example, sending ETH from one wallet to another might just require a few lines of code in the EVM, so it will require less gas than a more computationally-intensive interaction, like swapping several coins on a Decentralized Exchange (more on this below in the Decentralized Finance section!).

You might think of gas as similar to a fee that a centralized credit card company takes to operate its services. Visa, for example, takes a flat 3% of all transactions happening via the Visa network, which they’ve built, operated, and maintained since the 1950s. By contrast, Ethereum’s “fee” (gas) is variable, based on the supply and demand for the network at the time of the transaction.  Gas fees are paid out to computers that participate in the Ethereum blockchain (more on this below).

Gas is denominated in ETH, and users can decide to pay more in gas (by ‘tipping’ the computers processing transactions) to speed up their transaction time, increasing the chances of their transaction getting included in the next block.

Gwei - Gas prices are technically denoted in wei, which is just a very small increment of ETH. 1 wei is equal to 0.000000000000000001 ETH (1 quintillion weis, so 5 commas = 1 ETH). 1 gwei is equal to 1,000,000,000 wei, so gwei to ETH just makes the increments easier when comparing gas prices.

Users have gotten used to quoting gas prices in gwei. Something like 0.0001 ETH would be 1 gwei, which is a very low gas fee. Users can use Gas.Watch to keep an eye on current gas prices. Gas fluctuates based on the demand that exists for getting included into the blockchain

I think it’s pronounced gwey, but I’ve heard people say goo-ee. At this point, I’m too afraid to ask.

Sidebar - Why do we need gas, and how does it work?

The computers that validate transactions for the blockchain need to be economically incentivized. If they weren’t economically incentivized, it would be very difficult to convince people to run and maintain these computers and keep the blockchain running, and if there aren’t enough computers running, blockchains become too centralized in the hands of just a couple of controlling users.

As mentioned above, participants are paid in gas based on the demand that exists for getting included into the blockchain.

From: Understanding Ethereum

Solidity - Solidity is the name of the programming language that people can use to write smart contracts and build decentralized applications on the Ethereum blockchain. Crucially, Solidity is a Turing-complete programming language, which basically means that “anything you could conceivably write into code can be written using Solidity.” This means that developers can use Solidity to do a ton of different types of cool stuff on Ethereum.

Composability - Because smart contracts are deployed as open-source code on the Ethereum blockchain, anyone can build on top of these smart contracts (or ‘fork’ the code and change it up yourself), which means that applications on Ethereum (and other similar blockchains) are composable.

You can think of composability like an API on the blockchain. While developers have arguably been able to build software on top of other pieces of technical infrastructure in earlier generations, the main difference with crypto composability is that all of the underlying protocols are decentralized. In other words, developers don’t have to worry about a centralized entity owning all of the underlying data, suddenly changing its rules, or restricting access to developers, such as what happened to developers building on Twitter APIs in 2018.

Sidebar - What are some examples of composability? How does composability actually work in practice?

The concept of composability is the idea that developers can build an application using other applications that have already been built and deployed onto a public blockchain.

For example, Compound is a DeFi application that lets users earn interest on deposits, like a high-powered savings account. If a developer at a project like Argent (a crypto wallet) wants to embed Compound into the application they’re building, the developer can integrate Compound easily without having to reinvent the wheel. That’s composability.

From: Understanding Ethereum

Ethereum Improvement Proposal (EIP) - Because a blockchain like Ethereum is inherently public, decentralized, and open source, the way that the developer community around Ethereum makes changes to the protocol is a lot different than how decisions are made in a centralized entity. Modern open source communities (like the vibrant community around Linux or Python) are far more analogous to the Ethereum development process.

The Ethereum community has developed processes that outline how members of the community could propose an improvement to the Ethereum protocol. These processes provide a public forum for discussion and encourage open-source participation from the community, which is important since Ethereum is a decentralized blockchain and relies on a globally-distributed community to monitor and improve the blockchain.

These proposals can be about the core rules that the blockchain follows (for example, when reaching consensus), or the proposals can just be proposing standardized versions of a core building block of Ethereum, like non-fungible tokens or wallets (described later on in the guide). Standard versions of these types of things make it easier to know that the code will work as intended when someone takes advantage of the composability of Ethereum to build an application using these standardized pieces.

Ethereum Request for Comment (ERC) - ERCs are a type of EIPs. Specifically, ERCs are EIPs that describe “application-level standards and conventions.” This specific category of EIPs merits a mention in this guide because ERCs are the contract standards that act as a template for some of the most important and well-known use cases within Ethereum. Developers can use these contract standards when building on Ethereum to save some time and effort, instead of having to start from scratch. Some of the most well-known ERCs are:

ERC-20 - This is a token standard for fungible tokens.

ERC-721 - This is a token standard for non-fungible tokens.

ERC-1155 - This is a token standard that optimizes some parts of the ERC-20 and the ERC-721 standards, and is commonly seen in the fractionalization of non-fungible tokens.

Sidebar - Why would anyone fractionalize (or ‘make fungible’) a non-fungible token?

There’s a few different use cases for fractionalized NFTs, even though the concept sounds like a contradiction. The best way to think about this idea is that some pieces of art are expensive (like Beeple’s $69M NFT sale or the Mona Lisa), which makes them inaccessible to the average person. Fractionalizing a very expensive NFT gives consumers the opportunity to own a (small, fungible) piece of a (very expensive, non-fungible) token.

From: Algorand

One thing to note is that most fractionalized NFTs will have embedded fungibility amongst themselves, so a user wouldn’t own ‘a piece of Mona Lisa’s face’ as opposed to ‘Mona Lisa’s hands’ or ‘the background of the Mona Lisa.’ Those different pieces might actually not be fungible (I’d pay a lot less for the background piece compared to the face piece!) - in practice, a user would just own one small fungible fraction of the total artwork.

Fractionalizing NFTs aren’t just about the money, either. NFTs represent unique digital assets, so fractionalizing an NFT also has implications around ownership, identity, and community.

Testnets - Testnets are copies of blockchains that allow developers to play around and test how their code will work on the ‘mainnet’ blockchain. When developers deploy smart contracts on a blockchain, that code will be viewable for as long as that blockchain is active, even if that specific smart contract isn’t being used anymore. That permanence, plus the possibility of the smart contract interacting with huge sums of money, means that developers want to be sure that their code operates the way they intend it to.

In Ethereum’s case, there’s a bunch of testnets (like Rinkeby, Ropsten, and Kovan) that developers can test their code on without actually risking user funds. Testnets are practice development environments for software developers in crypto.

Faucets - Faucets distribute ‘fake’ ETH to developers so they can use that fake ETH to test smart contracts on the testnet. The developers will need this ETH to deploy the contract and interact with it, but the testnet ETH doesn’t have real economic value like ETH on mainnet does. Faucets are easy ways for developers to get some fake ETH on testnets.

Imagine you’re a developer ready to deploy a smart contract on Ethereum. Let’s pretend the smart contract you’re working on will handle some funds, maybe something like a decentralized exchange (discussed in the Decentralized Finance section below). First, you want to test that smart contract on a testnet to make sure the code is working as planned. You’re going to want some ETH on the testnet to play with your smart contracts.

But, remember, the testnets are copies of the Ethereum blockchain, so the ETH on a testnet is essentially ‘fake’ ETH, in the sense that it isn’t exchangeable with ETH on the main Ethereum chain. You still want to test your contract using ETH, to see how it might work in practice, so faucets make it easy to get some fake ETH to play around with on the testnet.

Oracles - Oracles are used to connect blockchains to external systems, as needed. At some point, some of the applications that can be built on Ethereum will want to interact with a data feed that isn’t secured by the Ethereum network. Some data, like today’s weather or the score of a basketball game, has to come from “off-chain”, so oracles are the connection to the “real world.”

Oracles can be used to check the weather near orange crops in Florida for the sake of crop insurance, or an oracle can be used to verify scores for a decentralized sports betting application. Oracles present a potential trust issue (since the network of computers that make up a blockchain can’t practically *prove* what the weather was like in Florida), but there are pretty good solutions out there for applications that need an oracle.

Providers of Oracles (like Chainlink) come up with systems to try and ensure that their oracles are not a vulnerability, but an oracle can always be a point of weakness for a blockchain. You could imagine setting up a type of consensus mechanism for oracles where, even though there's a trust vulnerability (since the data comes from off-chain so it can always be manipulated in some way), it still requires 9 of 16 oracles to agree on what the oracle network is saying (or some similar mechanism).

Mempool - When a transaction has been submitted by users but hasn’t been validated and added to the blockchain, the pending transaction gets added to a waiting area called the mempool.

Before a transaction can be processed, the computers in the network will have to check whether the transaction is valid. For example, the transaction might spend more money than available in the account that’s sending the transaction, or the private key might not match with the public key of the wallet sending the transaction (more on this below in the Wallets and Identity section). While the computers in the network check these types of potential issues, the pending transactions wait in the mempool.

Technically, each individual participant in the network has its own mempool, but for the sake of this guide, it’s fine to imagine the mempool as a single waiting area for all of the blockchain’s transactions. Usually, transactions wait in the mempool for anywhere from a few seconds to a few minutes, but this will depend on demand (more on scalability below!).

Pending transactions on Ethereum can be viewed on a data provider like Etherscan.

Sidebar - How do users and applications interact with Ethereum?

Users will almost certainly just be using a web application through a browser like Chrome. Those web applications are built using specific packages of libraries (like web3.js or ethers.js) that help web apps interact directly with the nodes of a blockchain.

Developers build applications that interact with Ethereum through nodes running client software - in the below example, the client is Geth, a command line interface used to interact with the Ethereum blockchain. There are also “Nodes-as-a-Service” providers like Infura that let developers easily interact with nodes managed by a service provider, similar to how developers can tap into AWS to access server space. Those nodes then interact with the smart contracts and individual account balances on the Ethereum blockchain.

From: Understanding Ethereum

This isn’t very different from the “back-end” vs. “front-end” of other software products today. On the left of the diagram below, we can see how a user might connect to a traditional web application.

And right next to that image is an example of what the architecture of an Ethereum-based application might look like. Similar! What’s the difference? Ethereum serves as the back-end infrastructure for the crypto application, which makes it global, permissionless, and uncensorable.

From: The Architecture of a Web3.0 Application

Wallets and Identity

By design, blockchains enable users to self-custody assets, but wallets are more than just self-custody - wallets are also how users represent themselves in the world of crypto. In this section, I’ll explain what DAOs have to do with identity and how users can be smart about wallet security.

Wallets - A crypto wallet holds your assets, just like how your physical wallet holds your cash. But these wallets also hold information that represents you and your actions, like the applications you’ve interacted with and the trades you’ve made *using that wallet*.

Remember that, by design, transactions on blockchains are public, so when you use your wallet to do something on Ethereum, your wallet holds traceable, public data about the transactions managed with that wallet. This traceable data underpins the idea of ‘owning your own data’ in web3 - your assets, your transaction history, your interactions with decentralized applications travels with your wallet. Also, unlike physical wallets, many crypto users have a few different crypto wallets for different purposes.

There’s a few additional definitions needed here to fully explain wallets:

Public Key - This is a long code word that represents the outward-facing address of a wallet. Public keys are like your home address; the home address is unique, the address isn’t secret (public records, etc.), and the address corresponds specifically to one home (or in this case, one account, which is yours)..

You might share your address with a friend who wants to send you a letter or a gift, but if a random person saw your home address in the local government property records, it wouldn’t be a big deal. It’s fine if someone sees your public key.

Private Key - On the other hand, the private key is the password for actually doing anything with your wallet, so it is NOT okay for others to know your private key. The private key corresponds to a specific wallet’s public key, so if someone knows the private key, they have full access to that wallet!

Private keys are like the actual key to the home - you wouldn’t mind if someone randomly knew your address, but if you knew they had the keys to the house, you’d be rightfully worried. It’s worth reiterating - anyone with access to the private key can access that wallet. Do not share your private key with anyone, and don’t keep your private key stored anywhere where someone else might find it.

Sidebar - How do public keys and private keys work?

The mechanism behind public and private keys  is a really important fundamental topic to understand. Basically, public keys and private keys are used in a method of encrypting and verifying authenticity called private key cryptography.

Remember that public keys are outwards facing. When a user sends a transaction to their friend’s wallet (by using their friend’s public key), the user is putting a padlock on the transaction that can only be unlocked when their friend confirms that they have the specific private key of the wallet that the transaction was sent to. Despite the transaction being visible (because it’s on a public blockchain), it can’t be ‘unlocked’ without the specific private key corresponding to the wallet that now holds the funds.

Whether you are a developer building a project on Ethereum or just a user, it's important to understand the distinction between public and private keys. Misusing (or misplacing) public and private keys may have massive financial consequences for users, and unlike forgetting a password for a centralized website, there is no way for application developers to help recover it. As more people create crypto wallets and transact on the blockchain, this mode of transacting will become more normalized. But in the meantime, it's important to be aware of the learning curve and help explain it to others.

From: How to Generate Public and Private Keys

Seed Phrase - These are sets of random words (usually 12-24 words) that act as a final wallet recovery tool in case of emergency. Seed phrases should be treated with the same level of security as private keys, since losing your seed phrase or storing it where someone else will find it means that everything in the wallet is exposed. It’s important that all users exercise the appropriate steps to keep their seed phrases safe and confidential.

Wallet application developers don’t have access to the seed phrase, so if you lose your private key and seed phrase, your wallet cannot be recovered. But if you lose your private key, you can recover your wallet with the seed phrase.

Custodial Wallet - These are wallets managed by a custodian (any centralized entity that is responsible for holding the currency within those wallets) such as a regular Coinbase account. These custodians take on the responsibility of managing the underlying assets in that wallet (so users won’t have to manage their own private keys if they use a custodial wallet) in exchange for providing users with a more centralized, streamlined user experience.

This user experience doesn't usually include crypto-native authentication mechanisms -  for instance, a user can use a Google email address and password to log into their Coinbase account.

Custodial wallets are a great way to get started in crypto and a useful route for transferring funds from cash into crypto. On the flip side, because these custodians are centrally owned and managed, they carry some of the problems that decentralization set out to solve - like data ownership, control of the flow of information, and potential regulatory requirements.

There’s a popular saying in crypto about custodial wallets - “not your keys, not your coins.” Even Coinbase CEO Brian Armstrong has spoken about the importance of non-custodial wallets because of the risk of government regulation of custodial wallet providers. For users who prefer to manage their assets and transactions in a fully decentralized way, non-custodial wallets are a better fit.

Non-Custodial Wallet - These are wallets managed by… you! Software providers (like MetaMask, Argent, or Rainbow) provide software for users to access their wallet, but crucially, the wallet’s assets live on the blockchain, not in the software of any of the wallet providers. So if something were to happen where MetaMask became inaccessible, users could easily jump onto Rainbow, import their wallet (without the need for MetaMask’s approval) and interact with their assets through Rainbow. There’s also non-custodial hardware wallets, where the private keys are stored directly on a physical device (usually a little piece of metal that looks like a USB).

Non-custodial wallets come with the burden of managing public/private keys and seed phrases, but they also give users self-sovereignty (owning the assets directly) and a single identity into the world of Ethereum. Ethereum applications allow for users to “Sign in with Ethereum,” which really means “sign in using your non-custodial wallet.” Because of this, non-custodial wallets are a representation of a user’s identity, and these wallets open up a ton of design space in crypto like new ways to think about identity, credentialism, and ownership.

Social Recovery Wallets - This is a type of wallet recovery tactic enabled by some of the non-custodial wallet providers. Instead of needing to store a seed phrase, which people have famously lost before, users can assign people in their social networks to verify that the wallet corresponds to the person that it is supposed to correspond to.

With social recovery wallets, users can use the trust of their social circles as the backstop for their non-custodial wallets, while still retaining the self-custody / decentralization / single-sign-on benefits of non-custodial wallets on blockchains. Argent is an example of a social recovery wallet.

Sidebar - How can users be smart about wallet security?

I’m not going to use a diagram for this sidebar, because it’d be impossible to fit all of the necessary information about wallet security into a single diagram. Wallet security is incredibly important, and it is worth the effort to spend a small amount of time digging deep on best practices for managing your own funds in the world of crypto.

Thankfully, Punk6529 published an incredible tweet thread on the subject that covers all of the information needed to be smart about wallet security. Vitalik has also written a great article on the importance of social recovery wallets. And here is more information from hardware wallet provider Ledger on wallet security.

Here are some highlights from Punk6529’s thread, although I strongly recommend going through the thread yourself:

“Unlike your public key, you must never ever show your private key to anyone. If someone has your private key, it is GAME OVER.”

“Address/Public Key: Your email address (can be shared)

Private key: The password to your inbox (never share)

Wallet: Holds private keys

Seed phrase: Recovery system for private keys (never share)

Passphrase: Optional: extra password to create new wallets (never lose)”

“Security/resiliency are opposite goals. Printing flyers with your private keys is very resilient but your NFTs will be gone.

You can easily solve security by destroying your private keys.  But then you can’t access your NFTs either.

The art is balancing these two goals.”

Ethereum Name Service (ENS) - The Ethereum Name Service is an open naming system for the Ethereum blockchain, somewhat similar to a domain name provider for traditional websites. ENS maps addresses in Ethereum to a human-readable name, so I can use something like “brunny.eth” as my address rather than the longer form of my public key, which is 0xF67cAEbBbE7b630d137d2901637C02899ED3211b.

You can try it from your crypto wallets directly (custodial or non-custodial) - set up a small transaction to send a few cents of ETH, but write “brunny.eth” as the recipient, instead of my specific public key. The service should match “brunny.eth” with the wallet address.

ENS is basically a public good, and ENS names are so important to identity in the Ethereum ecosystem that they deserve their own explanation.

Decentralized Autonomous Organizations (DAOs) - DAOs are the crypto-native way to organize. DAOs can be companies, or non-profits, or social groups, or really any type of organization that uses crypto-native principles to organize themselves. By crypto-native principles, I mean concepts like community ownership, transparency, and decentralization, although it’s important to note that decentralization is a spectrum and not a binary off/on switch.

Unlike traditional corporations, which are centrally owned and managed in their entity creation and leadership team structure, DAOs design structures for operating crypto-native projects and businesses without centralized entities making decisions. Instead, DAOs strive for community ownership of projects. Another objective for many DAOs is full decentralization and democratization. In other words, decisions are made by democratic votes of key participants in the DAO. DAOs can be used to vote on application-level changes to products built on blockchains, and DAOs can also be used to reward and incentivize participants in the system.

A few DAOs are actually pretty close to autonomous, in the sense that automated smart contract code runs many of the functions of the DAO. An example of this is DAOs in DeFi, where the core value proposition of the DAO is decentralized maintenance of some smart contract that’s serving some purpose in DeFi. Most DAOs are working towards progressive decentralization, and most are more similar to a group chat with a bank account than a truly autonomous organization.

DAOs are a social by-product of permissionless blockchains, non-custodial wallets, identity tools like ENS, and shared purpose of participants in the ecosystem. DAOs could deserve their own section (or entire guide!) but my personal opinion is that the DAOs we participate in crypto are a key piece of how we redefine our digitally-native identities, so the concept makes the most sense in this section.

Decentralized Finance

DeFi is arguably the most successful use case for Ethereum so far, with over $100 billion in assets locked into DeFi protocols on Ethereum. DeFi also tends to use the most confusing terminology. In this section, I define DeFi broadly, dig into some of the confusing terms used in DeFi, and explain how Uniswap, a decentralized exchange built on Ethereum, works.

Decentralized Finance (DeFi) - Decentralized Finance refers to any financial application, exchange, or system that operates entirely on a blockchain without centralized gatekeepers. Today, there are hundreds (if not thousands) of DeFi projects across a variety of blockchains, with applications ranging from decentralized exchanges to lending to options and futures contracts. The primary objective of DeFi applications is to reimagine the functions of centralized banking institutions in a world where no centralized bank holds the power.

As one example of how this might play out, consider the purchase of a share of stock on the stock market today. When Sally buys a share of Tesla stock through her brokerage (Robinhood, Charles Schwab, Vanguard, etc.), that share of Tesla bounces around through a handful of different intermediaries before it can get to Sally. Usually, the system works fine, and the act of bouncing through different intermediaries doesn’t get noticed by the general public. But sometimes, crazy things happen - like the 2008 Global Financial Crisis or the Gamestop mania of 2021 - and the system breaks (like negative oil prices and canceled trades).

When the system breaks, people want to find out who is responsible for the chaos. And when they start digging, they find out that the traditional financial markets aren’t as clear and transparent as they might expect!

Decentralized Exchanges (DEXs) - The first major DeFi building block. Blockchains have enabled a new type of exchange, where assets can be traded directly with a smart contract instead of with a layer of opaque middlemen and quasi-governmental institutions.

In the Sally Tesla stock example, instead of trading through a brokerage (like Charles Schwab), which routes trades through a marketmaker (like Citadel), both of which are subject to constraints imposed by United States clearinghouses (like the DTCC) - Sally just trades with Uniswap smart contracts! All of this code is transparent and public, so Sally can see the funds flow, with no opaque middlemen clouding her view.

These decentralized exchanges use blockchains and economic incentives to create a market for virtually any two assets (i.e, BTC and ETH, or US Dollars and Euros, etc.). I’ll explain how Uniswap, the biggest DEX by market share, works below.

To understand how these decentralized exchanges work, we need to define a few additional terms:

Liquidity Providers (LPs) - The opaque middlemen described in Sally’s transaction above do provide a useful function in our traditional financial system - they provide liquidity to the system. Whenever Sally wants to sell her stocks in the traditional financial system, she almost always can (during regular trading hours, at least…), because these middlemen are paid to provide liquidity to Sally and other market participants.

How does the smart contract in a decentralized exchange protocol have assets to trade? Liquidity providers. DEXs give individuals the opportunity to provide liquidity in return for a small percent of the trading fees that are generated when someone trades assets with the smart contract.

The most well-known model for LPs is Uniswap’s model, where LPs deposit the same amount in value of a pair of two tokens into a smart contract. Again, LPs deposit into these contracts in exchange for a percentage of trading fees. The LPs can withdraw the tokens they put in as liquidity whenever they want, but then they obviously won’t participate in the upside of future trading fees.

Automated Market Makers (AMMs) - This is a type of DEX. An automated market maker is a smart contract that uses an algorithm to set prices. Uniswap’s constant-product formula (x*y=k) is the most famous example here, but that’s beyond the scope of this guide. AMMs are just a formula or mechanism for setting prices without needing a human to set the prices instead.

Stablecoins - Stablecoins are digital representations of physical currency - they’re supposed to represent the value of the currency they’re pegged to, but as a digital currency living on a blockchain.

DeFi lets users do a lot with crypto assets, but  it can be hard for users and investors to manage their assets in a fixed price range, because of the moving prices of crypto assets. Stablecoins serve as a way to keep less-volatile capital on a permissionless, decentralized blockchain, and they also act as reference prices to compare crypto assets.

Usually, stablecoins are pegged to the US dollar, but there are other currency stablecoins as well. There are both centralized and decentralized stablecoins, each with their own mechanisms for maintaining the 1:1 peg with the currency they’re tracking. And yes, crypto is disrupting the global financial system, but the major global currencies (US Dollars, Euros, Yens, etc) are still useful reference prices.

Total Value Locked (TVL) - TVL just means the total value locked in smart contracts on a given platform. TVL can be used outside of the context of DEX’s, since other applications besides exchanges might involve a liquidity provider mechanism (like lending, for example). Uniswap has several billions in TVL, and Ethereum as a whole entered 2022 with over $100B in TVL across applications.

Sidebar - How does Uniswap work?

First, let’s talk through the user experience. When a user wants to use Uniswap (or another DEX) to swap a token, the user gets to use a simple frontend that Uniswap built around the more complex smart contracts behind the scenes. As the diagram below shows, the user can swap ETH (or any other token) for another asset, almost like a vending machine. Users can just go in and swap from any token into almost any other token. Simple!

From: Understanding Ethereum

But what’s actually happening behind the scenes? Let’s start with the blue box in the diagram below; this is the Uniswap smart contract where liquidity providers deposit their tokens (Token A and Token B in this case).

On the left of the blue box is the LPs relationship with this pool; the LP deposits in two assets, and in exchange, receives a pool token that corresponds to a claim on those two assets that they deposited. Those pool tokens can be redeemed at the smart contract for the assets that the LP put in originally, whenever the LP wants to redeem (here, traders need to be careful of the impermanence loss I describe below).

On the other end is the user in the above diagram. Without needing to have any interaction with the various LPs in the pool, the user can go in and swap one of the tokens in the pool for the other one. The user also pays a small fee that flows through equally to all of the liquidity providers in the pool.

From: Uniswap documentation

This mechanism is just so cool. I studied finance earlier in my career, so when I learned about decentralized exchanges, it clicked for me much more than descriptions of Bitcoin as “digital gold” or Ethereum as “the world computer.” Uniswap would not have been possible without the infrastructure of a trustless public blockchain - what else are we unable to imagine today that will be mainstream tomorrow?

Uniswap does about $60 billion in trading volume a month as of early 2022.

The following terms (and the whole DeFi rabbit hole beyond the introductory definitions) probably require their own deep dive. However, these can be some of the first terms and concepts that a new user into the world of Ethereum sees, so I believe they have an outsized influence on the amount of confusion for new entrants into the space, so they merit some extra work on my end.

Yield Farming - As the name suggests, yield farming is the practice of “harvesting” yields by moving your money around DeFi applications. These applications offer enticing rewards in exchange for using their applications. If you’ve ever had a friend tell you about the crazy 100,000% APYs they’re earning in DeFi, they’re talking about yield farming.

A lot of DeFi applications need lots of money on their platform (liquidity, like we described above) as a key function of the value proposition of that application, whatever it may be (exchanging assets, lending, etc.). These DeFi applications are left with two options; raise a billion dollars and provide that liquidity yourself OR offer crazy rewards for people to provide liquidity themselves, and have these yield farmers act as the liquidity on the platform instead.

But wait? Where do the crazy rewards come from?

Well, these applications are promoting these crazy rewards as some new innovative mechanism, but in reality, these rewards are usually just (expensive) customer acquisition costs. In other words, these applications have tokens that in some ways represent the value of the application, and they distribute rewards (the 100,000% APY) to get people to use the application (customer acquisition costs). These rewards can be a mix of native tokens and other types of tokens.

So yield farming is the practice of searching for these yields and moving capital to the applications that have the best chance of becoming lucrative. It’s almost a form of angel investing into DeFi applications.

Staking - This term gets thrown around a ton, but staking basically just refers to locking an asset for some period of time and getting some benefit from locking it up.

Usually, this term is used in decentralized finance, where users stake tokens in exchange for rewards, but staking could also apply to other stuff too. Many DeFi protocols use staking as a way to control the liquid supply of their protocol's native token, similar to how a central bank tries to manage monetary supply. Investors are incentivized to lock up their tokens in the short term in exchange for economic rewards - sounds a lot like a bond to me!

Impermanence Loss - This term refers to the potential risk that Liquidity Providers have when providing liquidity in two or more tokens. In the Uniswap examples above, Liquidity Providers deposit two tokens to Uniswap in equal proportions and receive pool tokens that can be used to claim the two tokens back when LPs want to withdraw their capital.

One nuance here is that LPs deposit two tokens, each token having its own respective price (and price movements). When the LP wants to redeem the pool token in exchange for the two tokens, the price of the two tokens may have diverged significantly - one token price might be down 5%, and the other might be up 10%.

This divergence between token prices might mean that the LP would have been better off just holding the tokens individually instead of holding the pool tokens and earning the trading fees yield. Importantly, impermanence loss is labeled ‘impermanent’ because these are just ‘paper losses’ until the Liquidity Provider actually redeems the pool token - if the LP doesn’t redeem the tokens and just continues to provide liquidity until the prices converge, then the loss disappears.

A good primer on DEXs, LPs, and impermanence loss in different types of pools can be found here. Daily DeFi has an impermanence loss calculator to play around with a few examples.

Layer 2 and Proof-of-Stake

2022 is colloquially known as the “Year of the L2” in Ethereum, and the much-anticipated transition to Proof-of-Stake consensus should happen sometime in the summer. This section will dig into the blockchain trilemma, the future of Ethereum, and how rollups work.

The Blockchain Trilemma - Every blockchain faces trade-offs between three concepts; decentralization, scalability, and security. The general consensus (as of early 2022) is that Ethereum gets a thumbs up for decentralization and security, but a thumbs down on scalability (gas fees! Ahhhhh!). Hopefully, a few scheduled improvements in the near-term will hopefully solve the blockchain trilemma for Ethereum. Below are explanations of the considerations associated with each of these areas - it's important to understand how these trade-offs impact individual blockchains.

Decentralization - The Bitcoin whitepaper describes decentralization perfectly (my own emphasis added):

“What is needed is an electronic payment system based on cryptographic proof instead of trust, allowing any two willing parties to transact directly with each other without the need for a trusted third party.”

Blockchains act as an infrastructure layer that enables people across the world to interact with each other using only their computers, and without an intermediary.

Decentralization of blockchains is a spectrum; If the blockchain can be shut down by a small minority of users, or if the cost to participate in the network is too high (gas fees or the cost of setting up a computer to participate in the network), then the blockchain falls towards the centralized end of the spectrum. The greater the centralization, the greater the risk of monopolistic power and exploitation.

Security - Security refers to how difficult it would be for the underlying blockchain to get hacked or manipulated by outside parties. A good rule of thumb is the 51% majority; if someone is able to control 51% of the computers that are processing transactions for a specific blockchain, they can probably hack and compromise the security of the network.

There’s some deeper technical considerations here, but 51% helps paint a picture for the trade-off between security, decentralization, and scalability. More independent computers processing transactions for a given blockchain means more decentralization and more security (more computers = smaller chance of anyone getting 51% of the network). But more independent computers in the network means that each of the independent computers needs to communicate with an even bigger set of other computers in the network, which slows things down…

Scalability - …which leads us to scalability. Blockchains can get very congested when demand for them is high. For example, Ethereum has famously had periods of exorbitant gas fees, specifically when the network is getting the most demand. This demand increases the cost of getting a transaction added to the chain (gas) and results in congested, slow blockchains.

Zero-Knowledge Proofs - This concept isn’t really specific to scaling solutions, but it’s an important definition to clarify before talking about some of the scaling solutions. A zero-knowledge proof is a cryptographic method for proving that something is valid without needing to expose the specifics of the information.

For example, let’s imagine I am a buyer on Craigslist, looking for a television to purchase from some random person on the internet. Someone messages me to say they’ve got the TV I’m looking for - but the profile is anonymous.

As the buyer, I want to make sure that the seller actually has the TV before meeting up with them. But the seller might not want to share their personal information (drivers license, home address, pictures of the inside of their home) to random people on the internet, and on top of that, the seller wants to know that I’m a real person too! Neither one of us wants to share our personal information.

Using zero-knowledge proofs, I could prove to the seller that I’m a real, verified person without telling them who I am. On the other hand, the seller might prove that they actually own the specific television and that they are a legitimate seller, again, without exposing any of their sensitive personal information.

These are complex cryptographic primitives, so this really is an oversimplification here. Mostly, these zero-knowledge proofs can be used to solve security, scalability, and privacy challenges in the world of crypto.

Layer 2 scaling solutions - People really want to do stuff on Ethereum. It’s the most decentralized and established smart contract computing platform in the world, Ethereum has attracted the widest network of developers building blockchain-based applications. As a result of this activity, the demand to get transactions included on the Ethereum blockchain causes gas prices to get pretty high sometimes, which means Ethereum can be slow and expensive to use.

The blockchain trilemma implies that any blockchain that has optimized for security and decentralization will be making a trade-off in scalability. Since decentralization and security are so important to the promise of what blockchains can achieve, scalability has become the hardest one to figure out. Ethereum is betting on a wave of changes to help solve the scalability issue.

One of these changes is a shift from users interacting primarily with the Ethereum blockchain itself (known as “Layer 1”) to instead interacting with Layer 2 scaling solutions. Basically, this means moving most transactions and applications on Ethereum’s mainnet to Layer 2, which are blockchains that use Ethereum’s security and decentralization, but can scale transaction volume several orders of magnitude above what Ethereum itself can do. Layer 1 Ethereum will be responsible for consensus specifically, while the Layer 2s will be actually executing the transactions and code.

Rollups - Rollups process a bunch of transactions on their own separate blockchain. After executing these transactions on their own chain, the rollup compresses all of these transactions into smaller packets of information. These smaller packets of information get ‘posted’ on Layer 1 Ethereum, which means that the rollups inherit the security of the Layer 1 chain while scaling the number of transactions that can be processed (since the information is compressed).

These much smaller packets of transaction information include proof that these transactions were processed in a way that would abide by the rules of Ethereum.

From: Understanding Rollup Economics

This might sound like a compromise of decentralization. But a key aspect to rollups is that Ethereum can just check the proof rather than doing the work of ‘proving’ all of the individual transactions, which saves an exponential amount of effort (so it makes Ethereum more scalable!). Because Ethereum gets the final say on whether these rollup transactions are allowed to be posted onto Ethereum, all of the rollup transactions are still fully secured by Ethereum without compromising on centralization.

There are a couple types of rollups. The difference between rollups is the method that they use to prove to Ethereum that their transactions are valid.

Optimistic Rollups - These types of rollups keep records of the proofs of the transactions on the rollup, but only present these proofs to Ethereum when Ethereum requests the proof specifically. Instead of having to prove to Ethereum’s mainnet that every transaction is valid, optimistic rollups provide proofs when necessary, which helps in terms of scalability.

ZK Rollups - These types of rollups use zero-knowledge cryptography to prove that transactions are valid without having to show all of the details within the transactions. Zero-knowledge proofs are explained above, but the main point is that these rollups save a lot of space by only needing to show the smaller zero-knowledge proof instead of the entire transaction.

Sharding - Sharding is the process of splitting up a blockchain into smaller shards to reduce congestion. Sharding makes Ethereum more accessible - basically, nodes will only need to hold the data about the specific shard they’re connected to, rather than the entire Ethereum blockchain - while also making Ethereum more scalable.

Sharding is one of the planned improvements to the Ethereum blockchain that will be important after The Merge.

Beacon Chain - The Beacon Chain is the foundation for Ethereum’s transition away from Proof-of-Work and into Proof-of-Stake consensus. The Beacon Chain exists separate from Ethereum’s blockchain today, and the Beacon Chain introduces staking, which is necessary for the transition to Proof-of-Stake.

Soon, the Beacon Chain will be merged with the existing Ethereum blockchain, introducing PoS officially as the Ethereum blockchain’s consensus mechanism and signaling a major turning point for the future of Ethereum.

The Merge - It is fitting to end this guide with a term like The Merge. In the next few months, Ethereum Mainnet and the Beacon Chain will merge in the most widely-anticipated event in the blockchain world…. Ever.

The end of the Proof-of-Work era for Ethereum is only a few months away, and the repercussions of this switch could potentially be massive. If for some reason, The Merge fails, the impact will reverberate across the entire crypto landscape. But if successful, The Merge could be a signal that Ethereum’s journey to becoming the global settlement layer is closer than expected.

Resources

So that’s it! That’s a Simpler Guide to Ethereum.

First, we worked through the foundational pieces of what a blockchain is and why blockchains are important before diving deeper into some of the specific features of the Ethereum blockchain.

Then, we talked about some of the killer applications being built on top of the Ethereum blockchain; wallets, DeFi, DAOs, and NFTs.

After that, we wrapped up with the future of Ethereum, discussing the shift to Proof-of-Stake consensus and describing how Ethereum hopes to solve the blockchain trilemma.

All of these definitions are simplified versions of complex topics, but hopefully this guide inspires you to dig deeper into the world of Ethereum. Below, I compiled some resources for those of you looking for the next steps in your learning experience. If you want to reach me for questions or feedback, DM me on Twitter!

Thank you to Josh Stark, Bethany Crystal, Daniel Schlabach, Nico Kuzak, Adam Tzur, Naz Rizvic, and Miguel Lemos for your thoughtful help and feedback here!

Good places to go next:

The following resources were compiled by the Ethereum community in this document after Josh Stark and I began the compilation in late 2021.

• General resources

  • Ethereum.org - What is Ethereum? - learn the basics, with links to material covering advanced topics

  • ETHHub - community maintained resources covering wide variety of Ethereum topics

  • Ethereum Foundation Youtube Channel - ethereum talks & community developer calls

  • Devcon archive - archive of all videos & talks from the annual Devcon conference

  • Scott Sunarto’s Working in Web3 Handbook - guide covering various topics

  • Blockchain@Berkeley Courses - free online courses about cryptocurrency

  • Finematics - video explainers for various topics in ethereum, web3, defi

  • Fellowship of Ethereum Magicians - a forum for the crypto community to have a place where anyone can join, create topic and discuss mainly about EIPs and technical difficulties of the Ethereum ecosystem.

  • Ethereum Wiki - Ethereum wiki covering all things related to Ethereum

• Blogs, Media, and Research

  • Week in Ethereum News

  • Paradigm Research

  • The Defiant

  • Bankless

  • The Daily Gwei

  • The Block

  • Decrypt

  • Dark Star

  • Messari Research Hub

  • a16z Crypto Canon

  • Linda Xie’s Beginner Guides

  • Tim Beiko’s AllCoreDevs Updates

  • Ben Edgington’s What’s New in Eth2 blog

  • Polynya – Medium

  • Ethereum: The Infinite Garden (feature documentary film in production)

  • Gaby's Web3 Reading List

• Podcasts

  • Into The Bytecode

  • Bankless

  • The Daily Gwei

  • Into The Ether

  • a16z

  • Into The Ether

  • Unchained

  • Epicenter

  • ZK Podcast

  • Uncommon Core

  • Redefined Life

• Books

  • The Infinite Machine

  • Out of the Ether

  • Mastering Ethereum (free online)

  • Finite and Infinite Games

Linked to in the Guide:

• Graphical Guide to Understanding Uniswap

• Ethereum EVM Illustrated

• Understanding the Ethereum Yellow Paper

• Understanding Ethereum

• Punk6529 tweet thread

• Understanding Rollup Economics

• The Architecture of a Web3.0 Application

One of the projects I’ve been tinkering with recently is figuring out how to calculate the total market capitalization of assets on Ethereum, or in other words, the Ethereum ecosystem’s total market cap. This is the total value of all assets on Ethereum including ETH, ERC-20s, NFTs, and synthetic/derivative assets.

https://twitter.com/0xstark/status/1465860165240950788?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1478185821060558851%7Ctwgr%5E%7Ctwcon%5Es2_&ref_url=https%3A%2F%2Fmirror.xyz%2Fbrunny.eth%2Fj9SNenT-U84EcqrZiDzMsE4AObZtsv33EkbB8YYbDV0

This is a relevant and useful metric. The entire crypto ecosystem is made up of blockchains, and these blockchains enable the creation of new types of assets, as well as new methods of utilizing and trading the assets. One of the most obvious questions to ask about crypto is “what is the value of all of the assets on Blockchain X?”, and for a huge blockchain ecosystem like Ethereum’s, the only sensible way to answer that question is to include the value of all assets that live on Ethereum, and not just the value of the blockchain’s native token (ETH, in this case).

Despite the various data providers and analytics solutions available for Ethereum, a single source of information for this data isn’t very easy to find. Most publicly available estimates for “total market cap of Ethereum assets” usually just refer to the value of ETH or just to the sum value of all ERC-20s. But with the rise of NFTs, most of which are transacted on Ethereum, and the large amounts of other blockchain’s native tokens that live on Ethereum as wrapped tokens, there’s a larger scope of assets that could be included in the calculation and compiled into one simple number.

Why is this a difficult problem? For one, the various data providers sometimes have different data about the same thing. For example, here are two different NFT data feeds - Crypto.Com and NFTGo - with significantly different values for the market cap of different NFT collections. On top of that, some metrics provided by sites like CoinMarketCap don’t correspond to the data that I am intending to capture in this analysis. USDT is a good example here; CoinMarketCap lists USDT’s market cap at ~$80B, but that number includes the token contract deployed on non-Ethereum chains like Solana and Avalanche. EtherScan shows that the USDT balance *just on Ethereum* is closer to $40B.

With all of this in mind, I set out to make a rough v1 dashboard for the total Ethereum ecosystem market capitalization calculation. My hope is that by poking at the problem and then open-sourcing my work, I might inspire someone to build a dynamic dashboard with permanence. If you’re interested in doing this, DM me!

Methodology

I broke down the Ethereum-based assets that I wanted to include in this calculation into four major categories; ETH, ERC-20s, ‘synthetic assets’ and NFTs. The market cap of Ether alone is simple; $310 billion as of January 26, 2022.

ERC-20s

For ERC-20s, I used CoinMarketCap to check which blockchains individual tokens were deployed to, and then I verified the reported market cap number versus Etherscan contracts. In situations where the token contract is deployed on several chains, like Tether described above, I only used the supply of tokens that was deployed specifically to Ethereum. Of course, this was a tedious task for v1, but going through the motions here helped me think through the nuances that need to be considered when building out a more dynamic dashboard.

In total, the ERC-20 calculation added an additional $240 billion in Ethereum ecosystem market capitalization. While ETH itself is not an ERC-20 token, wrapped ETH is an ERC-20-conforming token, so it is included in the calculation with other ERC-20s. I capped the analysis at ERC-20s with a total asset market cap of $300M or more as of 1/26/2022, but as a rough estimate, I believe that the ‘long-tail’ of ERC-20s adds another $20-40 billion in market cap. This is not included in this calculation, in an effort to conservatively underestimate the true number.

Synthetic Assets

I also wanted to capture the value of what I’m calling ‘synthetic assets’; basically, derivatives of cryptoassets that are traded in separate Ethereum-based liquid markets from the original asset.

The fact that many assets are now cross-chain introduces additional complexity. Some assets on Ethereum were “imported” from another blockchain. This means that they were created on a different chain, but then migrated over and “wrapped” inside an Ethereum ERC-20, which serves as an “IOU” that can be redeemed on the original chain. For example, wBTC is “wrapped Bitcoin” which can be used like an Ethereum token. We’ll call these “inbound wrapped assets”. There are also Ethereum-native assets that are migrated over to other chains, where they are ‘wrapped’ into another blockchain’s token format. This can be referred to as an ‘outbound’ wrapped asset.

An example of an outbound wrapped token is surprisingly ENS, the governance token for the Ethereum Name Service protocol, which would naturally seem like an Ethereum-only asset. However, the ENS token’s CoinMarketCap page shows that the ENS contract has also been deployed to Solana. If the Solana contract is opened, it’s clear that this “Solana-deployed ENS” is just a ‘wrapped’ version of ENS that has been sent over to Solana. Counting this Solana-wrapped ENS in this calculation would double count the true value of ENS, since the Ethereum-based ENS market cap already includes the Ethereum-native ENS tokens that remain on Ethereum, where they can be “redeemed” using the Solana-based IOU. These situations are not counted in my calculation to avoid double-counting assets.

Some DeFi positions are considered synthetic assets for the sake of this calculation. Uniswap v3 turned liquidity provider positions into NFTs, and other derivatives like stETH and xSUSHI act similarly - a financial instrument is created using another asset, and then the created financial instrument is traded in its own liquid market and utilized in its own ways, separately from the initial asset used to create the instrument. A reasonable argument against including these types of synthetic assets is that inclusion would seem to double count some values of assets on Ethereum, like the staked ETH in a staking pool. However, my thought process is that these derivatives have their own value and their own risk profiles (for example, consider the risks of holding stETH vs the risks of holding just ETH), so I chose to count them in this calculation.

I included all synthetic assets with a total asset market cap of $300M or more as of 1/26/2022. Synthetic assets accounted for roughly $25 billion in assets that live on Ethereum.

NFTs

Finally, NFTs. Like I mentioned in the introduction, finding the right NFT data is difficult. The biggest reason for this difficulty is the fact that most markets for NFTs are infrequently traded and illiquid, which makes calculating a market cap figure difficult. On top of that, the methodology used by two different firms can be significantly different, while both remaining completely reasonable. I used NFTGo’s data feed because I felt that their methodology was the most transparent and reasonable of the NFT data providers. For example, NFTGo counts NFTs that have previously traded at $X but are currently listed at a higher price $Y at the value of their last trade ($X) rather than at the inflated listed price ($Y).

NFTs added another $9B to the total market capitalization figure, which might be surprising given their outsized influence in ‘web3 culture’ relative to their cumulative market capitalization. As the NFT digital art and collectibles category continues to grow and evolve, I’m confident that this data will become more standardized and accessible, and I’m hopeful that NFTGo’s soon-to-be-released API will make it easy to pull this data into a dynamic dashboard.

Conclusion

So that’s it! During a static moment in time during the last week of January 2022, the Ethereum ecosystem’s total market cap was roughly $585 billion. This “static moment in time” approach is crude, but it serves a few purposes, like helping me think through the process, surfacing potential issues to solve in a future iteration of the dashboard, and providing a useful ballpark estimate for the true figure.

Hopefully, this project inspires people to experiment with creating dynamic versions of this dashboard or approaching the problem from a different angle. Especially if 2022 becomes the year of the L2, the inclusion of Layer 2 assets into this calculation will add a whole new dimension of complexity to the problem. If you’re interested in building something like this out or if you have any feedback, please reach out via Twitter or e-mail!

Calculation and sources are documented here.