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the end of this month marks one year of being out of my abusive relationship. this isn’t something I’ve talked about publicly but it has been on my mind. i have been going through a period of learning self acceptance and trying to cope/understand what was said and done to me. I hope this next year is a new chapter for me and it brings lots of good things. i am very excited and motivated to move forward and put in everything i have for the things I love. i want to thank everyone who has supported me the last two years. i cannot begin to explain the amount of loneliness and sadness I felt during these times but i ALWAYS had a community and so many people being kind to me through vtubing. every compliment, supportive message, or just checking in on me meant so much even though im very shy and might not show my gratitude enough. i truly believe it is what kept me going. thank u guys for supporting me 💙

Full disclosure, and just to get this out there publicly so that it's impossible to "leak". I haven't told anyone yet. Some people are making guesses. The reasoning is off, but they do hit certain areas. 👇 I might name the Chinese version of my book/memoir "币安人生". This is not related to any meme tokens or listings. But I embrace the meme culture. I like that meme/word. It's sticky, for me. Disclaimer: I don't hold any "币安人生" meme coin, and have no intention to do so. And I also reserve all rights not to use that title. I might change my mind last minute. The English name of the memoir will likely be completely different, not decided yet. Book ETA, 4-6 weeks, English and Chinese version both at the same time. Self published. Takes too long to go through a publisher, even though they will likely help significantly with distribution. All proceeds I receive from the book will go to charity. Not trying to make money from the book.🙏

A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

🔥llm.c update: Our single file of 2,000 ~clean lines of C/CUDA code now trains GPT-2 (124M) on GPU at speeds ~matching PyTorch (fp32, no flash attention) On my A100 I'm seeing 78ms/iter for llm.c and 80ms/iter for PyTorch. Keeping in mind this is fp32, with no flash attention yet, and slightly stale PyTorch (2.1.0). - It is a direct implementation of the training loop and backpropagation in C/CUDA. - It compiles and runs instantly. No more "hit run then wait for tens of seconds for unknown reasons", for mountains of inscrutable abstractions to build a Universe. - It deletes the need for the Python interpreter and a deep learning library. - It allocates all the memory a single time at the start. - It's pretty cool. How: Getting this to work required us to write a lot of custom CUDA kernels, and doing this manually (instead of using Tensor ops of aten/PyTorch and torch.compile etc.) is a bit like programming in assembly. And you spend quality time looking at more assembly (CUDA PTX/SASS). But this also means we get to hyperoptimize the code and possibly explore optimizations that torch.compile might find difficult to, which is awesome. Examples of optimizations that went in over the last few days: - we're being clever with our memory consumption in the backward pass, only using a few buffers we need to propagate the gradients, saving memory capacity. - one fused classifier kernel does the last layer forward pass, the loss, and kicks off the backward pass. - many improvements to all the kernels involved, including e.g. gains from carefully constraining execution within the autoregressive mask in attention - cuBLAS(Lt) calls for all heavy lifting matmuls, and fused bias accumulation Big credits to two CUDA experts who appeared from somewhere on the internet to help this open source project, ngc92 and ademeure. We're hanging out of Github and Discords of CUDAMODE and my NN Zero to Hero. Next steps: - more optimizing of our (fp32) kernels, and especially switch to flash attention. - mixed precision training (fp16 to start). - multi-gpu training (DDP to start). - data & evals to set up a proper GPT-2 training runs - 🚀 repro GPT-2 (1.6B) training run. - more modern architectures etc. (Llama 3?) - writing, videos, exercises on building all of this from scratch. Figure 1: eye candy: timing profile of the kernels (one layer). NVIDIA cutlass kernels with solid compute throughput taking up a lot of the running time => nice.

Updates since then: * Deepseek v4 is out. There *is* a 2-bit quant that can run within 90 GB ( ), and it works, however it's only fast on Apple hardware (I've head ~35 tok/s). On AMD, it's ~7 tok/s. IMO actually taking the effort to properly support more than one hardware manufacturer is a great example of the difference between mere "decentralized AI" and genuine "CROPS AI". I hope we can become better at this. * also has alpha telegram support now. However, the path to adding your account is quite janky * looks promising as a way to run "dense" models (eg. Qwen 27B) more efficiently. It's janky, but on my 5090 laptop it seems to be ~2x more tok/s than llama.cpp * VoxTerm (local AI recording, no third-party servers) continues to be developed And there's a lot more projects coming on the horizon. One other thing that has been on my mind is that there's actually a lot of intersection between "CROPS ethereum access layer" and "CROPS AI". For example, we want a ZK way to make (paid) calls to remote LLMs. But if we have this, then it's just as useful for solving another problem: private RPC reads in Ethereum. Another example: application-specific finetuned LLMs. Leanstral ( ; I get ~38 tok/s on AMD) fits into < 70 GB, but can hold its own against 1T models on writing Lean code. Things like this are a huge boon for writing more secure code ( ). We should have models finetuned for Ethereum-related use cases as well.

In 1990, the World Wide Web was invented on Steve Jobs' computer. Steve ignored it. This is the story I tell in my new book Steve Jobs in Exile. Here is what it should tell the rest of us about the moment we are in now. Steve was running NeXT, an unsuccessful computer company. He had been pushed out of Apple five years earlier and was burning his fortune trying to build a successor to the Macintosh. The machine NeXT sold was a matte-black magnesium cube -- expensive and beautiful and not selling. In October of that year, on the other side of the Atlantic, a British physicist named Tim Berners-Lee took delivery of a NeXT Cube at CERN, the physics laboratory on the Swiss-French border. He used it to invent the World Wide Web. The web ran on the Cube for its first year of existence. The revolution was happening on Steve's hardware, and yet Steve ignored it. Here is the question I keep thinking about from my book. If Steve Jobs, the most visionary tech mind of his generation, missed the Web, the most civilization-shaping tech of his lifetime, how are the rest of us supposed to see anything coming? Berners-Lee had been asking his boss at CERN for a NeXT Cube for months. His boss finally signed off, hoping to test the exotic Cube. "He suggested that I should buy one of these NeXT machines I'd been talking about so enthusiastically," Berners-Lee later told Fresh Air. "And if we needed a sort of test project to run on the NeXT machine ... 'Why not just do this hypertext thing you're talking about?'" The "test project" evolved into the World Wide Web. The problem Berners-Lee was trying to solve was not a glamorous one. CERN employed thousands of scientists from over a hundred countries, most cycling through on short assignments and taking their knowledge with them when they left. Berners-Lee was trying to keep institutional knowledge from walking out the door. He wanted a system that worked the way human memory does, where any piece of information could connect to any other without permission or central control. Through late 1990, he coded in his gray-floored office. The Cube's object-oriented system let him build in months what would have taken a year on anything else. By December, the first website went online. The World Wide Web now existed, running on a single black NeXT Cube in CERN's Building 31. Berners-Lee scrawled a warning on it in red ink: "This machine is a server. DO NOT POWER IT DOWN!!" Underneath the elegant interface he was building HTTP, HTML, and the server software that would deliver web pages. These three inventions would form much of the invisible plumbing of our modern connectivity. When a colleague of Berners-Lee's brought a demo of the Web to NeXT's headquarters in California, he could not get anyone there to pay attention. Nobody even dared show it to Steve, afraid he would dismiss it. NeXT was busy with its own internet plans, which Steve eventually killed. So back to the question. If Steve Jobs missed the web, how are the rest of us supposed to see whatever comes next? The honest answer is that we cannot. Nobody can. The rest of us are not going to outpattern-match Steve Jobs. But here is what I learned writing Steve Jobs in Exile. Transformations almost always begin in obscurity, on the margins, solving boring problems with boring tools. The web did not look revolutionary in 1990. It looked like a tool for sharing physics papers. We are in another such moment now. AI is the obvious changemaker. But the biggest transformations are rarely the obvious ones. The next one is happening somewhere right now, and it is trickier to spot than any sweeping proclamation about AI. We will recognize it, if we recognize it at all, from the unglamorous work few people are focused on. I will not speculate on what Steve would have made of AI today. But if he could miss the Web, the rest of us are going to have to look harder. Photo of the original CERN NeXT Cube courtesy of Robert Scoble.

Some of my perspective on where the @ethereumfndn is going. First of all, this is only my own view. The board is not just me, and I have no extra special powers on the board that the other board members do not. @aerugoettinea is the one executing much of this transition. My input has been largely on technical questions. The board is in the process of expanding, and my own power within the org will continue to decrease, which is honestly what I want. The 2025 era brought many important improvements to EF and its ability to execute. Many issues were resolved, and EF continues to benefit from its improved efficiency and greater focus on concrete goals to this day. And so with those problems resolved, early this year, the largest remaining hole that I perceived was something different nagging at me: I would regularly spot people saying things like "vitalik says these beautiful things about ethereum needing to be decentralized, and have privacy, and be a sanctuary technology, but why do the EF's actions not reflect that?" Now, you may have been hearing something different. You may not have been sensing a feeling of crisis at all, and maybe were hearing people saying that finally we were taking execution and BD seriously and the main task for us is to keep going that way and be even better and faster. Then probably there is genuine difference between you and me, in what kinds of criticism I take most seriously, and what kinds of critics through their criticism are most able to make me feel pain. As an analogy, let's briefly switch over to a different domain. One belief you can have about Google is that it is a success story, and has brought a lot of good to humanity in organizing the world's information. Another belief you can have about Google is that they had a beautiful idealistic beginning, but at some point the corruption of mainstream corporate attitudes seeped in, and they slowly bit by bit completely abandoned the "don't be evil" slogan. My belief on Google specifically is probably somewhere between the two. BUT, if you had taken me back in time to ~2008, and offered me a button to press to make Google one or two standard deviations more "dogmatic", eg. give Richard Stallman permanent veto power over some key policies, I would immediately press it. Why? Because a choice for one company is not a choice for the world, or even one country. Google existed and exists in the context of a technology industry generally drifting away from early idealistic don't-be-evil roots and toward greed for financial gain, totalizing visions of accelerated superintelligence, infiltration by sociopaths, and craven capitulation to (or worse, active participation in) government pressure for ideological control, surveillance and war. And so *one company* doing something different, positioning itself to be what George Bernard Shaw calls the Unreasonable Man, resisting the trend of the times, would have been better for freedom, balance of power and stability of society as a whole, than *all* large companies bending to dominant trends. This is a part of my version of pluralism. This line of thinking is not just mine, but I also is not too far off from what Aya and others had in mind with the Mandate. Now how does this all get to the role of the EF? EF is not a "center of Ethereum", rather EF is "one node, with a defined purpose, alongside other nodes". We've always said that the EF should be the latter, but many in the Ethereum ecosystem (and even within the EF) wanted us to be the former. Now, we are taking action to ensure that we will be the latter. This is particularly important because EF is a limited organization, with limited resources and limited organizational capacity. The EF has only ~0.16% of all ETH (less than many other individual ETH holders), whereas among other blockchains it's common for "the central foundation" to have 10-50%. Fiscally, the EF was originally designed to fulfill a limited work scope defined in the token sale docs and other pre-launch materials (building the chain software; getting through Frontier, Homestead, Metropolis, Serenity), which was fully completed in 2022; it was not designed to be an eternal steward. And so today, the EF is choosing to use its remaining resources to pursue longevity over breadth (yes, this means we sell less ETH). The EF focuses *specifically* on those activities critical to the success of ethereum as a censorship/capture-resistant, open, private and secure system, that would not happen otherwise. This means making hard choices, and in some cases even activities that we highly approve of and people that we highly respect becoming outside of the EF. People of great technical talent, public respect and even alignment with the mission and CROPS being outside of the EF is in fact necessary if we want important tasks to be able to attract outside capital. This also means the EF taking opinionated stands culturally. This is all intended in cooperation with all other parts of ethereum. We recognize that many other parts of the ethereum world highly respect CROPS and related values. But highly respecting is not the same as choosing to specialize and totally dedicate to a domain (Compare in a different domain: I think reducing animal cruelty is important, and I like vegan food, but am not full unconditional vegan myself) EF is still in a transition period, and we expect its new long-term form to stabilize over the next few months. What are the guiding principles of this new form? Again, I am only one person, but I can give my answer from a technical perspective (there are also critical non-technical aspects). At the core, *Ethereum must be impressive*. We are living in an age of highly intelligent AI and all kinds of other technological acceleration. "Status quo EVM, with a hard fork or two a year to optimize for short-term needs of users" is not interesting. To some, "impressive" means: 250ms latency and 1M TPS. I think Ethereum trying to go that route is a mistake. Being as fast and as scalable as possible, and only a small epsilon more decentralized than the others, is a route to mediocrity, and if we try it we will lose. I think Ethereum should scale. But I think Ethereum should strive the hardest to be deeply impressive in a different dimension: the CROPS dimension. This means things like: * Provably bug-free Ethereum. This is a goal that all cybersecurity researchers would have thought is absurd and impossible, up until roughly 6 months ago. Now, it's on the cusp of being possible, thanks to AI-assisted formal verification. So we should be frontrunners in doing this. * Available chain consensus. Ethereum is, and with lean consensus will cotninue to be, the ONLY chain that has both (i) traditional-BFT style properties that it's safe under asynchrony up to a high level of fault tolerance, and (ii) the bitcoin PoW-style property that under synchrony it's safe up to 49% attackers. As far as I can tell, literally no other chain has this or is planning for it; bitcoin goes for (ii) only and most other chains go for (i) only. Some will remember I fought hard for this, Unreasonably insisting that it is not OK for ethereum to rely on social consensus and hard forks to rescue ethereum from 34% of nodes going offline. It's OK for chains like hyperledger, bnb, solana, tempo, etc. It's not OK for bitcoin or ethereum or eg. zcash. * Intermediary minimization. The fact that smart contract wallets, protocols like railgun, etc have to send transactions through intermediaries to get included onchain is honestly embarrassing, and it's a constant point of fragility. Hence the work on FOCIL and EIP-8141 (and 7701 and years of work before) to make transaction sending intermediary-minimized with public mempool and strong inclusion properties, in a truly general-purpose way, that covers not just eg. secp256r1, but also privacy protocols and much more. Kohaku is pushing intermediary minimization at the user layer, pulling Ethereum away from the dystopian status quo world where our wallets don't even verify the chain, send our private data out to a dozen third-party servers, and toward a brighter CROPS future. Some of these goals are Unreasonable - maybe Ethereum would be "fine" getting only 50% of the way - what if we depend on intermediaries, but make it easy to switch? But going 50% of the way would not make Ethereum Deeply Impressive in the CROPS way. So we push for 100%. Fortunately all these goals are compatible with high TPS, this is a major focus of research (esp. on scaling the state). Well-designed L2s can also help, especially L2s optimized for specific applications (eg. high-volume trading, privacy...). These goals are even compatible with significantly lower slot times, thanks to Raul's work on erasure-coded P2P, and many other optimizations. The most high-value "product" of the ethereum blockchain, financially speaking, is ETH the asset. Ethereum secures $250 billion of ETH. The types of properties of Ethereum that I mentioned above are very good for ETH the asset. Nearly 90% of my net worth is in ETH, and most of the remainder is ~$40m of onchain fiat of which every dollar has already been allocated for some open-source biotech or software or hardware initiative. That said, there are aspects of supporting ETH the asset - *necessary* aspects even - that are outside the scope of the EF. This is where we need other heroes (some of whom hold more ETH than the EF does) to step in and help. EF has been recently thinking more about how it will relate to other such organizations, and give them needed initial support. EF will be a smaller ship than in previous years, a more opinionated one - in some cases more opinionated in ways that might be difficult to comprehend - but a longer-lasting one, and one suited to making sure that ethereum brings something meaningful to the world. We are grateful to all those inside and outside the EF who are helping to make this happen.

My first breakthrough in understanding how people think differently occurred when I was a young father and had my kids tested by Dr. Sue Quinlan. I found the results remarkable, because she not only confirmed my own observations of the ways that their minds were working at the time but also predicted how they would develop in the future. I turned to her and others years later when I was trying to figure out the different thinking styles of my employees and colleagues. #principleoftheday#