This is an email I sent earlier today to all employees at Coinbase: Team, Today I’ve made the difficult decision to reduce the size of Coinbase by ~14%. I want to walk you through why we're doing this now, what it means for those affected, and how this positions us for the future. Why now Two forces are converging at the same time. We need to be front footed to respond to both. First, the market. Coinbase is well-capitalized, has diversified revenue streams, and is well-positioned to weather any storm. Crypto is also on the verge of the next wave of adoption, with stablecoins, prediction markets, tokenization, and more taking off. However, our business is still volatile from quarter to quarter. While we've managed through that cyclicality many times before and come out stronger on the other side, we’re currently in a down market and need to adjust our cost structure now so that we emerge from this period leaner, faster, and more efficient for our next phase of growth. Second, AI is changing how we work. Over the past year, I’ve watched engineers use AI to ship in days what used to take a team weeks. Non-technical teams are now shipping production code and many of our workflows are being automated. The pace of what's possible with a small, focused team has changed dramatically, and it's accelerating every day. All of this has led us to an inflection point, not just for Coinbase, but for every company. The biggest risk now is not taking action. We are adjusting early and deliberately to rebuild Coinbase to be lean, fast, and AI-native. We need to return to the speed and focus of our startup founding, with AI at our core. What this means To get there, we are not just reducing headcount and cutting costs, we’re fundamentally changing how we operate: rebuilding Coinbase as an intelligence, with humans around the edge aligning it. What does this mean in practice? - Fewer layers, faster decisions: We are flattening our org structure to 5 layers max below CEO/COO. Layers slow things down and create coordination tax. The future is small, high context teams that can move quickly. Leaders will own much more, with as many as 15+ direct reports. Fewer layers also means a leaner cost structure that is built to perform through all market cycles. - No pure managers: Every leader at Coinbase must also be a strong and active individual contributor. Managers should be like player-coaches, getting their hands dirty alongside their teams. - AI-native pods: We’ll be concentrating around AI-native talent who can manage fleets of agents to drive outsized impact. We’ll also be experimenting with reduced pod sizes, including “one person teams” with engineers, designers, and product managers all in one role. In short: AI is bringing a profound shift in how companies operate, and we’re reshaping Coinbase to lead in this new era. This is a new way of working, and we need to leverage AI across every facet of our jobs. To those who are affected I know there are real people behind these decisions — talented colleagues who have poured themselves into this company and our mission. To those of you who will be leaving: thank you. You’ve helped build Coinbase into what it is today, and I am sincerely grateful for everything you've done. All impacted team members will receive an email to their personal account in the next hour with more information, and an invitation to meet with an HRBP and a senior leader in your organization. Coinbase system access has been removed today. I know this feels sudden and harsh, but it is the only responsible choice given our duty to protect customer information. To those affected, we will be providing a comprehensive package to support you through this transition. US employees will receive a minimum of 16 weeks base pay (plus 2 weeks per year worked), their next equity vest, and 6 months of COBRA. Employees on a work visa will get extra transition support. Those outside of the US will receive similar support, based on local factors and subject to any consultation requirements. Coinbase prides itself on talent density. Our employees are among the most talented people in the world, and I have no doubt that your skills and experience will be highly sought after as you pursue your next chapters. How we move forward To the team that is staying, I know this is a difficult day. We’re saying goodbye to colleagues and friends you've been in the trenches with. But here’s what I want you to know as we move forward together: Over the past 13 years, we have weathered four crypto winters, gone public, and built the most trusted platform in our industry. We’ve made it this far by making hard decisions and by always staying focused on our mission. This time will be no different – nothing has changed about the long term outlook of our company or industry. And most importantly, our mission has never been more important for the world. Increasing economic freedom requires a new financial system, and we’re building it. The Coinbase that emerges from this will be more capable than ever to achieve our mission. Brian

The non-English tax is real. Sutton's Bitter Lesson, translated across languages and normalized to OpenAI English token count: Hindi: OpenAI 1.37×, Anthropic 3.24× Arabic: OpenAI 1.31×, Anthropic 2.86× Chinese: OpenAI 1.15×, Anthropic 1.71× Claude’s tokenizer charges a much higher linguistic tax.

大模型厂商交替领先，真是各领风骚三五月：去年四季度是gemini、今年一季度是cluade、现在感觉轮到GPT5.5了。核心还是大家都在积极进取迭代，只很多时候领先源于对手的松懈。去年在算力投入上非常节制的Authropic最近应该是感受到了算力短缺的痛。 梳理下时间线 1、去年四季度： Google Gemini 3 系列（尤其是25年11月左右的Gemini 3 Pro/Deep Think）强势登顶，很多基准（如Humanity’s Last Exam、推理、多模态）领先，引发OpenAI“Code Red”。它在多模态、长上下文和搜索集成上特别亮眼，一度被视为转折点。 2、今年一季度： 最耀眼的自然是Anthropic Claude 4.6（Opus/Sonnet，2月发布）强势反超，尤其在编码（SWE-Bench）、长上下文推理、agentic任务和实际生产力上领先。 3、当下2026年4月： OpenAI GPT-5.5正处于发布窗口，刚 在ChatGPT和Codex上即将全面上线。它强调更好的上下文理解、编码、computer use和agent能力，试图追赶和超越。 大模型领域现在并没有绝对的“唯一王者”，而是各有专长： 1）Claude：主攻编码、长任务、可靠推理往往领先，Agent上迭代非常多。 2）Gemini：多模态、速度、性价比、超长上下文强（3.1 Pro Preview仍很能打）。 3）GPT：通用agent、工具调用、实时应用和生态集成突出，新版在上下文和特定专业任务上提升明显。算力囤积最积极 4）grok：有X这个实时内容平台提供源源不断的训练数据，但近期受制于团队动荡。看跟cursor的合作、以及囤积的大量算力，后面会不会进一步跟上。 当然还有meta最新的Muse Spark，AI团队的最新之作。 更不用说国内豆包、千问、混元、kimi也是各有特色，杀疯了。 这就是当下大模型领域的现状：快速迭代、轮流坐庄。暂时还没有一家能长期领先甚至垄断。当然竞争对用户是好事——模型越来越强、价格/速度也优化。 2月中在《资本开支的战争》推文里有聊过：”往下游看，越往用户端竞争越激烈，当然也是未来AI决胜的关键所在。 可以说大模型、在面向B端或者C端的Agent或者应用才是AI的王冠，但这一层面短期其实很难看出谁会成为最后真正的赢家，再很多时候都是交替领先”。现在看确实如此 GPT-5.5出来后估计又要新一轮刷榜了，下一个出来交替领先的会是谁？