I don’t normally write these things. But this one hits a bit different. Nearly three years ago I told a16z I wanted to spend part time outside the firm helping @drfeifei start and build a frontier model company. And what followed were some of the most remarkable moments of my career. From being at the founding table. To watching the first git commits. Seeing the very early very rough results that hinted at something much greater. Contributing to the open source. Watching the creation of new model architectures that pushed the state of the art in multiple areas. I saw the team spin magic from nothing again and again. And I was very privileged to be within the walls. I’m very proud of what was accomplished, and am so excited for what lies ahead. So congratulations to AMD for entering into an agreement with the leading spatial intelligence frontier lab. And congratulations to the World Labs team on a partner that has the vision, ambition and leadership to be the top AI technology provider globally. Also congratulations to Dr. Su and Dr. Li. Two world class CEOs with a common vision. The both of you working together is unimaginably legendary. Arguably the smartest leaders in tech with the shared goal of building the world's leading AI capabilities. I know you both share an optimistic view of AIs ability to aid humanity. We need far more of that. As everyone knows. I’m World Lab’s biggest fan. And will remain so. Thanks to @drfeifei , @BenMildenhall , @jcjohnss and the entire team for letting me tag along. What a crazy fucking ride. You stood at the frontier, and moved it. And will continue to. Again, many congratulations to everyone involved. The future of AI will be so much brighter with this partnership. I can’t wait to see where it leads. Here’s to new worlds!

Adam Neumann on first principles for founders: ask why until nobody can answer, then ask again. "It's our second WeWork building. We need to do the floor. We only had ninety thousand dollars." "I said, 'How much is the floor?' Everybody's like, 'The floor is between thirty to forty-five thousand.' I said, 'Why?' They said, 'What do you mean why? These are the quotes.'" "I said, 'Can you break down the quotes for me? How many pieces of floor? How many nails? How much glue? How many hours of work per person? How much does each person cost?' No one could answer." "I called the top three guys and said, 'I would like you to earn fifteen percent above the cost. I think that's a fair margin. Do you agree?' All three of them said yes." "Very quickly, that first floor, instead of thirty to forty-five thousand, was twelve thousand." "You can call it first principles. You can call it asking every question. But if you're the entrepreneur, or if you're an employee or a partner, ask why." @AdamNeumann w/ @StevenBartlett

World Labs co-founders Dr. Fei-Fei Li and Justin Johnson on compute as the constraint, and the Slack message that convinced them to go all-in on their Atlas model: Fei-Fei: "I think [we] have total conviction about the scaling law." "I do think the exact architecture choices and data mixtures is where the devil's in the details. I watched Justin and his team going from 'we really don't know how long this is gonna take,' to 'maybe sign of life,' to 'wow, this is gonna work.'" Justin: "We're basically at the beginning, and we're basically limited by compute at this point." "During development, we trained a sequence of models, the first couple rungs of the scaling ladder. Each time we made the model bigger, each time we trained it for longer, each time we put it on more chips, it got significantly better." Fei-Fei: "Here's a little bit of an insider story... There was one day in early summer... Ben and Justin feed [a smaller model] into the viewpoint generation... Remember that famous garden table from the NeRF paper?... Overnight we all saw the Slack from Ben that our camera flew under the table." "That morning, the three of us looked at each other in the eyes and said, 'That's it. We're gonna build this.' We made a decision within five seconds. No one has ever seen this result." @drfeifei @jcjohnss @BenMildenhall @martin_casado

Assistant Benchmark creator David Pawlan says the internet is about to get an agent-to-agent layer: Anish: "It does feel like there's going to be infrastructure and products that exist only for agent-to-agent interactions that doesn't exist today." David: "You have agent emails, you have agent phone numbers. What does the world of service look like when it's no longer human booking to human, and no longer agent booking from human, but it's now agent booking from agent? How does that redefine the entire service industry?" "Internet came first, then came cybersecurity. Agents came first, now comes the security component of these agents. What industry is that going to create?" "There's so much opportunity and so many problems to solve with these agents. I think it is inevitable that we're going to see so many startups popping up trying to figure out all these niche problems to build this new wave of internet and digital connectivity." @DavidPawlan @illscience

Marketplaces earn their money when you browse, not when you buy. An AI assistant that shops for you skips the browsing. Ad revenue vs operating income (2025): - Amazon retail: 2x - DoorDash: 1.9x - Instacart: 2.2x AI assistants don't need to rebuild Amazon's warehouses to hit Amazon's profits. Full piece from @aleximm and @santiago__rdz on who gets paid when AI does the shopping:

Assistant Benchmark creator David Pawlan sits down with a16z's Anish Acharya to unpack the sudden explosion of personal AI agents and what it will take for one to become part of everyday life. David has been testing dozens of assistants across real-world tasks, from managing email and booking travel to handling financial admin. They discuss why the most useful agents may become increasingly invisible, proactively checking you into flights, finding refunds, filing reimbursements, or simply handling the small tasks that pile up across everyday life. They also explore whether the winning interface is an app, text thread, voice, or wearable; how much autonomy consumers will actually give their agents; and what happens when agents start interacting with other agents. From commerce and restaurant reservations to entirely new agent-native services, Anish and David ask what the internet looks like when software starts acting on our behalf. 00:54 Poke, Instinct, Muse: the agent boom 03:41 What Assistant Bench actually tests 09:14 Cost savers beat time savers 14:53 Muse charm as Meta's data play 20:03 Silent agents in group chats 26:01 Proactivity is the real moat 32:21 Assistant vs agent, defined 40:22 Amazon blocks Muse, Shopify opens the door 47:35 The $20/day agent economics YouTube: @DavidPawlan @illscience

World Labs' Dr. Fei-Fei Li on why the 3D world and spatial intelligence are fundamentally different from language models: "Language is fundamentally a purely generated signal. There's no language out there. You don't go out in the nature and there's words written in the sky for you." "Whatever data you feed in, you pretty much can just somehow regurgitate with enough generalizability the same data out, and that's language to language." "But the 3D world is not. There is a 3D world out there that follows laws of physics, that has its own structures due to materials and many other things. And to fundamentally back that information out and be able to represent it and be able to generate it is just fundamentally quite a different problem." "We will be borrowing similar ideas or useful ideas from language and LLMs, but this is fundamentally philosophically, to me, a different problem." @drfeifei

Adam Neumann on why top-down management fails with great talent: "Top to bottom means you think because someone reports in to you, they have to do what you say." "But it's not true. This is not a dictatorship. They have free will." "If you hired someone, they're really talented, they'll go work elsewhere. The more talented they are, the more the top to bottom does not work. They won't be willing to do it. They shouldn't." "Great talent is not willing to be managed like this." "If you're gonna manage these employees and you wanna attract the best talent in the world, remember that power comes from influence, not control." "If you think they need to do what you said because you're their boss, you've already lost, and it's a matter of time till it doesn't work out. If they're okay with it... they're not the right employee for you, and you're not the right boss for them. There's no chance you're getting the best out of them." @AdamNeumann w/ @StevenBartlett

We are excited to announce that World Labs is joining @AMD. The research and technical breakthroughs we have achieved since our founding in 2024 have given us a clear vision for AI’s potential to solve problems in the spatial and physical world. Accelerating the future of spatial and physical intelligence requires scaling our efforts, scaling our reach, and getting closer to the hardware.

Greg Brockman on the next year at OpenAI and what he spends his time thinking about: "The business is a huge area that we're not done yet with really up-leveling every part of execution. But I also think we are moving into a new phase of AI development." "We call this the AGI era. And I think that that is something that you can debate. Is it this model, previous model, next model? It doesn't matter." "The point is that we are in a new phase where safety, security, alignment, really thinking about these things, not just at deployment time, but all the way back at development time, evaluation." "It's objective. This is critical. It must happen. This is core to our mission." "A lot of what I spend my time thinking about is making sure, do we have all the right processes? Are we talking about the right things? Do we have plans that really, at an operational level, at a practical level, lead us to... the kinds of safety guarantees that we view as core to our mission?" "The theme of OpenAI, certainly for the past five years, has been deeper co-design, deeper intertwining across these functions that are maybe on the surface very disparate. All the way from go to market to long-term research to chip design." "The areas that I will focus on will be dictated by the areas that most need that intertwining." @gdb @eriktorenberg

Sam Altman thinks OpenAI should be a platform, not a product company: "What I think most people want is the single interface to their own personal or their company's AGI that can kinda help them with whatever they need, and then the ability with an API to build anything they want on top of it." "That is the platform that we should offer to the world." "I don't think we should go build every product category. I don't think we should go try to compete with all of our customers. I don't think we should try to subsume the entire economy." "I think we should offer this platform and try to have a hundred million new businesses and eight billion people use it in all kinds of new ways." "So one kind of direct interface to the product, one API for people to use however they want. Those eventually come more and more together too, and then it's all about what people do with it, build on top of it." @sama w/ @davidsenra

TypeSafe AI's Diogo Almeida says AGI is extremely doable, yet basic work remains largely unautomated: "I still don't think we're on the path of RSI. I do think that what OpenAI defined as AGI is extremely doable: automating most of the world's economically valuable work." "There's a lot of work out there. A lot of it is very rote and simple... As far as I can tell, the intelligence of that has been available in the models for quite a while now. My chip on my shoulder is: Why is this not available?" "Since RLHF, the AI industry kind of bifurcated into gigantic overpromise, underdeliver... Because humans evaluate how good the models are, it looks really good because they are the judge. But we've been optimizing that judge instead of the automation part. That has been the missing thing." "Are you really telling me that math is solved, or even two years ago, GPQA... is solved, but we still can't handle a drive-through? It's a very hard thing to hold in your head at once. I think a lot of people don't have good answers to that." @CompleteSkeptic

Codex went from near zero to 64% of OpenAI's enterprise output tokens between Aug 2025 and Jun 2026 @DavidGeorge83 on what OpenAI understands about distribution:

TypeSafe AI's Diogo Almeida expects an inverse SaaSpocalypse, and Martin Casado calls it "SaaSpalooza": Ben: "When the coding agents came out, it was the SaaSpocalypse, and all their values dropped through the floor. Then when Jev came out, every SaaS company is like, 'This is the greatest thing ever.'" Diogo: "In the SaaSpocalypse story, the story I feel has panned out really poorly is that software is very cheap and perhaps easy to replicate. I could believe the former. I could not believe the latter, because a lot of the stuff happens beneath the hood." "I think SaaS will be one of the largest winners of the whole AI game. I want to work really, really well with the biggest, most boring... SaaS companies because I think they're the best positioned to know what workflows to automate, what people need. That's their bread and butter." "Software is always a CapEx investment. You spend it ahead of time to make the experience better, and that gets distributed to all that mass of users." "I'm not going to forecast anything about the financial markets. But as far as capabilities go, I think it's going to be like an inverse SaaSpocalypse. I'm so jazzed about it. I should make a name..." Martin: "SaaSpalooza." @CompleteSkeptic @bhorowitz @martin_casado

"Anyone can do nearly anything; but most people aren’t, yet." Who uses AI power tools every week: - OpenAI's own team: 93% - The top 10% of companies: 19% - A typical company: 3% @DavidGeorge83 on why most people haven't been awakened as AI customers yet:

TypeSafe AI's Diogo Almeida's elevator pitch for Jev: "Where the f**k is all the automation?" "AI is so unbelievably smart. Not that I hate on chatbots or coding agents, I love them myself, but it's so useless at all other stuff. It's tragic." "TypeSafe is making AI for software. We want to make AI powerful, not just for humans in the loop, but to actually build real software. Jev, to us, is our first model in this whole space to make [automation] way, way better." "I like Claude Code and Codex. I love the description from Garry Tan and them: It's just-in-time software. It makes software on the fly, and you can program software in natural language, but it has the same expressive power as software." "What I want instead is smart software. Instead of automating software engineering, I want to expand what software itself can do, such that things that should be automatable can then be automatable." "I want to express things like intent. I want to expand the vocabulary of what we can do." "Programming is hyper-specifying valuable things and then infinitely replicating them. It's so freaking cool." @CompleteSkeptic

"Given how amazing AI models are at writing code, they're surprisingly bad at calling tools and carrying out instructions in everyday knowledge work, unless you flip the script around and say, 'write a program that does these tasks', and then they're great at it." AI use for coding, by department: - Engineering: 63% - Design: 59% - Finance: 46% - Legal: 33% @DavidGeorge83 on why agents need to write code:

TypeSafe AI's Diogo Almeida with a16z's Ben Horowitz and Martin Casado on Jev, the model built to live inside software: Diogo's elevator pitch for Jev is a simple question - where is all the automation? AI is unbelievably smart, but outside of chatbots and coding agents, it hardly touches any real work. His diagnosis is the industry built models that generate text for humans to read, and software can't consume that output. Jev reads natural language and returns a choice from a set of options with a confidence level assigned to each, so developers can build programs that reason about intent and make probabilistic decisions rather than relying on human interpretation. TypeSafe's philosophy is "We build prod, not God." 0:50 "Where the f**k is all the automation?" 2:50 Jev vs. Claude Code and Codex 6:55 Jev is a classifier and classifiers are sick 7:40 Chat vs. code: is Jev a slider? 9:00 Diogo: From mathlete to Kaggle to OpenAI 12:20 "We build prod, not God" 15:55 Reliability over demos 16:55 2021 thoughts: RLHF is AGI? 20:45 Optimizing for the wrong use case 21:50 Is the real world too messy to automate? 25:00 Nobody expected the Jev launch 26:35 Three kinds of reliability 28:05 Good at syntax, bad at architecture 30:00 The inverse SaaSpocalypse 33:40 Why coding agents automate so little 36:05 Probabilistic programming returns 38:45 Jev as the UDP-to-TCP layer for AI 40:20 The 5 stages of grief for embedding AI 41:30 Utopia: AI that actually does what you mean YouTube: @CompleteSkeptic @typesafeai @bhorowitz @martin_casado