fang

We do much more than sell training-data! And we are much much farther ahead than the numbers here show Happy to see us recognized. Towards being the most profitable neolab! More soon

update: i've joined @fleet_ai as a member of technical staff. absolutely generational team + opportunity. excited to model the world 💃

@kylekane edits + builds are scoped per block so none of the other blocks on the canvas are affected during edits

@sofangtastic been using codex and cursor in my 4am window to ship real apps. maintenease, leaselineage, a handful of others. this would slot right into that workflow. how does the canvas handle state when the agent is mid-build?

i built an infinite canvas where your agent builds & publishes live web apps in real time works real-time with any coding agent that can add an mcp (codex, claude code, cursor, etc) great timing to ship this the day after OpenAI announced Codex Sites :D demo:

@lilfuwa yezzir

@sofangtastic time to make a vision board

@akhil_kestur it rewrites in place! each new publish of a block updates a new version of just that block at the same url

@sofangtastic does each canvas branch deploy to its own url, or does the agent rewrite in place? still figuring out how state should work across branches.

@ship_temp_md exactly! keep everything in one place

@sofangtastic infinite canvas is a good home for agent-built apps. the artifact and the conversation stay in the same room.

@LocolSynth youtu.be/4c8O2n1Gfto?si…

@sofangtastic I love this song choice and I love the little dance you’re doing while you’re waiting for it to load 😂

@olsenbdnr this would have been very helpful for the hackathon projects we did together

@sofangtastic Sick!

@mari_glyph first thing on tisane is me putting down the journey of us coming up with the logo tgh

@sofangtastic sick!!!!!!!!! so proud of you! when's the chatblocks <> tisane collab 😫

@kushbhuwalka api keys are in beta -- what is not available through mcp that you'd want in the api?

@sofangtastic do u have api access to this at all?

@kushbhuwalka would love to see ai employees connected to this

@sofangtastic wait this is such a great way to prototype!

you can try out Chatblocks right now! pretty generous free limits -- dm me if you need more lots more coming (data connections, custom domains, mobile support, checkout) chatblocks.ai

@MichaelElabd PEAK

I am leaving the Foundational Research team at DeepMind! I just wanted to take the time to reflect on this truly amazing journey. It was such an intense and fulling ride that I will always cherish. Two efforts shaped me in particular: the reasoning work and building the continual learning infrastructure for robotics. They taught me what it takes to turn ambitious ideas into real systems. Here are some of my biggest takeways: 1. Iteration speed, iteration speed, iteration speed: the teams that win arent neccessarily the smartest but the ones able to execute on a thousand ideas in the time their competitors excute on five. This became way more obvious when we were working on reasoning for humanoids where the iteration contains hardware in the loop. You have to really deeply think about what it takes to test your hypothesis and how to greatly simplify the iteration loop to move faster. 2. Building scalable infrastructure from day 1: Researchers sometimes think that moving fast means building unscalable infrastructure. My time at DeepMind taught me that there is always one more experiment that requires refactoring the entire repo, as those come up, we should figure out how to better build the stack from the ground up to support more and more wacky experiments. 3. Having fun is probably the most important thing at work: When you truly enjoy your colleagues’ company and you are motivated by the success of the larger team, the late nights become memorable, not exhausting. I never truly understood this until the 1am nights at work all huddled near one of our humanoids trying to figure out why its behaving this way. I’m especially gratefJ to my mentors @sippeyxp , Jie Tan, @Kanishka_Rao, and @carolina_parada for constantly finding harder challenges for me and pushing me to grow. Peter Pastor, @keerthanpg, and Stefani Karp thank you for the late-night hacking sessions and the PEAK dinners. Those are some of my most treasured memories! @claudiofantacci, Alex Lee, @Sumeet_Robotics, and Ken Caluwaerts thank you for teaching me how to build scalable infrastructure, from building the new inference stack to scaling experiments. @Stacormed, @xiao_ted, @ColinearDevin, and Giulia Vezzani I learned so much from you. Thank you for entertaining all my hypotheses (especially the weird ones) and helping me learn through them. I can go on and on.. I just can’t thank each one of you enough. Truly thankful for the time we spent together! Will share more soon 👀

@neilkale lessgoo cmu represent

I've left Scale AI after 9 months of agent monitoring / AI safety work. The world needs open and trustworthy AI systems more than ever before - built BY and FOR users. I've joined a cracked team of researchers and engineers pushing the frontier here! More to come... 🔜

@QuantumArjun congrats!!! excited to see where ur vision takes you

Very bittersweet, but I'm leaving Apple. Anyone who knows me knows how much I admire Apple's story and ethos. The iPhone captured my imagination as a kid, and never let go. And getting to spend the early innings of my career here, working on brand new interfaces on Vision Pro, has been a gift I'll spend a long time trying to repay ❤️ A few things I’ll never forget: (1) Design around the magic moment: Building a good product is really about finding the one moment that does the convincing and building everything else around it. You'll know you've found it when someone smiles without meaning to. I'll never forget the first time a butterfly landed on my finger inside Vision Pro, and my body believed it before my brain did. (2) It takes research to will products into existence: Most people treat research and product like a handoff, where researchers figure out what's possible and the product team figures out what to do with it. The best work happens when both sides are in the same room arguing about the same thing. You don't know what the research is for until someone shapes how a person uses it, and you don't know what to shape until the research tells you what's possible. (3) The best products are arguments, not compromises. Every product is the output of thousands of decisions, and at most companies, each one gets averaged. The result is defensible in every meeting and exciting in none. Great products feel like someone meant them. The work isn't making good decisions, it's protecting the ones that matter from being negotiated into mush. Thank you to everyone who taught me, pushed me, and trusted me with hard problems. You know who you are (and by that I mean more of you should be on X haha) We're at a real shift in how products work, and in the interfaces we'll use to build and interact with them. These shifts only come around every couple of decades, and I couldn't imagine a more exciting time to be a builder. Excited to share what's next soon!!

@rronak_ wait until ppl see what's coming next 👀

I’ve left Google DeepMind. The last two years have been an incredible whirlwind. A couple years ago, I joined a small startup called Codeium. There, I got to ship Windsurf, train SWE-1 (a frontier agentic coding model), go to DeepMind in the $2.4B acquisition. Now, I decided to leave the acquisition money and DeepMind. I’m grateful to the mentors, teammates, and friends I worked with along the way. At Windsurf, thanks to @_mohansolo and Douglas Chen, I got to see what a fast moving startup that ships relentlessly and builds for the future looks like. I learned from @thenickmoy how excellent research leadership can drive outsized innovation. At DeepMind, I got to push the frontier of agentic coding, be part of the amazing team that shipped Antigravity and contributed to Gemini 3. DeepMind is a rare place: deeply curious people, exceptional research taste, and access to enormous compute and Google-scale infrastructure. A few things that I learned: 1. Finding the right hill to climb. Now more than ever, there are a multitude of directions to push the frontier in AI research. It’s easy to optimize for the wrong benchmark or capability. You should step back regularly to question if you are climbing the right hill, and adjust course often. 2. The secret to being a fast-moving team. Moving quickly is not just about working hard and long hours. It requires making concrete bets about where the world will be in 6 months, aligning around them, and cutting everything else. This was our journey from the Codeium Extension → Windsurf IDE → SWE-1 → Antigravity → Antigravity CLI 3. Silicon Valley is small. Since the split of Windsurf to DeepMind and Cognition, many of my colleagues have gone to other exciting places - Thinking Machines, OpenAI, xAI, Cursor, fast-moving startups, or started their own companies. I’m grateful to have worked with so many talented, hungry people whose stories are not yet finished. So what’s next? We are living in one of the most exciting and powerful times in human history. Just like we transformed software engineering, soon every industry, every unit of work will be radically transformed, democratized, accelerated. With this comes new challenges, and new doors of frontier research to be opened. More soon.

working with ronak is the real continous learning if ur interested in composer 2.5 / swe-1.6 keep an eye on what he does next

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