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Walden
@walden_yan
I sometimes code @cognition
691 Following    12.5K Followers
Mobile development has long been a “secondary” project due to the amount of investment it takes to maintain No longer. Development and actual live testing is possible via massively parallel cloud agents
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Devin can now build and run Android apps. We added Android Virtual Device (AVD) support for Devin’s machine, which means Devin can now autonomously build, launch, and test Android apps.
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You should work with people who are better than you conceive possible. Not only Scott, but several of the team members at Cognition have expanded my understanding of the skill ceiling
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Scott Wu is the co-founder of Cognition AI, one of the fastest-growing companies in history. He’s also the greatest competitive programmer the US has ever produced. You may have seen him doing impossible card tricks and mental math. You’ve never seen him asked about weed, Michael Jordan, cancer, and human consciousness over a punnet of strawberries. That is what Colossus editor-in-chief Jeremy Stern did on a recent visit to San Francisco. For those less familiar with @ScottWu46: In 2nd grade, he entered a math competition for 7th graders, lost, and was so furious he still fumes about it 20 years later. The next year he entered the 9th-grade division as a 3rd-grader and got a perfect score. Then he won first place at the US national middle-school math competition and three straight gold medals at the International Olympiad in Informatics, where he became the greatest American gold-medalist and coach in history. Most of the people running the biggest AI companies met as teenagers, competing for their countries on international math and science teams. OpenAI’s Greg Brockman, Anthropic’s Dario Amodei, Meta’s Alexandr Wang, to name just a few. Most agree that the von Neumann among them was Scott Wu. In November 2023, a few weeks after his mother died of lung cancer, on the day Sam Altman was fired from OpenAI, Wu founded his own AI company: Cognition. He was 26 and saw earlier than almost anyone that AI would converge on agents that work in the background, 24/7, like coworkers. He shipped Cognition’s AI software engineer Devin in March 2024. It worked poorly, and he took intense public criticism for it. Now, in its first 18 months of service, Devin has generated $445 million of revenue run rate and usage has doubled every eight weeks. The US Army, Goldman Sachs, and Mercedes-Benz are all customers. Cognition is raising at a valuation around $25 billion. @JeremySternLA sat down with Wu, the emperor of the nerds, to ask the questions we’d all ask one of the smartest people in America—building the most consequential technology of our generation—if we ever got the chance. As well as MJ and weed, they talk about the cluster of competitive math prodigies behind so much of AI, what makes us human when AGI arrives, and why Wu believes he was put on this earth to teach AI how to code. Read the piece below.
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At some point as we grew, we set up tables, chairs, and a heater in the garage. So technically we would work out of a garage, though quite far from the Google/Apple experience I imagine (dinners in the house were also quite special)
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the inside story of the legendary Cog House. i believe there have not been any public photos of this place until now (bc we were explicitly not allowed to lol) as an advisor its been awe inspiring to see this company grow into a well oiled product and gtm machine that will be worth $100B by EOY (imo)
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@mattbergland @sandeepDshah Devin Review is criminally underrated. One of my favorite modern “AI dev” products.
@DevinAI has completely replaced Claude Code for me this week
Cool to see failure modes of different coding agents in new report from @greptile - seems like Devin is better than humans in almost all categories!
Agents finding bugs in agents and tagging another agent to fix those agents Welcome to the singularity
now, your agent can fix itself. introducing raindrop triage. an agent for finding and investigating agent issues.
This post is completely outdated FWIW. Devin is really good now. One of my favorite tools. What's good about it: 1. UX is really great and super polished 2. Love how it gives me a video and visual proof of work 3. It actually works now Some of it is models are better but the UX/harness is also better. I suspect this blog post would not be written today.
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Great deepdive with @3blue1brown into the day-to-day of working at Cog: - mental math & rocket launches - proofreading @Mokshit06's college essays - not writing code anymore - injecting taste - hiring the best people Come work with us!
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In 2024, a high schooler cold DM'd us asking if he could work at Cognition before college. We said yes. We ended up helping him with his college essays and his US visa. If you've used DeepWiki or Devin, you've seen @Mokshit06's work. @3blue1brown sat down with us to hear the whole story.
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realization from watching this: People in SF brag about how they vibe-coded an app 10x faster. And its still bug-ridden Bro Mercedes is out here rewriting actual gnarly legacy production code. 8 months -> 8 days Most of yall gotta step up your coding agents game
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Cognition is partnering with @MercedesBenz to accelerate software engineering across their global engineering teams, representing one of the most extensive deployments of AI software engineering in the automotive industry to date. @ScottWu46 sat down with Katrin Lehmann, Mercedes-Benz CIO, to discuss the work:
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"Man I wish I could close my laptop and the agent would keep working" Cloud handoff has never been easier (@MattSchrage' first ship here, and certainly not his last - welcome to the team)
The terminal hasn’t changed much since the 1970s. What you do with it has. Introducing Devin for Terminal: everything we learned building Devin, now as a local agent, available right in your shell. And when your work outgrows your laptop, hand it off to the cloud.
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I find myself really reaching for 5.5 nowadays. Seems like a model built for cloud. Congrats @OpenAI
GPT-5.5 is now available in Devin as an Agent Preview! GPT-5.5 has set a new bar for what's possible with Devin. It runs longer and more autonomously than any GPT model we've tested, surfacing bugs no other model can catch, and investigating and fixing production issues end-to-end.
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# The Path Forward for AI Startups A lot of founders are messaging each other after the SpaceXAI <> Cursor “IPO-deferred acquisition”. Common discussion topic: what is the future for independent startups? Must ~everyone ultimately be acquired by a frontier lab or go extinct? The data from our direct experience @cognition suggests the opposite. The more startups in a category that defect from independent competition by selling to a lab, the stronger the remaining ones become. We experienced this firsthand last year with Windsurf. When the founders went to Google and we acquired the remaining company, it dramatically accelerated our product roadmap and GTM. Now, cloud agents are ready for prime time, and our usage has exploded. (We’re in the fastest rate of usage growth in Cognition’s history - almost 50% month-over-month growth in Devin enterprise.) We already see the next round of acceleration with yesterday’s news, from prospects and customers to candidate inbound. In just about every category, there’s a clear market for a winning independent offering that’s not tied to models from any one lab. Especially in a space as dynamic as software engineering, where customers value model flexibility as the rankings from different providers are constantly changing. For startups to seize that independence opportunity, here are the lessons we’ve learned so far: 1. DIFFERENTIATION You need to have extremely clear differentiation vs. what’s already offered by the labs. Cursor had stiff competition from Claude Code in self-serve, in part because one tool was substitutable for the other, which presented a challenge. Our approach has been to differentiate heavily for enterprises, which is the largest market for software engineering. Specifically: 1. We invest as much in forward deployed engineering and AI enablement as we do in core R&D. Our customers treat us as a change management partner, not just an AI software engineering platform. We run 1000-person workshops all around the world to help train developers inside companies on frontier AI adoption. We target specific use cases and outcomes in addition to providing developer tooling. 2. We focus on accelerating the *entire software development lifecycle* at large company scale, not just the writing of code. Devins now spin up automatically for everything from ticket scoping to DeepWiki codebase indexing to security vulnerability remediation and application monitoring alert response. 3. We eat the pain of deployment complexity to work well in the largest and most complex environments imaginable. Cognition can run inside a customer’s virtual private cloud, has a permissioning and team collaboration model that can scale to 100,000+ developers inside one company, runs as well for COBOL mainframes as it does for modern Python. From day 1 each Devin ran in a microVM on its own machine, vs running locally as a CLI tool, which allows arbitrary horizontal scaling and is a better fit for event-driven automation. Of course, one element of startup differentiation will always be model independence. This is particularly powerful in large enterprises, who value supplier continuity and the ability to centralize tooling without taking on the business risk that they committed to the wrong foundation model. And useful for individual developers, who always want to try the latest models. (If you haven’t yet tried the Windsurf 2.0 release which came out last week, it’s a good day to give it a shot!) I expect the labs will catch up on some of these fronts at some point. But at that point, we’ll have already made the next leap in differentiation, because… 2. FOCUS You won’t outcompete the labs in everything, but you can outcompete the labs in *your* thing. Every application domain has fractal complexity at the edges. Lean in to what makes your domain special and offer things no one else can. Does it make sense for a lab to devote training resources to a specialized code review model? Probably not - they’re working on AGI. But for the 3-6 month window where the latest frontier models don’t solve that use case at acceptable performance, cost, or latency, do it yourself and build a better product experience than would otherwise be possible. Rinse and repeat as the frontier of what’s possible via specialization continues to evolve. 3. VELOCITY One of our values at Cognition is: “Every second counts.” Maniacal urgency helps in every startup, but it counts extra in today’s accelerated AI times where advantages compound faster than before. With sufficient focus, you can out-accelerate the AI labs on any one specific feature or workflow. Do this consistently to stretch the overhang of what’s enabled by each new generations of models, and you can maintain your edge on a differentiated product experience. - In many ways the SpaceXAI <> Cursor news is a win for everyone. SpaceX gets a new research team and the chance to become competitive in coding. Cursor gets a meaningful exit and the opportunity to accelerate their research roadmap with much more compute. And the whole ecosystem benefits from increased competitiveness among the foundation model labs. Congrats to the teams on the outcome.
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Crazy how much changes in a year
I see a lot of people make the same mistakes building agents. So we shared a few of the principles we use
A year ago, I'd tell people to not build multi-agents and to focus on context engineering fundamentals Today, many sexy ideas are still impractical, but we've found some setups that actually work
Rivian and Volkswagen Group's joint venture put Devin to work on testing and ticket triage across a software platform that will power up to 30M vehicles. Devin handles autonomous ticket triage in Slack and generates tests on safety-critical propulsion code 10-15x faster than manual authoring, freeing RV Tech's engineers to spend more time on new features.
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Ever wanted your coding agent to keep working after you close your laptop?
Introducing Windsurf 2.0. Manage all your agents from one place and delegate work to the cloud with Devin - so your agents keep shipping even after you close your laptop.
A model that can review your PR in 10 seconds
Today we're releasing SWE-check, a specialized bug detection model we RL-trained with @appliedcompute that matches frontier performance on internal in-distribution evals and makes meaningful progress on out-of-distribution evals, all while running 10x faster.
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That’s just one month People don’t realize Devin is quietly the best cloud agent out there
TIL @cognition usage has ~DOUBLED globally since these 2 launches. people are finding all sorts of creative usecases when u can compose agents together and make them proactive. agent recursion is all you need?
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I see a lot of people make the same mistakes building agents. So we shared a few of the principles we use
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