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I wouldn't believe it if you told me something like this would be possible just a few months ago. If you're also building an AI-powered GTM Ops team like we are, reach out, would love to exchange notes (and tell you about how we build with @DevinAI)! 🤩

The funnest part: I dig into our data locally in the terminal, then spin up Cloud Agents from those same insights to build the apps, reports, and automations our GTM motion actually needs.

I truly cannot remember (nor want to) recall life on our GTM Operations team @cognition before Devin for Terminal. 🧵

# 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.

@cognition 💙

Devin!!! In!!! Windsurf!!!!!

my biggest productivity problem with @DevinAI is that I can't stop watching it work. seeing it troubleshoot bugs and argue with itself during PR reviews is genuinely mesmerizing. I should be doing other things while it cooks but here I am just… spectating lol

Brazil feeds a billion people. It holds 12% of the world’s freshwater. It produces 87% of its electricity from renewables at half the cost of American power. It holds 94% of global niobium, the second-largest reserves of rare earths, and the second-largest reserves of graphite. Its stock market trades at 9.25x forward earnings. The S&P 500 trades at 21x. An American investor pays more than twice as much per dollar of expected earnings for exposure to the US economy than for the country that holds the minerals, the water, the food, and the energy that the 21st century runs on. Someone explain to me how that math works. Read why I’m bullish on Brazil below 👇

Cognition is live in Japan! 🇯🇵 We launched today with Tokyo Merge - a standing room only event with industry leaders across the country. We’re hiring, partnering, and building in Japan. If you’re building here, we’d love to work with you! cognition.ai/blog/launching…

We’re releasing SWE-1.6, our best model in both intelligence & model UX. SWE-1.6 matches our Preview model on SWE-Bench Pro while dramatically improving on various behavioral axes. It’s available today in Windsurf in two modes: free tier (200 tok/s) and fast tier (950 tok/s).

Devin Review caught the axios supply chain attack for multiple Cognition customers before the attack was publicly known. These attacks will be 10x more frequent in the age of AI; it is critical that repo maintainers start using AI for defense as well. (showing one example below where Devin Review caught the attack within an hour of its release - text minorly edited for anonymization)

Traditional coding benchmarks do not reflect how software is actually built and maintained. That's why we built a new benchmark, APEX-SWE, in partnership with @cognition. It measures whether AI models can perform complex, real-world software engineering work to ship systems that work and debug them when they don't. @OpenAI GPT 5.3 Codex (High) tops the leaderboard at 41.5% on Pass@1.

Regardless - still disruptive + making me want to consider a new browser. 1) What are better alternatives to Arc? 2) Am I the only one struggling/is @browsercompany working to keep the tool operational?

Have been a @browsercompany Arc user through and through since launch day. Yet - been struggling so much with the constant blackouts/full browser quitting in the middle of work/a call. Thankfully I always have a @DevinAI session running and he has his own machine. :)

Devin managing Devins!!!!!

Interesting stat - our enterprise customers have already done more Devin sessions (and more merged Devin PRs) in 2026 than in all of 2025. Not bad for 2-ish months into the year!

We are sharing an early preview of our ongoing SWE-1.6 training run. It significantly improves upon SWE-1.5 while being post-trained on the same pre-trained model - and it runs equally as fast at 950 tok/s. On SWE-Bench Pro it exceeds top open-source models. The preview model still exhibits some undesirable behaviors like overthinking and excessive self-verification, which we aim to improve. We are rolling out early access to a small subset of users in Windsurf.

Proud to have worked for Josh and Julio and to count on them as mentors who continue to shape my life. Powerful reflection from one legend about another. 👏