Building a magical AI code editor, Varun Mohan
Skip the fluff. Hear the best bits.
Just 5 minutes. All value, no filler.
📓 Key Takeaways
📘 The company rebuilds its own product every 6-12 months. Varun wants each iteration to make the last look silly. Progress must be aggressive and constant. They don't wait to be disrupted - they disrupt themselves.
📘 Windsorf’s strategy is to aggressively replace their own offerings before someone else does. Their new IDE replaced their plugins inside Visual Studio Code, not because users complained, but because they hit a ceiling. Acceptance rate of AI-generated suggestions tripled after switching to the custom IDE.
📘 They began as a GPU infrastructure company, made money, and had $28 million raised - then killed it. As generative AI took over, the team bet everything on a new direction. Pivot decisions happen overnight. Focus matters more than revenue.
📘 Forget just working smart. The best people take initiative. They don’t wait to be told what to do. The most underrated trait for future engineers: agency. Especially with AI lowering the barrier to build, agency becomes the new moat.
📘 They hire only when the team is underwater. Their metaphor: the company is dehydrated, and every hire is just enough water to keep going. It keeps things lean, reduces politics, and forces ruthless prioritisation.
📘 AI will write 90% of code. But engineering isn't just typing. Understanding systems, debugging, designing - still matter. AI increases ROI on tech, so companies will hire more engineers, not fewer. Especially ones who understand how to build well with AI.
📘 They invested in enterprise sales early - now over 80 go-to-market people. Understanding huge codebases (100M+ lines), handling security and compliance (e.g. FedRAMP), and deploying private infrastructure make Windsorf viable for massive clients like Dell and JPMorgan.
📘 They run two roadmaps. One for what users want. One for bets users aren't asking for yet. Incrementalism is not enough. They're planning 6-9 months out to cannibalise their own products again.
📘 Windsorf lets you upload a crude sketch and say, “Build Airbnb for dogs.” It does it. PMs, salespeople, and marketers at the company now build full tools themselves. Even internally, this saved them over $500k in software costs.
📘 You won’t understand the upside until you use these tools. Engineers, PMs, and anyone in tech should be playing with Windsorf or similar every day. The next 12 months are the biggest alpha opportunity in years.
💬 Top Quotes
A lot of the bets we're making inside the company are for things that are not, you know, three, four weeks away. We should be cannibalizing the existing state of our product every six to 12 months. Every six to 12 months it should make our existing product look silly. It should almost make the form factor of existing product look dumb
The reason why we were able to build it for free was because of our infrastructure background. We were able to optimize these workloads a ton. And I guess very quickly after that, some large businesses also wanted to work with us. And we built out this kind of enterprise motion to work with these large companies like Dell, JP Morgan Chase
I think what engineering kind of goes to is actually what you wanted engineers to do in the first place, which is what are the most important business problems that we do need to solve? What are the most important capabilities that we need our application or product to have and actually going and prioritizing those and actually going and making the right technical decisions to go out and doing it
One of the things that we do believe, though, for software, if you want to do great things, it's not possible to just say, hey, I want to get it done in one month. Because you have to think about it from this perspective, if a software project could get built in two to three weeks, what does that really mean about the true complexity and differentiation of what you built?
If we are forced to make a decision constantly on like, we cannot do X, it's very clarifying. It's very clarifying because our engineering interview process is also like extremely low acceptance rate. So it's not very easy for us to very quickly spin up people and have them join the company really, really quickly either
One of the worst things is like, if someone comes here and doesn't like using these tools, like we believe they're massive productivity improvements. We do bring people into the company like on-site so we can actually see how they think through problems on a whiteboard and all these other pieces. So we do want to see how they think on their feet
If AI is writing over 90% of the code that doesn't mean engineers are 10x more productive. Engineers spend more time than just writing code — they review code, test code, debug code, design code, deploy code, navigate code. There's probably like a lot of different things that engineers do
