Evidence receipt / recommendation
Published · transcript-backedVarun Mohan: recommendation
20 Apr 2025 Lenny's Podcast Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO)
“If there's a very large directory, don't go out and make it refactor the entire directory because then if it's wrong, it's going to basically it destroy 20 files. And I think from there, one of the key pieces I think that comes from the users that use the product is they sort of learn what the hills and valleys of the product are.”
Source trail
Everything needed to verify it.
- Speaker
- Varun Mohan
- Attribution
- Verified speaker
- Claim type
- recommendation
- Recorded
- 20 Apr 2025
- Publisher
- Lenny's Podcast
Transcript context
…Yeah. Okay, cool. So we'll let it run and we'll talk. Let me ask you this question that I've been asking everyone that comes on that is building a product that helps engineers build products and product managers build products and designers. Say you could sit next to every single new user that opens up Windsurf and whisper a couple tips in their ear to help them be successful with the product. What would be a couple tips you'd share? Tip number one is just be a little bit patient and both patient and explicit. When you ask the application to go out and make some changes, it could actually go out and make many irrelevant changes. One of the things that I think prevents this the most is just be really, really explicit or as explicit as possible. And one of the things I ask people to do is in the beginning, start by making smaller changes. If there's a very large directory, don't go out and make it refactor the entire directory because then if it's wrong, it's going to basically it destroy 20 files. And I think from there, one of the key pieces I think that comes from the users that use the product is they sort of learn what the hills and valleys of the product are. The analogy I like to give are kind of similar to autocomplete. When you use a product like autocomplete, you would think a product that is suggesting things but only getting accepted 30% of the time would be really, really annoying. But the reason why it's not very annoying is actually because you've actually learned that, hey, 70% of the time, I don't need to accept this. And the times that I do, I know to get value from it. And you also know beforehand if a sort of command that you write is very complex, you just expect, "Hey, the autocomplete is not going to work for it." So I think it's almost like a, understand what the hills and valleys of the product are. The crazy thing is, every three months that kind of gets changed and reevaluated. It almost becomes the case that it becomes materially better than it was in the past. So I think maybe patience and being explicit are maybe the two important key pieces I would tell users. And I think something that was kind of between the lines there is get a gut feeling of what the model is capable of, like how specific to be versus how abstract it can be. And there's kind of this gut feeling you start to build over time.…
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