Ashvin Nair
speaker
533 appearances
1 recordings
1 series
first heard Dec 2025
last heard 30 Dec
Ashvin Nair’s voice in public audio — every appearance, attributed to the second.
Trend
recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Dec 2025 with 1.
Appearances
And I think that's like basically the whole company is just really, you know, full of people who want to, you know, code, even like the co-founders, you know, uh
Like actually uh the co-founders are often some of the best like like high taste testers, which it also kinda gives you a lot of like reassurance that you're gonna ship good stuff.
So yeah.
Well yeah, ironically, uh I feel like I'm actually like a low taste tester in some ways.
Because I don't know, like, you know, I just like write like slow like machine learning code and just like think about um algorithms and stuff all day.
Yeah.
Um I think more broadly, I'm super excited about co-designing the product so that you can actually, you know, not just right now we're getting better and better at like answering user prompts.
Um and I think that's why Compose One is like quite good.
But uh you know, what we're really aiming for is like more like, you know, automate software engineering as a process where you like write code, you go look at Datadog.
Uh look at what's like happening, then come back and like, you know, maybe have some hypotheses about what's better, like re rerun stuff.
I think that's the type of thing that we actually want to make them all do.
And I do think that cursor is kind of like uniquely positioned to do that in the sense of like, you know, if we can kind of if if a lot of what a software engineer does kind of ends up in the product, um, I think we can use that to like get better and better at, you know, not just writing code, but kind of like the whole job.
um the tooling at cursor is actually really good.
I think because you know it's just kind of like a people are just down to like vibe code stuff.
They like do test their own stuff.
Like um so we just have like a lot of good tooling where you can, you know, like have like a SSH session into like um our own like um user environment or something and like you know see if like uh code runs the way that like users got it to run.
Like this kind of
Yeah, quite nice.
I think basically one of the big lessons in ML in general is that you want to be like really close to your data and understand your data well.
And um yeah, I think there's like kind of yeah, again, kind of like uniquely positioned to do that well.
Showing 461–480 of 533 · page 24 of 27
← Previous
Next →