akurilin

Joined 14 years ago

Karma
818
Submissions
492
Member since
Jan 23
CTO @ Freckle Education (YC), Double Dusk (Speedrun), former Microsoftie

https://www.kuril.in/

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Recent submissions

Comment · 20 days ago
Superwhisper trains their own S1 models for this, you can use either a smaller local version of them or a beefier one in the cloud
Comment · 1 month ago
Really liked that "Go Full Screen" as a modal flow, surprisingly intuitive.
Comment · 1 month ago
Curious which model this can supplant as a clear winner on almost every metric. Sol? Looks like it's not quite there on a couple of benches, but I'm not clear how much they matter in practice.
Comment · 1 month ago
Comment · 2 months ago
Comment · 2 months ago
"few applicants, most pretty good" was true for us as well when hiring Haskell developers at Freckle (https://tech.freckle.com/) - in some ways it was scary: we're away from the herd, the numbers aren't on our side, what if we ever need to hire large volumes of people? Instead of getting 200 JavaScript devs in the pipeline, you would get maybe 10-20 Haskellers. What if the person you're looking for is not in that pool? Intuitively, you assume that more is always better.

In other ways it made filtering through candidates quite simple: half of the people who applied were really good, the other either language astronauts or folks fascinated with the tooling who didn't genuinely want to move fast to produce commercially-viable software, they wanted to tinker. You just needed to figure out which bucket the person was in.

Comment · 3 months ago
Comment · 3 months ago
Comment · 3 months ago
Came here to see how it performs against Luna. Would love to see how they compare on specific types of tasks.
Comment · 3 months ago
I enjoyed this magazine and subscribed to it for a while, but I wish there was a US-centered version of it for those of us on this side of the pond.
Comment · 3 months ago
Really hoping that all of the attention you're bringing to the longitudinal sloppification of codebases makes it back to the labs and creates some pressure to improve that trait of the models. This new benchmark seems promising.

At the same time, I imagine it will be hard for them to prioritize this over improving flashy one-shots of impressive zero-to-one feats that demo so well and attract more customers.

Can we have simonw make "pelican on a bicycle after 1000 requests for iteration" popular?

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