Yes

m1 has perfect performance. Screen is the issue. Having all modern devices with 90-120Hz and good brightness, Im feeling headache switching on air on regular basis.

I've known and used SQL for 25 years; over the last year I haven’t written a single query by hand - AI is very good at it. I use SQL editors only to quickly see what I have there and to check the AI-generated query.

Must be nice to only work with solid, well-documented data models.

That sounds like snark, I guess, but I’m actually jealous. AI would choke on the last few “DWs” I’ve used.

Frontend, Backend, Devops Full Stack Engineer with 25+ years of experience in complex Frontend components, Backend, and DevOps. Open Source Creator of libraries with [~10k stars ](https://github.com/istarkov). Former maintainer of Recompose. Architected and built end-to-end systems from scratch, scaling platforms to 1 million+ users and 20M daily requests. Master's degree in Mathematics.

https://github.com/istarkov istarkov@gmail.com

Remote.

"Lampreys /ˈlæmpreɪz/ (sometimes inaccurately called lamprey eels) are a group of jawless fish"

I'm not sure what you mean? Jawless fish are pretty far from most fish but that's not much of a reason to say they're not fish.

GPT-5 says that now its not. So while lampreys are technically fish under traditional definitions, modern evolutionary science places them as one of the most primitive branches of vertebrates—not part of the “true” jawed fish group.

Only a fool would trust the output of GPT-5 for, well, any purpose.

I don't know where it got that idea because I only see a few people using the term "true fish" and they're using the normal definition of vertebrates. If you want to be extra restrictive then there's multiple options. If you really want to exclude tetrapods you might use rayed fish. And there's also bony fish if you think sharks aren't quite right having only cartilage. Who uses jawed fish in particular?

Gpt makes things up. It really shouldn't be used in technical discussions except for a catalyst to find something to look up.

An article that's basically an ad for Datadog: Pay us a ton of money - it’s still cheaper in the long run.

Any real life tasks examples?

What do you consider a real life task, if Graph reachability, Graph coloring nor finding Connected components count? They all have many straightforward applications.

Cloudflare results with worker as a reverse proxy can be much better.

But won't it add an additional hop hence additional latency to every single request ?

Nah, because the Cloudflare Workers run at closest edge location and are real fast.

The real solution with Cloudflare is to use their Load Balancing (https://developers.cloudflare.com/load-balancing) which is a paid feature.

Hi! In your benchmark, do you use a fixed number of iterations to stop the test, or do you apply a statistical criterion, such as the Student's t-test, to determine when to stop?

i didn’t want it to be complex so it uses simple time budget + at least x amount of samples, both and more can be configured with lower level api.

in practice i haven’t found any js function that gets faster after mitata’s time budget (excluding cpu clock speed increasing because of continuous workload)

another problem is garbage collection can cause long pauses that cause big jumps for some runs, thus causing loop to continue searching for best result longer than necessary

Why Hatchet might be better than Windmill: Windmill uses the same approach in PostgreSQL, very fast and has an incredibly good UI.