HN user
It was all distillation up to this point anyway. And I agree with what Suhail said on twitter: "Make the margins next to zero for all these AI models. It was trained on humanity's data, it should be gift to ourselves. Doing so will save us from a few in control of our species."
The point isn't that people will vibecode their own SaaS. It could mean the end of extremely high-margin software businesses, as building cheaper, better alternatives becomes easier. You'll see more people with deep domain expertise trying their hand at startups. For example, Atlassian employees with Jira expertise leaving to build niche alternatives.
Which large companies seem best at trying to avoid this? Apple, Airbnb, Box?
So many years reading his newsletter, and forever grateful for Om. He replied to a cold email a long time ago with very specific, helpful advice on a project I was working on. What a legend!
Good point, that's probably more interesting for the home-page. I will play with it. Thanks!
I wonder if package indexes become more important in our new day-to-days with LLMs, not less.
We might be browsing less, but the models need a source of truth for package metadata, etc.
I was surprised today by how much better GLM-5.2 was than GPT-5.5 at aesthetic/UI work. I'll keep my Claude/Codex setup via Conductor for now, but this model got me to set up OpenCode, download their desktop app and do most of my work there today.
The interesting part here is not whether Anthropic is right on safety, but that safety gives them a moral vocab for bold policy changes and platform power.
Yeah, this is similar to finding 10 customers who love your software rather than 1,000 who only kinda like it. And if you do, it's probably because you've found a use case that is urgent enough for one specific kind of user.
What kinds of graph shapes or query patterns do you feel are the worst case for object storage?
Humm maybe. But a plain model sampling outputs obviously isn't doing discovery in the AlphaGo sense. But once you put the model in a loop with tests, feedback, tools or even a human picking the good result, it starts to get much closer to the process he's describing.