4/14/2026 at 9:19:24 PM
Inventing a new thing "for agents" always feels counter-productive. Your new thing isn't in the training data, so you have to teach it how to use your thing. Why not use tech that's already in the training data? Agents know Python and Django. Or, better (because the performance, maintainability, and deployment story are much nicer with no extra work, since agents write the code), agents know Go.The very nature of LLMs means you can't invent a thing for current agents to use that they'll be better at using than the things they already know how to use from their immense training data. You can give them skills, sure, and that's useful, but it's still not their native tongue.
To make a thing that's really for agents, you need to have made a popular thing for humans ten years ago, so there's a shitload of code and documentation for them to train on.
by SwellJoe
4/14/2026 at 9:46:51 PM
this was true a year ago, but if you give an agent a new spec to follow (e.g. a .md file), it will follow it.we have a custom .yaml spec for data pipelines in our product and the agent follows it as well as anything in the training data.
while I agree you don't need to build a new thing "for agents", you can get them to understand new things, that are not in the training data, very easily.
by mritchie712
4/14/2026 at 10:17:56 PM
Just because they can doesn't mean inventing a new framework "for agents" is going to be superior to letting agents use what's in their training data. I suspect it'll be worse, but the time/resources needed to prove that is beyond what I'd be willing to invest.What makes something like this "for agents", anyway? It's opinionated...a human's opinions, I assume, since agents don't want anything and thus can't have opinions. But, many existing tools are opinionated. Types are good for agents, because it keeps them honest, but many existing things in this space have types. Python is good for agents, because there's a shitload of Python code and documentation in their training data, but many existing things are built with Python (and TypeScript, Go, and Rust are also typed languages and well-represented in the training data).
I dunno. I think a lot of folks are sitting around with an agent thinking, what can I build? And, a lot of things "for agents" are being built, as a result. I think most of them don't need to be built and don't improve software development with agents. They often just chew up context and cache with extra arbitrary rules the agent needs to follow without delivering improvements.
by SwellJoe