You can write the "prompt tuning" down in AGENTS.md and then you only need to do it once. This is why you need to keep working with different ones to get the feeling what they're good at and how you can steer them closer to your style and preferences without having to reiterate from scratch every time.

I personally have a git submodule built specifically for shared instructions like that, it contains the assumptions and defaults for my specific style of project for 3 different programming languages. When I update it on one project, all my projects benefit.

This way I don't need to tell whatever LLM I'm working with to use modernc.org/sqlite for database connections, for example.

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Razengan 4 days ago | parent [-]

> You can write the "prompt tuning" down in AGENTS.md and then you only need to do it once.

Yeah, I just mean: I know how to "fix" the AI for things that I already know about.

But how would I know if it's wrong or right about the stuff I DON"T know?? I'd have to go Google shit anyway to verify it.

This is me asking ChatGPT 5 about ChatGPT 5: https://i.imgur.com/aT8C3qs.png

Asking about Nintendo Switch 2: https://i.imgur.com/OqmB9jG.png

Imagine if AI was somebody's first stop for asking about those things. They'd be led to believe they weren't out when they in fact were!

	▲	theshrike79 3 days ago \| parent [-]
		There's your problem right there. Don't use it as a knowledge machine, use it as a tool. Agentic LLMs are the ones that work. The ones that "use tools in a loop to achieve a goal"[0]. I just asked Claude to "add a release action that releases the project as a binary for every supported Go platform" to one of my Github projects. I can see it worked because the binaries appeared as a release. It didn't "hallucinate" anything nor was it a "stohastic parrot". It applied a well known pattern to a situation perfectly. (OK, it didn't use a build matrix, but that's jsut me nitpicking) In your cases the LLM should've seen that you're asking about current events or news and used a tool that fetches information about it. Now it just defaulted to whatever built-in training data was in its context and failed spectacularly AIs have a branding issue, because AI != AI which isn't AI. There are so many flavours that it's hard to figure out what people are talking about when they say "AI slop is crap" when I can see every day how "AI" makes my life easier by automating away the mundane crap. [0] https://simonwillison.net/2025/Sep/18/agents/