How is this different from proper prompt engineering?

Every library should have cursor rules.

I don't know what we do when the rule files fill up the entire context, but until then, every library should have them.

Transcripts don't hallucinate

I'm building a free, open-source tool for checking the citations in the AI-generated output. False citations should be a solvable problem. laoshu.ai

It's like building a house on sand and then blaming the roof for leaking.

If you're building RAG systems, "The Map Is Not The Territory – Multimodal Retrieval" video is a masterclass.

Don't miss it.

www.youtube.com/watch?v=hf9B...

Here's what matters first:
0. The source data you feed the system
1. How you preprocess and chunk that data
2. The indexing method you choose

If any of that's sloppy, incomplete, or mismatched with how your users query, AI is going to hallucinate. And no clever prompt engineering will save you.

mikulskibartosz.name/effective-ll...

Expect to spend 60–80% of your time reading AI responses and judging what’s good or bad.

No automation will save you here. But a clear process will.

In my new article, I break down how to debug RAG systems and LLMs.
If AI quality matters to your org, this guide will save you time and reputation.

From the BentoML team, I would expect something more in-depth. This is just scratching the surface.

They are all biased towards the owner's opinions. You only notice it when you disagree with those opinions.

Would it work for the people who diagnose themselves with Reddit?

You don't get "nerd points" for saying, "I coded frontend for an AI chatbot."

I know a journalist who wrote over a dozen articles in the style of "I asked ChatGPT what is the best comedy/horror/romance/whatever movie. The answer shocked me."

But wait, it gets worse. Someone reads this...

Do those keys work, or just look like keys?

It depends on how many engineers prepare the evaluation dataset and run the tests. If 0, you can have 100s of engineers tweaking the prompts and get no expected results.