I have tried dozens of different writing skills and my own prompt ideas, listened to podcasts with engineers from both major american LLM companies, actually read the prompting guides from anthropic for the models I use, and of course, as if it needs to be said, I use the latest and greatest frontier models, for difficult work.

What is your genius setup?

Can you give an example of what you wanted explained, the LLM explanation and why it is bad?

Obviously if you don't understand an idea you aren't really in a position to evaluate how good an explanation of it is. I have a background in Physics research and find models like Astra to be excellent at explaining concepts at a level for an advanced practitioner. It also has done very well, from what I can tell, for areas I am less knowledgable in. So I am confused by statements like yours that directly contradict my experience and the subjective experiences of many others.

> Can you give an example of what you wanted explained

Something I do dozens of times a day: "Please explain what this PR does, I haven't read it"

it will make me 20 pages of gibberish about caches, correctness checking, race conditions, github action runners, tradeoffs between a bunch of invented terminology internal to the PR without defining the terms- you'd have to have already read the code to know what it was referring to

without ya know, explaining it. I ask my colleague and he says something like "oh it deletes records from such-and-such a system when they aren't needed anymore after a merge" and I know exactly what he means. A single well composed sentence was all that was needed.

You can ask the agent for a single sentence explanation and it will write something like "linked candidate records are trimmed when canonical record determination window is passed"

The agent has full context of what systems the code talks to, our terminology sheet etc. It just pathologically cannot simplify things down