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And here I am, using AI twice within the last 12 hours, to ask it two questions about an extremely well used, extremely well documented, physics library, and both times having it return to me sample code which makes use of library methods which don't exist. When I tell it this, I get the "Oh, you're so right to point that out!" response, and get new code returned, which still just blatantly doesn't work.

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Someone had a blog post that said if a LLM hallucinates a method in your library, that means it should statistically have a method like that. LLMs work on probabilities and if the math says something should be there, who are you to argue =)

Also use MCPs like codex7 and Agentic LLMs for more interactivity instead of just relying on a raw model.

Hello, have you ever tried using the coding agents?

For example, you can pull the library code to your working environment and install the coding agent there as well. Then you can ask them to read specific files, or even all files in the library. I believe (according to my personal experience) this would significantly decrease the possibility of hallucinating.

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