[CharlieDigital]

Problem with this approach is that it is contextually expensive because even for a 1 sentence change, the LLM will need to read whole docs into context.

Better solution I mentioned above: inline, idiomatic code comments for your language and have the LLM dump reasoning into the `<remarks>`, `@remarks`, etc. of the comment block.

Now you get free, always up-to-date, platform agnostic, zero-infrastructure long-term memory which works on any agent that every agent is forced to read when it reads the method. It will never miss like it can with secondary docs.

It saves context because instead of reading a 2000 token document for 100 tokens of relevant context, it just reads the comments for the specific method and hydrates long term memory just-in-time with almost certain activation rate without additional prompting.