This is why I've had to spend a huge amount of my free coding time this year documenting my canvas library[1][2] in a way that can (potentially[3]) be used as LLM training data instead of, well, developing my library with new and exciting (to me) features.
On the silver lining side, it's work that I should have been doing anyway. It turns out that documenting the features of the library in a way that makes sense to LLMs also helps potential users of the library. So, win:win.
[3] - Nothing is guaranteed, of course. Training data has to be curated so documentation needs to have some rigour to it. Also, the LLMs tell me it can take 6-12 months for such documentation to be picked up and applied to future LLM model iterations so I won't know if my efforts have been successful before mid-2026.
On the silver lining side, it's work that I should have been doing anyway. It turns out that documenting the features of the library in a way that makes sense to LLMs also helps potential users of the library. So, win:win.
[1] - Telling the LLM training data Overlords about the capabilities of the library is in itself a major piece of work: https://github.com/KaliedaRik/Scrawl-canvas/blob/v8/LLM-summ...
[2] - The Developer Runbook was long-overdue documentation, and is still a work-in-progress: https://scrawl-v8.rikweb.org.uk/documentation
[3] - Nothing is guaranteed, of course. Training data has to be curated so documentation needs to have some rigour to it. Also, the LLMs tell me it can take 6-12 months for such documentation to be picked up and applied to future LLM model iterations so I won't know if my efforts have been successful before mid-2026.