

Documentation will always have to be actually written by the author(s) of the code (or at least someone who understands the code really well), because only the author knows the intent behind a certain function or API endpoint, and that’s what the documentation is for.
LLMs don’t understand shit (sorry AI bros), they will sometimes produce accurate descriptions of the function code as written, but never the intent. Even if the LLM “wrote” the code, it doesn’t “understand” the real intent behind it, because it is just a poor mashup of code taken/stolen from someone else, which statistically fits the prompt.
What LLMs could help with is generating short, human-readable descriptions of what is happening in a given function. This can potentially be helpful for debugging/modifying projects with poor documentation, naming, and function separation, so that instead of gleaning through multiple 2000-line C functions in a 100k SLOC file, you can kind of understand what it does quickly. I’ve used deepseek for this before, with mixed-to-positive results.
But again, this would just be to speed up surface-level digging and not a replacement for actual documentation or good practices.






Except in this case this particular fridge has worked for 40 years already, so just by Bayesian statistics it is more likely to keep working than a modern one from a range that are known to break. Same reason why some old cars are getting more expensive nowadays.