Yeah, someone made the point in a popular post here recently that all the firings are reducing institutional knowledge. IMHO, replacing that knowledge with LLM-written documentation is even more potentially catastrophic. Just from organizations I've worked in, a lot of the useful human knowledge is in knowing how to handle either undocumented edge cases or situations where the documents are outdated or wrong. Working with LLMs and reminding them to update those docs every time? Good luck. And if it's something where the docs touch actual real world operations, that's an area where only human operators with hands-on experience are going to recognize the potential conflicts or cognitive dissonance.

Companies really want to use AI because they can cut the workforce. But today's AI is generally not able to fill in the gaps in processes and documentation a human could. Hence the renewed focus on formalizing everything properly because it's the only way it will work.

The humans are the only ones knowing the why. The what is cheap.

> Having the humans document the code seems backward (maybe that's not what they're doing, but "make everything ready for ai" sound manual).

No, that's forward. Any documentation an AI can make, another AI can regenerate. If an LLM didn't write the code, it shouldn't document it either. You don't want to bake in slop to throw off the next LLM (or person).

It would / should / can, but there's big efforts in reducing token consumption now, so AI will likely try to skim and pick documentation just like real humans.