recently I gave AI a task to configure a software and the software didn’t have any docs of how it works only the source code. the agent went through all the files and generated a summary of how it works and why it’s not working for my particular scenario and suggested edits to my docker-compose.yml file. I couldn’t believe it since the bug was very hard to find and it used headless firefox to find why it wasn’t working.
made me realize do we still need documentation of how a software work when a AI can easily explain it?
Heres a hot take: as a technology AI (whatever that may mean) can be genuinely useful. In the way it is implemented right now destroying the environment and rising the cost of everything I despise everything that it is. LLMs are the main culprit and the utterly idiotic decision to have one model know everything from embedded coding to ancient Babylonian history.
Neural networks and even specialized small LLMs that I run on decentralized systems are genuinely useful. I use open weight models that I run locally to help with implementing functions from stubs and even do documentation, which it truly is not bad at.
I don’t hate the technology, I hate the greedy dystopian hyper capitalistic environment destroying way it is deployed in. And the way that it is trained by literally stealing the work of creative people.