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?


How many times are you getting married? 😄
Uhm, because it’s not the same? Why would I vibe code an app that’s almost exactly the same as an existing one?
Let me fix that for you: How many times are people getting married?
The answer: Lots.
There are already wedding websites out there, in every variation possible.
Why reinvent the wheel when we have so many wheels that they’re treated as disposable?
Because a vibecoded app is going to be a ripoff of its training data anyway. LLMs can’t produce creative or novel works, all they can do is stochastically regurgitate what they’ve already seen in their training data. So why deal with risk of injection attacks hidden in the training data when you can just use the original source instead?