> Managing a codebase written by an LLM is difficult because you have not cognitively loaded the entire thing into your head as you do with code written yourself
This happens with any sufficiently big/old codebase. We can never remember everything, even if we wrote it ourselves
I do agree with the sentiment and insight about the 2 branches of topics frequently seen lately on HN about AI-assisted coding
Would really like to see a live/video demo of semi-autonomous agents running in parallel and executing actual useful tasks on a decently complex codebase, ideally one that was entirely “manually” written by devs before agents are involved - and that actually runs a production system with either lots of users or paid customers
> This happens with any sufficiently big/old codebase. We can never remember everything, even if we wrote it ourselves
The important thing about a codebase wasn't ever really size or age, but whether it was a planned architecture or grown organically. The same is true post-LLM. Want to put AI in charge of tool-smithing inconsequential little widgets that are blocking you? Fine. Want to put AI in charge of deciding your overall approach and structure? Maybe fine. Worst of all is to put the AI in charge of the former, only to find later that you handed over architectural decisions at some point and without really intending to.
That sounds like a hard or, as if ten years of development of a large codebase was entirely known up-front with not a single change to the structure over time that happened as a result of some new information.
"We build our computers the way we build our cities—over time, without a plan, on top of ruins." -- Ellen Ullman
This happens with any sufficiently big/old codebase. We can never remember everything, even if we wrote it ourselves
I do agree with the sentiment and insight about the 2 branches of topics frequently seen lately on HN about AI-assisted coding
Would really like to see a live/video demo of semi-autonomous agents running in parallel and executing actual useful tasks on a decently complex codebase, ideally one that was entirely “manually” written by devs before agents are involved - and that actually runs a production system with either lots of users or paid customers