[janoelze]

Any views on the nature of "maintainability" shifting now? If a fleet of agents demonstrated the ability to bootstrap a project like that, would that be enough indication to you that orchestration would be able to carry the code base forward? I've seen fully llm'd codebases hit a certain critical weight where agents struggled to maintain coherent feature development, keeping patterns aligned, as well as spiralling into quick fixes.

[simonw]

Almost no idea at all. Coding agents are messing with all 25+ years of my existing intuitions about what features cost to build and maintain.

Features that I'd normally never have considered building because they weren't worth the added time and complexity are now just a few well-structured prompts away.

But how much will it cost to maintain those features in the future? So far the answer appears to be a whole lot less than I would previously budget for, but I don't have any code more than a few months old that was built ~100% by coding agents, so it's way too early to judge how maintenance is going to work over a longer time period.

[htrp]

I'm seeing a lot of duplication in our AI coded repos that is getting to the point of being problematic to maintain.

[visarga]

> But how much will it cost to maintain those features in the future?

Very little if they have good specs and tests.

[brianjeong]

I think there's a somewhat valid perspective that the Nth+1 model can simply clean up the previous models mess.

Essentially a bet that the rate of model improvement is going to be faster than the rate of decay from bad coding.

Now this hurts me personally to see as someone who actually enjoys having quality code but I don't see why it doesn't have a decent chance of holding

[Deevian]

They demonstrated the ability to bootstrap... "something". There's no maintainability to the output of the experiment.