[cgaooo]

The maintenance cost argument cuts both ways. We ran into this building our own project AI moves fast, but the bugs it introduces are weirdly hard to spot. Not the obvious stuff. The logic that looks completely reasonable until three weeks later, when something breaks in production, and you trace it back to a subtlety the AI got wrong. My honest take: AI doesn't reduce maintenance costs, it shifts them. Less time writing, more time reviewing. And reviewing AI code is harder than reviewing human code because it's fluent and confident even when it's wrong. Whether that's a net win depends entirely on how good your team is at reading code vs writing it

[azurewraith]

The review burden scales with the agent's decision space (which almost nobody is doing anything to limit today) and it's a variable you can control. When an agent has a discrete state, a subset of tools it can work with and constraints on the quality of the result the surface area of what could go wrong shrinks in proportion. The article treats this shift as inherent. It's more like we're all surprised pikachu that we gave the agents access to everything and expected it not to happen ever.

[cratermoon]

AI coding assistants are really good at writing code with subtle errors of the sort humans struggle to notice, even with close and sustained focus.