Managing complexity, modularity, separation of concerns, were already critical for ensuring humans could still hold enough of the system in their brains to do something useful.

People who do not understand that will continue to not understand that it also applies to AI right now. Maybe at some point in the future it won't, not sure. But my impression is that systems grow in complexity far past the point where the system is gummed up and no-one can do anything, unless it's actively managed.

If a human can understand 10 units of complexity and their LLM can do 20, then they might just build a system that's 30 complex and not understand the failure modes until it's too late.

> People who do not understand that will continue to not understand that it also applies to AI right now.

I think this is mostly a matter of expectation management. AIs are being positioned as being able to develop software independently, and that’s certainly the end goal.

So then people come in with the expectation that the AI is able to manage that, and it fails. Spectacularly.

The LLM can certainly not manage any non-local complexity right now, and succeed in increasing the technical debt and complexity faster than ever before.