Measuring the impact of AI on experienced open-source developer productivity

As an open source maintainer on the brink of tech debt bankruptcy, I feel like AI is a savior, helping me keep up with rapid changes to dependencies, build systems, release methodology, and idioms.

But what about producing actual code?

Producing code is overrated. There's lots of old code whose lifetime we can extend.

I find it useful for simple algorithms and error solving.

Very, very much this.

If you stewarded that much tech debt in the first place, how can you be sure LLM will help prevent it going forward? In my experience, LLMs add more tech debt due to lacking cohesion with it's edits.