Comment by layer8

Our production incidents have dramatically increased over last 2 years after management pushed AI. In 2023, we never failed our SLA. Now, we continuously keep failing it due to some stupid outage. There was no real change in architecture or strategy - only the adoption of AI.

There have already been several high-profile AI-root-cause incidents at many companies this year. I guess we can look forward to even more deterioration in the next 2 years.

AI easily generates PR's with thousands of lines. I my company there's even a directive for agents to split up their work into multiple PR's based on some arbitrary metric of files/lines changed. When one of my colleagues uses AI to "implement" something, the amount of code I need to review is much much more. If I were to do review as I am supposed to, then AI is absolutely increasing the time and effort I have to put into a change (as opposed to the person who just writes a prompts and calls it a huge productivity boost).

There's the meme in programming that goes something like this "Give a programmer two lines of code to review and he'll find 20 issues. Give a programmer 500 lines to review and he's say that it looks good". At some point you simply cannot keep pace with the amount of generated code as a human.

> This is usually due to time pressure and cost. AI arguably substantially reduces that kind of pressure.

This is categorically false because time and cost pressure is relative and if anything AI has exacerbated the exceptions for ROI and Turn Around time.

This along with the fact that even state of the art AI tends to generate subpar (albeit working) code extremely fast and in large volume.

You can see the effect of this already in the increased rate of production incidents recently.

This isn’t to say that AI is useless, but the tech debt it generates is unprecedented.