[neom]

If AI tools are making teams 76% faster with 100% more bugs, one would presume you're not more productive you're just punting more debt. I'm no expert on this stuff, but coupling it with some type of defect density insights might be helpful. Would be also interested to know what percentage of AI assisted code is "rolled back" or "reverted" within 48 hours. Has there been any change in number of review iterations over time?

[refactor_master]

I’m interested in earnings correlating with feature releases. Maybe you’re pushing 100% more bugs, but if you can sell twice as many buggy features as your neighbor at the same time, it could be that you could land more contracts.

It’s definitely a raise to the bottom scenario, but that was already the scenario we lived in before LLMs.

[apercu]

Right? I want to see the problem ticket variance year over year with something to qualify the data if release velocity is more frequent.

[8note]

i wouldnt find that convincing.

plenty of tickets are never written because they dont seem worth tracking. an llm speeding up development can have the opposite effect - increasing the amount of tickets because more fixes look possible than before

[apercu]

Fair. Everything has nuance.