Comment by rvz
6 hours ago
Given the issues with AWS with Kiro and Github, We already have just a few high-profile examples of what happens when AI is used at scale and even when you let it generate tests which is something you should absolutely not do.
Otherwise in some cases, you get this issue [0].
[0] https://sketch.dev/blog/our-first-outage-from-llm-written-co...
Don't "let it" generate tests. Be intentional. Define them in a way that's slightly oblique to how the production code approaches the problem, so the seams don't match. Heck, that's why it's good to write them before even thinking about the prod side.
The linked article does not speak of tests, it speaks of a team that failed to properly review an LLM refactor then proceeds to blame the tooling.
LLMs are good at writing tests in my experience.