[banannaise]

The ticket has subtle errors in its description that are only caught by someone experienced with the codebase.

The code hides an exception behind an if-then-else that defaults to the most common state, which isn't caught until it breaks things for the 1% of users who don't have that state.

The new feature quietly breaks a feature not covered by the acceptance tests.

The documentation is four times as long and nobody who relies on it can read it.

And I'm stuck spending my time going over tickets with a fine-toothed comb, reviewing PRs, and mentoring contributors to prevent all of this garbage from ending up in the live code.

[elfly]

I will give you 4.

1, 2 and 3 happened a ton in the good old times before AI. If anything, we can make the code be more tested than before, but that requires a lot more engineering, that is made easier by LLMs.

It's just we haven't adapted to do them.

[chorsestudios]

People noted similar issues ever since LLMs came out, but the rate at which they have been rapidly improving on all of these is significant. Documentation being 4x too long could probably be fixed with a rule instructing the agent to keep it concise and no longer than 2-3 paragraphs.

[banannaise]

They seem to be converging toward an asymptotic accuracy level that is not particularly close to 100%. That is not good enough when you're trying to instruct engineers, particularly junior ones.

[skydhash]

Conciseness is variable. Sometines a paragraph is enough, some other tome you need multiple chapters and a glossary to get the point accross. 4x too long may be 4 paragraphs in the first case and a 400 pages book in the second case.

Adding a rule like yours is not the solution.

[glial]

Definitely, but the first 3 issues are also created by human co-workers.

[oliveralbertini]

Do you use Microsoft Copilot ?