You need a harness, yes, and you need quality gates the agent can't mess with, and that just kicks the work back with a stern message to fix the problems. Otherwise you're wasting your time reviewing incomplete work.
replyHere is an example where the prompt was only a few hundred tokens and the output reasoning chain was correct, but the actual function call was wrong https://x.com/xundecidability/status/2005647216741105962?s=2...
replyGlancing at what it's doing is part of your multitasking rounds.
replyAlso instead of just prompting, having it write a quick summary of exactly what it will do where the AI writes a plan including class names branch names file locations specific tests etc. is helpful before I hit go, since the code outline is smaller and quicker to correct.
That takes more wall clock time per agent, but gets better results, so fewer redo steps.
Here is an example where the prompt was only a few hundred tokens and the output reasoning chain was correct, but the actual function call was wrong https://x.com/xundecidability/status/2005647216741105962?s=2...
replyI as a human have typos too - and sometimes they're the hardest thing to catch in code review because you know what you meant.
replyHopefully there is some of lint process to catch my human hallucinations and typos.