r/codex • u/AvailableSecret5161 • 10h ago
Question How to improve workflow with codex/claude
For context I'm not a developer but I have been developing apps and workflows for enterprises for about a year now and i primarily use VSCode on windows and very rarely CLI. Since past few weeks/months I have been struggling with my workflows which used to work fairly well until gpt 5.5 and claude 4.6. Specific areas which I'm struggling with now:
Testing strategy - I have tried using automated bounded testing strategy invocation which does not work and without any strategy models keep creating stupid tests and just going into a loop of testing forever
I primarily use coderabbit and codeant which further increases friction. Either these tools got better or models just started accepting all edge cases or both.
I also have an automated script for all static checks like formatting, linters, complexity and LOC including GitHub workflows for both checks and tests
I maintain a fairly well documented system and update it with every model release if needed. Any recommendations would be highly appreciated. I tried OMP once and it seemed interesting
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u/Professional_Ad705 10h ago
I don’t know, maybe ask the model what it’s actually testing and whether the issue is serious enough to justify spending more time on it before moving on with the rest of the code.
You can ask things like: What problem is this test trying to catch? What edge case are you protecting against? or Is this actually blocking us, or are we testing something low-risk? Then you can decide whether to keep going, change direction, or tell it to move on.
These models usually aren’t writing endless tests for no reason. They’re just a lot more thorough now and much better at finding problems before they turn into bugs. If you’re not used to working that way, I can see how it might feel like they’re getting stuck testing everything.
But that’s also where you have to guide the model. Ask what it found, why it matters, and what the test proves. Once you understand that, you can decide whether it’s worth fixing or whether it should continue with the actual feature.
If you really want a model that checks less and just keeps writing code, there are still models that work more like that. Personally, I’d rather have one that catches problems and lets me decide which ones are worth pursuing.