
unfortunately you were right, I have to read the code now it got too sloppy
Post

unfortunately you were right, I have to read the code now it got too sloppy




I've been treating AI work from the beginning as the work of an intern, and that has worked out pretty well. Sometimes if the feature is complex I first do a pass of light scaffolding where i start to structure the code how I want it, and leave placeholders. LLMs thrives around structure, as they are designed to recognize patterns. From my experience, if you design a whole new feature and the AI can't really find proper structure around it in your codebase, result quality will be much lower. I then make Codex do most of the implementation work, and do a very light review myself, to make sure the code is not unnecessarily bloated. If codex doesn't structure the code the way I imagined and I can think of a more efficient way to do it, I'll guide it. Then in a new session I ask codex to review the changes compared to the base branch, most of the time he will find issues, in which case I make him fix what's worth fixing, always making sure the fix doesn't lead to unnecessary bloat through a very light review I then trigger a new review in a new session, and keep repeating this until there are no more issue worth fixing. When codex is done fixing issues, I then usually make Claude do a pass of review. Claude is usually much more nitpicky and often a lot of his findings are not really worth fixing. So I feed the output to Codex, and ask it to review what is valid and worth fixing. In some case, it will highlight a valid problem than Claude found and Codex missed. Once all those steps are completed and both Codex and Claude don't find any meaningful issue anymore, I'll do a manual very in-depth review myself, in the same manner I would review the PR of an intern. Then another person from the team will also do another pass of manual review on my PR before it is merged. Ultimately, I think it also depends on what type of software you are working. I could probably live with few less pass of reviews that I am currently doing if I wasnt working on a financial app like @KyanExchange where there is no room for mistake.




