Yes, the code archaeology is the time consuming part. I could use an LLM to do that for me in my co-workers generated code, but I don’t want to because when I have worked with AI I have found it to typically create overly-complex and uncreative solutions. I think there may be some confirmation bias with LLM coders where they look at the code and think it’s pretty good, so they think it’s basically the same way they would have written it themselves. But you miss a lot of experiences compared to when you’re actually in the code trenches reading, designing, and tinkering with code on your own. Like moving around functions to different modules and it suddenly hits you that there’s actually a conceptual shift you can make that allows you to code it all much simpler, or recalling that shareholder feedback from last week that — if worked with —could allow you a solution pathway that wasn’t viable with the current API design. I have also found that LLMs make assumptions about what parts of the code base can and can’t be changed, and they’re often inaccurate.