I think this is a symptom of the limited size of context which the current tools can hold. As more and more data enters the context, the weighting of what's im

I think this is a symptom of the limited size of context which the current tools can hold. As more and more data enters the context, the weighting of what's important or what already exists becomes "hard" for the AI tools to correctly deal with. Even to the point that information in any CLAUDE.md file is easily "forgotten" by the tool once the context gets quite deep. My experience is that the tools are like a smart intern. They are great at undergraduate level college skills but they don't really understand how things should work in the real world. Human oversight and guidance by a skilled and experienced person is required to avoid the kinds of problems that you experienced. But holy cow this intern can write code fast! Having extensive planning and conversation sessions with the tool before letting it actually write or change any code is key to getting good results out of it. It's also helpful to clarify my own understanding of things. Sometimes the result of the planning and conversing is that I manually make a small change and realize that the problem wasn't what I originally thought.