The major problem I see with current LLM-based code generation is their overconfidence beyond a certain point. I've experienced agents losing track of what they

The major problem I see with current LLM-based code generation is their overconfidence beyond a certain point. I've experienced agents losing track of what they are developing; a single line change can literally mess up my entire codebase, making debugging a nightmare. I believe we need more structured, policy-driven models that exhibit a bit of self-doubt, prompting them to revert to us for clarification. Furthermore, there should be certain industry standards in place. Another significant issue is testing and handling edge cases. No matter what, today's AI consistently fails when dealing with these scenarios, and security remains a concern. what are some problems you have noticed ??