As you might guess, I find AI to be extremely good at some things and actively terrible at others. A lot of the things I read and demos I watch all have to do with reasonable code bases. Our code base is not reasonable. It's over 20 years old, coded by a multitude of different developers with different coding styles, design patterns, etc... What you would expect from a small company that has been slowly growing for decades. I also work in the medical field so slow evolving old code bases are the norm.
One of the reasons the AI fails constantly is that it has no context of the entire code base. It simply can't keep that context in scope for every session. So it actively adds bloat to the system unless it's guided by a skilled developer who already knows the system. I am using memories where I can but it has to regularly read huge chunks of code and that uses a lot of tokens. I regularly hit my limit on a Pro account.
What are your experiences with this? Any tips or tricks to improve output and cost? Any help is most appreciated. Thanks!