Hard AI

Problem - coding on large code bases I have been doing a lot of vibe coding, and current models deteriorate in quality when the problem gets too large and too detailed. This makes complete sense if you know how current transformers work, and is well described here: https://research.trychroma.com/context-rot  The LLM simply glosses over details, and when it then rewrites some code, it forgets some instructions or previous details in the code, and you as a human will have to keep adding these things back. It is possible for the framework to do patches - but the problem is the same. The LLM is not smart enough to do a good patch.  I have a lot of experience in this, and if it was solved my life as a coder would be much easier. So I assume it is not a solved problem.  So this page is  description of an LLM that should be able to both handle large code bases, having deep knowledge of algorithms that exists and be smart enough to solve the problem asked. I have made some s...