Great code needs great understanding and agents need excellent guidance. Even in my current solo-dev work, I can't imagine making a production commit I haven't read until I understand it. I own the consequences of my code; that's a responsibility AI agents can't take.

Where is the bottleneck? WHERE?? Tell me! No evidence needed, just lay it on, man to man, thought-leader to thought-leader!

AI have limitation and hallucinate. Complex code will be explained in hallucinated way. At some point AI will be unable to write more because the arch has become too complex or the volume of code will be to high.

The article I would like to read would suggest how to force LLM to architect the code like a solid tower instead of a pile of unstable mud.

Also, a huge reason to understand the code yourself is to make sure the LLM isn't wrong, but this doesn't work if an LLM is itself generating the understanding.

The problem pre-dates LLM's: writing code that "works" but breaks the underlying model. Because it works, it always sounds reasonable and doesn't raise any flags.

Only someone - human or LLM - who holds the model as the standard would see that this working solution breaks the model.

(In theory, the model is to preserve scaling, flexibility or some other systemic feature not immediately invalidated by this working code, but as always the model itself could be bad.)

LLM's are not bad at giving an account of the model; indeed, fighting with the LLM over what the model is can clarify things. But LLM's will happily hold on to a stream of inconsistent statements as their model, so they are not the authority.