The problem with your example of applying analyzing something as complex and esoteric as a codebase is that LLMs cannot reason they simply return a response based on statistical inference, so unless you followed a standard like PSR for PHP and implemented it to a 't' it simply doesn't have to context to do what you're asking it to do. If you want an LLM to be an effective programmer for a specific application you'd probably need to fine tune and provide it instructions on your coding standards.

Basically, how I've become successful using LLMs is that I solve the problem at a 9,000ft view, instruct the LLM to play different personas, have the personas validate my solution, and then instruct the LLM step-by-step to do all of the monkey work. Which doesn't necessarily always save me time upfront but in the long run it does because it makes fewer mistakes implementing my thought experiment.