> Whereas if you're handing off all dev and no longer reading code, just making CTO-level architecture decisions, then there are only 2~3 models right now worth using, none cheap.

I use frontier models every day and night, but not sure if the described approach is possible with any of them right now. Models still make stupid mistakes and people who do not read the code produced are bound for surprising discoveries in their codebase. Not trying to downplay the effectiveness of LLM-assisted coding and all that, but it's hard to imagine how much stupid shit i would've committed if I was not reading their output.

If you can test well enough, both manually and automated, then it's okay if there's a bunch of stupid mistakes in the code, as long as the end result works right. Not unlike biology.

Serious question: Are you do a combative code analysis with a range of different models?

I used to find real dumb bugs in code reviews. With 2-3 different models doing a combative code review.. most of that is already fixed when I get it.