Snake oil may be a bit strong, because snake oil never works (except maybe as placebo?) whereas anything with an LLM, even though stochastic, has a pretty high chance of working.

> ... you also realize that promised productivity gains are also snake oil because reading code and building a mental model is way harder than having a mental model and writing it into code.

Not really, though it depends on the code; reading code is a skill that gets easier with practice, like any other. This is common any time you're ever in a situation where you're reading much more code than writing it (e.g. any time you have to work with a large, sprawling codebase that has existed long before you touched it.)

What makes it even easier, though, is if you're armed with an existing mental model of the code, either gleaned through documentation, or past experience with the code, or poking your colleagues.

And you can do this with agents too! I usually already have a good mental model of the code before I prompt the AI. It requires decomposing the tasks a bit carefully, but because I have a good idea of what the code should look like, reviewing the generated code is a breeze. It's like reading a book I've read before. Or, much more rarely, there's something wrong and it jumps out at me right away, so I catch most issues early. Either way the speed up is significant.