> Now we admit folks who don’t know what they’re doing and are in the process of learning. They don’t know what to look out for. How does this tech help them? Do they know to ask what a use-after-free is or how cache memory works? Do they know the names of the algorithms and data structures? Do they know when the GenAI is bullshitting them?

You can know enough in X to allow you to do Y together with X, which you might not have been able to before.

For example, I'm a programmer, but horrible at math. I want to develop games, and I technically could, but all the math stuff makes it a lot harder sometimes to make progress. I've still managed to make and release games, but math always gets in the way. I know exactly how I want it to behave and work, but I cannot always figure out how to get there. LLMs help me a lot with this, where I can isolate those parts into small black boxes that I know they give me the right thing, but not 100% sure about how. I know when the LLM gives me the incorrect code, because I know what I'm looking for and why, only missing the "how" part.

Basically like having 3rd party libraries you don't fully understand the internals of, but can still use granted you understand the public API, except you keep in your code base and pepper it with unit tests.