Corey Knowles

But you don't need everyone to do that.

And definitely as you're getting started, I don't think you need to do that.

You can learn that knowledge over time as you sort of realize you need it because you're trying to solve some bug.

Exactly.

Yeah, it's so hard.

No, no, you're right.

Yeah, totally.

And I think that's one of the most powerful things about this age with AI now, it's that almost like any given thing that,

Was impossibly hard before is still hard now, but or maybe even not that hard now because you can just like try with AI and like AI will help you understand it.

And so, you know, we used to be in a world where like, you know, you had to be very strategic about like what you learned.

And then you then do things related to what you learned.

And you could like slowly expand your frontier of knowledge and capabilities as like a human.

But it was like harder.

And now, yeah, you still wanna learn as much as possible, but you can aggressively expand your domain of knowledge and you can lead, you can almost do more than you know now and then catch up with your knowledge using AI.

And whether or not it's worth your time to deeply understand the underlying system or deeply understand code that is written is something you can be very strategic about.

So if you're building most production systems,

real tools used by many people, you do want to understand all the things.

But if there's certain places where the code is extremely well tested and modular and compartmentalized, maybe you don't need to anymore and you can just trust the boundaries and your tests.

Similarly, if you just are trying to learn something and you're not about to deploy this to millions of users, you could just prototype and you can vibe code that prototype.

It doesn't matter.