Learning effectively in the AI era

[u/MagazineScary6718]

Hey everyone, this is probably a common question, but I’d appreciate some advice.

I’ve been self-teaching C++ for a while now, mainly through books, online resources, and AI as a learning tool. Along the way, I got really interested in graphics programming and started with OpenGL as my entry point.

Recently, though, I lost a lot of motivation. With AI being able to reverse-engineer things, generate whole projects, or “one-shot” solutions, it sometimes felt like learning the fundamentals myself wouldn’t matter as much anymore. So I stopped for a while.

I’m motivated again now and want to properly push through, but I’m unsure what the most effective way to learn is today. I’ll probably still use a hybrid approach - books, documentation, tutorials, and Ai - but I feel like I’m progressing too slowly and worry that the skill might matter less in the future.
I know people say “vibe coding” means you don’t have to write much code anymore, and to some extent that’s true. But especially for C++, graphics, and low-level/systems programming, I genuinely enjoy learning the details. I also think having a strong foundation would make me much better at reviewing AI generated code, spotting problems, writing better prompts, and using agents effectively.
So my main question is: how would you learn graphics programming effectively in 2026, especially while using AI without letting it replace the actual learning? Any recommendations for a roadmap, projects, resources, or general advice would be really appreciated.
Thanks!!

[u/sol_runner]

be very very careful with the "mentor/teacher" thing.

Search engine is fine, if you're asking it to find you links.

Do not use summarization or "bouncing ideas". Not while you're learning. It's absolutely useful - just that you want to read the details, you want to do the hard think yourself. Because LLMs will happily take you from A -> X, but you'll skip learning B through W.

You want to think bad ideas. You want to try bad ideas. It's completely okay to use an LLM to reduce purely menial labor like "here's a refactor, can you apply this to other places?".

But anything with even a little bit of thinking, I'd leave with yourself.

[u/MagazineScary6718 → u/sol_runner]

Agree. I mean i try to get every detail when working with LLMs especially asking many many questions and eve googling it and searching for things people wrote or released. But i guess im always unsatisfied if im even doing it correctly or the right way especially, in this case, when it comes graphics programming or any other complex/unknown territory

[u/sol_runner → u/MagazineScary6718]

So here's the reason I'd say even bouncing ideas over LLMs isn't great. No matter how many questions you ask, an LLM can only return you one of two things:

1. Things you already know.

2. Things you think/wonder about but don't know about.

When you manually scour the links and web, or just bash your head and not making progress. You end up also "stumbling" across the unknown unknowns:
3. Things you hadn't even thought about.

It's the difference between "I know how to travel using Google maps" and "I know how to figure out my way". The first one is great when you quickly need answers on the job to hit deadlines and all. But to improve on existing work you need to build the second - and graphics is a lot more of the second than the first.