Introduction
There has been a lot of noise around AI lately. Some people treat it like a shortcut that removes the need to learn anything. Others treat it like a competitor that is coming to replace developers entirely. I see it differently.
If you use it properly, AI can speed up your learning in ways we didn’t have access to a few years ago. It’s not there to replace your thinking, it’s there to challenge it, refine it, and sometimes explain things in ways that finally make them click.
I used AI to improve my understanding of backend development. I only had a basic understanding of handling API endpoints. But by using AI alongside official documentation, I was able to build a media upload application for a wedding that ran without any hiccups. Along the way, I learned how to set up a VPS, configure S3 buckets for file storage, and use a PostgreSQL database to manage file information properly.
That’s the key difference. AI should support your learning, not do it for you.
Planned Study
Before jumping into any topic, create a rough plan of what you actually want to learn. Be specific. Do you want to understand authentication at a high level, or do you want to deeply understand JWTs, sessions, cookies, and their security implications?
Once you know the scope, you can ask AI to structure a learning roadmap for you. For example, you might say:
“Create a structured plan to learn Node.js for backend development.”
“Break this into beginner, intermediate, and advanced topics.”
“Suggest practical exercises for each stage.”
This gives you direction instead of random information.
You can also control the depth. If you want a surface-level understanding first, say that. If you want deep technical explanations, say that too. The quality of what you get depends heavily on how clearly you ask.
Explain how you prefer to learn. You might even provide an example of the structure you like. Maybe you prefer visual breakdowns of concepts, or maybe you like topics chunked into smaller pieces. When I’m using it, I often ask it to go line by line through code and explain exactly what is happening. That level of detail helps everything settle properly.
And if you’re unsure or not confident in its answer, ask for references. Ask where the information is coming from. Then go and read the documentation yourself. AI is powerful, but your real confidence comes from verifying and understanding the source material.
Dumb It Down
One of the most underrated ways to use AI is to ask it to simplify things.
There will always be topics that just don’t click the first time. Maybe it’s closures in JavaScript. Maybe it’s event loops. Maybe it’s how databases handle indexing. Instead of pretending you understand it, lean into it.
Ask it to explain the concept like you’re brand new to programming. Then ask it again in more technical detail. Then ask for examples. Then ask for edge cases.
There are no stupid questions here. And honestly, the “stupid” questions are usually the ones that unlock deeper understanding.
Sometimes I’ll even open a completely separate chat dedicated to one topic and just explore it. I’ll ask ten, fifteen, twenty questions on that single idea until I can explain it back in my own words. That kind of focused curiosity builds real skill.
Compare Your Understanding
One of the most powerful techniques is explaining the concept back in your own words.
After you think you understand something, write out your explanation and ask AI to critique it. For example, you might say, “Here’s how I understand how middleware works in Express…” Then paste your explanation and ask it to point out any mistakes, missing details, or areas that need clarification.
This forces you to think instead of passively reading. It also exposes gaps in your understanding that you might not notice on your own. Sometimes you’ll realise you only understood 70% of the concept, and that final 30% is where real confidence is built.
But here’s something important. Don’t treat every response as absolute truth. AI can occasionally fabricate details or confidently present outdated information. That’s why you should double-check critical concepts against official documentation.
Use AI as a reviewer, not as your only source of truth.
Practise
None of this matters if you don’t actually build something.
After learning a concept, create a small throw-away project. It doesn’t need to be perfect. It doesn’t even need to be useful. It just needs to force you to apply what you’ve learned.
You will fail. Something won’t work. You’ll misunderstand part of the implementation. That’s normal. Each failed attempt sharpens your understanding.
And sometimes, while experimenting, you’ll stumble across a completely new idea. A small test project might turn into a portfolio piece. A random experiment might turn into your next main application.
AI can guide you, but your hands on the keyboard is where the real growth happens.
Conclusion
AI is not your competition. It’s a tool. Like a calculator for math or Stack Overflow for debugging, it becomes powerful when you use it intentionally.
The doom and gloom around AI replacing developers can be discouraging, especially if you’re still learning. But tools don’t remove skill, they shift it. The developers who grow the fastest will be the ones who learn how to work with AI, not fear it.
Use it to plan. Use it to simplify. Use it to challenge your understanding. But always think for yourself and always build.
If you approach it the right way, AI won’t replace your skills. It will help you sharpen them.
If you enjoyed this blog and want to keep learning, check out these other blogs of mine:
Thanks for reading, and happy coding.
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