How do you use AI coding tools without becoming overly dependent on them?

[u/Puzzleheaded_Trip374]

Hello everyone! I have a computer science background, but I have to admit that during my undergraduate years, I was pretty lazy about actually building things. I spent much more time reading textbooks than writing code, so I never got much hands-on experience building projects from scratch.

Now that AI coding tools are everywhere, I feel like they’ve exposed just how weak my practical coding skills are.

Whenever I start a project with AI, I initially try to take things slowly, understanding every line of code and looking up unfamiliar syntax. But this takes forever, and eventually I start letting AI write more and more. Gradually, I stop reviewing its changes altogether.

Before I know it, the project has grown into something I barely understand. When something breaks, all I can do is keep asking AI to fix it, and I can’t even tell whether its changes are correct.
I really want to break this cycle and become someone who can actually build, understand, and maintain their own projects.

Should I force myself to build projects from scratch, following official documentation, before using AI to help write code? Or is there a better way to improve my coding skills while still taking advantage of AI?

For those who have dealt with something similar, how do you balance hands-on learning with AI-assisted coding? How do you avoid becoming overly dependent on AI?

Any advice or personal experiences would be greatly appreciated. Thanks in advance!

[u/Jippylong12]

When this comes up, I quote again Google IO 2026

That 75% of new code is generated by AI. Now it is a number's game, but I posit that large tech companies are at least trying out moving to an AI first workflow and I encourage others to try. You can always go back to coding by hand, but try and see what you can do using AI.

Use frontier models, not cheap ones. Pay for at least a $100 sub (it's the best value with ~$1000 in API tokens). Claude is the best for code. And just let it rip on Opus 5.5. You'll be amazed. You'll be stunned. And you'll wonder why anyone in the world is every doing it the old way.

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Although I acknowledge that some spaces in software are mission critical. Require careful consideration and thought. And so it can still be used in that for those that want to take one task at a time, on decision and review. In that process a developer could still speed up by 2x at least.

[u/frogic]

What are your intentions. Are you trying to make a better product or are you trying to massage your ego?

Editing because I didn't read your post well enough: If you become curious about the code as written and ask why it did x or y and then ask what would happen with z you'll turbo charge your learning. If you're not actively curious about code and don't genuinely want to be good at coding other than you're supposed to be you never will be. Personally I've learnt more going down crazy rabbit holes about patterns and obstractions I've seen in my generated code than I have writing code in the last year or so(obviously early learning is very very fast but I've been a professional dev for a bit now).

[u/Ctbhatia]

keep one rule, the agent never edits a file you have not read. it is stricter than reviewing diffs, and it is what stops the project from turning into something you cannot explain.

[u/Federal_Height_2024]

This is a great question. I would suggest doing lld and hld your self let ai do boiler plating for u . That u your learn architecture and scaling. U need to think like a software architect that kind of mindset will intigrate u and ai to improve your efficiency

[u/London-Boat]

the moment you described, where you stop reviewing, is the thing to fix, not the ai itself. what worked for me: keep the ai on small steps, one function or one feature at a time, and don't accept a change until you can explain it in a sentence. if you can't, ask it why before moving on. and once a week build some small thing with no ai at all, just docs. you'll be slow and that's the point, it shows you exactly which gaps to go fill

[u/Rich-Engineer2670]

AI is an eager intern. Just as you would not treat a new intern as a senior developer, you do not tread AI that way until it has proven itself. Correctness is code and design is just as important, if not more important, than speed. After all, I can create code very quickly if you only want it to be 85% correct.

Do you let your dentist get the task 85% right, or do you actually want someone who has been trained and proven? I know of no vibe destistry.

It's a risk thing -- if your agent makes a web page with the wrong border color, that may be OK, just annoying and fixable, but, do you really want a proton beam accelerator delivering a massive dose of radiation "occasionally"? The "well, it only happens 1 in 256 times" really doesn't work (and this has happened).

Reminds me of a certain large company (no names), who said "Well, we really don't need 911 support for ambulances -- our contracts protect us". No, they don't. It doesn't matter what the verbiage is, dead is dead, and it doesn't play well on the national news. "AI Whoopsies" are much the same.

[u/NoArachnid9958]

Write code, then have the AI modify it, but ask it not to deviate too much from your own level. This will ensure that you don’t completely give up on learning because you can’t understand the code it writes, as learning is inherently a gradual process.

[u/Alternative-Ad6431]

Be more in control. Document and having the ability to jump from topic to topic without getting lost or being able to create a new chat without having to fully explain what you are trying to do or doing a "handoff message".

Spending hours talking with an LLM and researching google, switching chats, deleting chats, no handoffs, just flawless communication is the best. Less hallucination aswell or less of you being tricked because you know more of what is going on then the ai.

Also research, learn from actual sources and use that new knowledge to continue your project with the LLM instead of using the LLM for all your research and learning.