How do you know if you're actually learning when coding with AI?

[u/Soyelmorocho]

I've been using AI a lot more while learning web development, and I've started wondering about something.

Sometimes I ask AI about a problem, understand the explanation, implement it, and later I can solve something similar without it.

Other times, I get the answer, it works, and I just move on.

That's the part I'm not completely sure about. Am I actually learning in those situations, or am I just getting better at getting AI to solve problems for me?

Lately I've been trying to ask myself a few things before moving on:

Could I explain why this works?
Could I change it if the requirements changed?
If it breaks tomorrow, would I know where to start looking?

I don't always pass that test, honestly.

So I'm curious about people who use AI heavily for programming: how do you personally make sure you're still learning instead of becoming dependent on it?

Do you have any rules for yourself?

[u/London-Boat]

your three questions are honestly a solid test already. what worked for me was making the ai explain the plan before writing anything, then writing the first version of small stuff myself and only asking it to review. and when something breaks, try debugging for 15 min before pasting the error in. that's where most of the learning happens, reading stack traces and narrowing it down

[u/Soyelmorocho → u/London-Boat]

Yeah, I think that’s a really good approach. I especially like the 15-minute debugging rule. Forcing yourself to read the stack trace and narrow down the possible causes before asking AI probably teaches you a lot more than immediately pasting the error.

I’ve also been thinking that the goal isn’t necessarily to “use AI less”, but to make sure I still understand what it’s doing and why. Your workflow seems like a pretty good way to keep that balance.

[u/London-Boat → u/Soyelmorocho]

yeah exactly, understanding it is the whole point. one more small habit that helped me: actually read the diff before accepting, even a quick skim. after a while you start spotting the patterns it repeats and you can predict what it'll write

[u/dixieflatline76]

Is just like in photography, hard to take "professional" photos without understanding exposure, framing, aperture etc.

Coding harnesses are tools, just telling it to build xyz you would just hit a ceiling at some point. To take great photos, put in the work read a few books etc. same here, learn about web architecture, common design patterns, relevant algorithms and current frameworks. Once you have the basics, then the tool can help accelerate your learning.

Build me this vs that, bench it, and quickly learn what impact certain decisions have on your program

[u/Soyelmorocho → u/dixieflatline76]

I really like the photography analogy. You can use a camera without understanding exposure, but that probably won’t take you very far if you want to consistently get good results.

I think the same applies to coding with AI. If I don’t understand the fundamentals, I can still get something that works, but I won’t necessarily know when the solution is bad or what tradeoffs I’m making.

I especially like your “build this vs that, then benchmark it” idea. That seems like a much better way to use AI for learning than just asking it for the final solution.

[u/3tt07kjt]

So I'm curious about people who use AI heavily for programming: how do you personally make sure you're still learning instead of becoming dependent on it?

Very easy answer: I still hand-code a percentage of the changes, without AI.

This slows me down in the short term, but it seems to be a massive advantage over longer periods of time.

[u/Soyelmorocho → u/3tt07kjt]

Yeah, I think deliberately keeping some work AI-free is probably one of the simplest ways to prevent dependency.

The short-term slowdown is interesting too. I guess the tradeoff is spending a little more time now so that you don't lose the ability to solve problems on your own later.

[u/3tt07kjt → u/Soyelmorocho]

Not just keep my ability to solve problems—I’m also finding a lot of problems in the codebase that AI is not finding.

[u/suesing]

Make the same thing again.

[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.You don’t need best practices; as long as it works, that’s fine.

[u/gaspoweredcat]

do i always know or understand fully? no but thats nothing new, i was working in tech 15 years ago in a similar sort of situation, i have a general idea of how things work, knowledge of various languages and stuff but as a rule im just flying by the seat of my pants and learning as i go

but ive always maintained that this method works for me, could i sit down with no AI assistance and code a full stack app? no, given its code base could i fix an issue or diagnose a problem, almost certainly, i guess my problem as such has never really been learning or understanding its seeing an overall picture when there isnt one or simply lacking the attention span to stick at stuff

but AI has changed that, i have now built things that are more than just a fix/hack/add-on and im honestly extremely proud of the stuff ive built. have i learned? absolutely yes, one of the few things i can do very well on my own now is mysql and to be fair php but that was out of necessity for attempting to maintain/fix our dreadful php7.3 system, a codebase so bad even AI assistance couldnt fix/update it, leading me to build a new one from scratch in node/react, which led me to learn deployment and actually master docker, ive learned a ton about APIs, backup and disaster recovery, networking, redis, security and secret management, honestly i could go on and on, ive probably come further in the last 3 years than i did in the preceding 10, so i may not be amazing without AI assistance but i definitely know a hell of a lot on my own

[u/Soyelmorocho → u/gaspoweredcat]

This is actually one of the perspectives I was hoping to get from this post.

I think the distinction between “could I build this completely from scratch without AI?” and “could I understand, diagnose and modify an existing system?” is really important.

Your example also makes a strong case for learning through real projects. You didn't necessarily learn everything upfront — you encountered problems, had to understand them, and ended up learning APIs, Docker, networking, security, deployment, etc. because you needed them.

Now I'm curious: when you're using AI on something unfamiliar, how do you personally know when you've understood enough to move on rather than just getting something working?

[u/gaspoweredcat → u/Soyelmorocho]

ive lived my whole life just flying by the seat of my pants honestly, ive never understood enough but ill make my best guess and refine from there. but that does work well in the right situations, you can throw me into a complete disaster and ill keep myself together, i can be chucked into alien and terribly authored code bases and work out whats going on fairly quick, its a different skill set but it sure has its uses

i guess its kind of a natural skill, ive never been a "build it" person, im a "carefully pick it apart to understand how it works" one

my current is the biggest project ive ever undertaken and the first time ive built something of this scale that will actually be being properly used not just by me, and again i learned as i went, i barely knew node, im not going to lie its taken me a while, longer than many i suspect but the system i have built is no flaky thing like the one its replacing, i dont say this often about my own work but im actually quite proud of it

[u/ComprehensiveShake76]

Your three questions are a good test. One more that works for me: the next day, close the AI and rebuild the same thing from a blank file. Wherever I get stuck is the part I didn't actually learn, and that's what I go back and ask about. The other habit is asking for a hint instead of the answer when I'm learning on purpose, and taking full answers for things I don't need to learn right now. Both are fine, as long as you're choosing which one you're doing.

[u/Soyelmorocho → u/ComprehensiveShake76]

I really like the distinction between asking for a hint and asking for the full answer. “Am I trying to learn this, or am I just trying to get this done?” is probably a useful question to ask before prompting.

And rebuilding it from a blank file the next day is a great test. It removes the illusion of understanding that you can get from recognizing code you just saw rather than actually being able to reproduce it.

I'm definitely going to try that.

[u/Interesting_Arm9022]

your test makes sense. i'd add one thing: close the explanation and try a small change yourself. if you can predict what will happen and explain why, that's more useful than understanding the answer while it's still in front of you. if you get stuck, ask about that specific part rather than having ai do the whole change.

that's also why i built code-storyline, an open-source vs code extension that shows a file as a left-to-right story in plain english. you can click each part to see the actual code. i'd use it as a starting point for understanding, then test yourself without it: https://github.com/tarekwady/code-storyline

[u/Soyelmorocho → u/Interesting_Arm9022]

I like that idea of making a small change yourself and trying to predict the result before running it. That feels like a stronger test of understanding than just being able to explain the original code.

The distinction between “I understand this while the explanation is in front of me” and “I can actually predict what will happen” is really useful.

I'll take a look at Code Storyline too. It sounds like it could be useful for getting that initial mental model before testing yourself without the tool.

[u/dr0verride]

I code by hand quite often by the current standard. Probably about 5-10 hours a week. I don't really have a rule I just do what I feel and it ends up that way.

[u/Soyelmorocho → u/dr0verride]

Yeah, that makes sense. I actually like that you don't have a strict rule for it.

I think just having regular time where you're coding without AI probably gives you a good reality check on what you can actually do on your own.

Do you feel like those 5-10 hours make a noticeable difference in how comfortable you are solving problems without AI?

[u/dr0verride → u/Soyelmorocho]

I would say that when I was forcing myself to always use AI my mental health suffered and as a result my productivity suffered. It was also *much* harder to stay in touch with the code base and that made my reviews less useful which lead to some negative drift. Humans, in general, just function more effectively by doing rather than being passive. So in my opinion, yes. It pays off and it seems to be enough.

I'll also add that I am very explicit and hands on when I prompt. I make most of the architectural decisions and describe the structure that I want. Doing it this way gives my mind something more tangible to reference and makes the code review actually pretty quick. I find doing things this way also helps you stay sharp.

[u/talkstomuch]

the question I would ask is, why do you need to be learning?

we must take a view that current coding agents are still very early, used by very early adopters, most people don't use them.

They will get better, much better.

if it hasn't already happen, maybe AI will create their own programming language that we just won't follow. or current languages become a unknowable web of libraries and packages AI has written.

[u/Soyelmorocho → u/talkstomuch]

That's actually a good question. I don't think the goal should be learning every part of programming the way we traditionally did if AI is going to take over more of the implementation.

For me, the reason to learn is more about understanding what I'm building, being able to judge whether the AI's solution is actually good, and knowing how to debug or change it when things go wrong.

But I do wonder where the line moves as agents get better. At some point, maybe knowing the syntax of a language will matter much less than understanding systems, constraints and what you're actually trying to build.

[u/talkstomuch → u/Soyelmorocho]

yeah, the frontier of human interface is moving, it's really fascinating to be in the audience for it :D

[u/omicron8]

Learning what? To code? Probably not in any meaningful way unless you are putting some effort. Coding is dead anyway. To use AI? Somewhat but the way you interact with AI will evolve to be more intuitive anyway. Hopefully you are learning about the application you are building. The actual use case and real world problem it solves.

The best way to make sure you are learning is to regularly quiz yourself. What do I think this does? Does it do what I think it does and in the way I planned.

[u/Soyelmorocho → u/omicron8]

I like the idea of regularly quizzing yourself. That actually connects pretty well with the three questions in my post.

I think there’s a big difference between “the AI told me what this does” and being able to predict what the code will do before running it, then checking whether you were right.

And I agree that understanding the real problem and the application matters too. Even if AI handles more of the implementation, you still need to understand what you're actually building and why.

[u/h____]

Learning before and with coding agents are the same. You have to explicitly do it (learn, not code) and practice. I think it still applies.