Technology makes us lazy.
That's not an opinion but a fact. We can't do mental math, find addresses, or memorize phone numbers anymore. That's the...
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Point #4 nails it. But here's the catch: toy projects expose the gap between "I can prompt" and "I can debug."
The real test? When your from-scratch app throws
NullReferenceExceptionat 2 AM and AI suggests 5 wrong fixes. That's where strong typing (C#) vs weak typing decides if you sleep or not.AI writes fast. Experience knows why it breaks.
Yes, debugging is a completely different skill to master...one more people are offloading to AI
AI is definitely super helpful for developers, it’s like having a caffeinated intern who never sleeps. But let’s be honest, its biggest weakness right now is confidence. It will happily answer a question it doesn’t actually know… and do it with the confidence of someone who wrote the textbook.
And then, if you ask the same question later, you might get a completely different answer like it had a philosophical awakening overnight. Of course, I get that there are technical reasons for this, model updates, access layers, all that good stuff. Still, it can be a little wild when the “expert” suddenly changes their story.
Sometimes it feels like AI would rather improvise than admit, “You know what? I’m not sure.” And honestly, we’ve all worked with someone like that before 😄
Oh, the classical "you're absolutely right" when you confront AI
The other way I had a season with an AI and I explicitly ban it to say that. I wrote:
Stop prepending "you're right" to your answers.It answered:Understood.And it complied from then on! XDI like these advice, but I'd say that you shouldn't be in that situation in the first place. You should not rely on AI that much that you feel insecure with the programming languages. AI is great for asking questions about code, or about the API, generate code for a possible solution to evaluate a design path... It's surprising that a programmer can feel insecure without AI, taking into account the relative small amount of time passed since their appearance!
Yes, Baltasar. It's like sending someone else to the gym and then complaining when we don't see our muscles growing.
Point #8 about rubber duck debugging doesn't get enough credit. I've been doing a variation of this where I explain the problem in writing before even opening my editor - like a mini design doc. Forces you to think through the actual logic instead of just throwing code at the wall.
One thing I'd add to this list: read other people's code. Not just tutorials, but actual open source projects. Pick a library you use daily and spend 30 minutes reading through its source. You start picking up patterns and idioms that no AI prompt will teach you. It's how I finally understood how async/await actually works under the hood in JS - not from a blog post, but from reading through a well-written library.
The calculator analogy is perfect btw. You still need to know what operation to perform even if you're not doing the arithmetic yourself.
That's one of the best way to improve our coding skills. I wrote a post about it the other day.
Thanks! A good idea among many :)
being in high school and learning how to code in this ai era is tough. most of my classmates are using ai to do websites and i am here tryingto learn. very tough and thank you for this read
Building websites is everything from letting GitHub pages render your README to developing and maintaining a complex corporate website with customer login, B2B shop and database logic. It's totally legitimate to use no-code solutions to make websites. An early success might empower people or cause Dunning-Kruger delusion.
You can do this with AI (or StackOverflow) as well. Start typing, describe and refine your problem. Mind that you spend expensive tokens (AI) or risk downvoting and deleting instead of an answer, so don't post too early. Review and refine your question and try to narrow it down to a minimal reproducible example!
The most underrated "hack" in 2026: Reading the manual also saves futile and costly search engine requests.
When building projects, use descriptive variable names, meaningful comments and commit messages! Write a README and try to understand, review and maintain it. That's your own private "official documentation" of proven code examples.
Use AI where it helps, especially to get things done quickly for customers.
That's the point. AI is not intelligent. But you can be.
Further Reading
Thanks Cesar @canro91 for the insightful and actionable post. I appreciate and support your advice!
The dependency problem cuts deeper than coding skills once you're running AI in production.
There are two kinds of AI dependency worth separating:
This post nails the first one. The advice is right: ban AI long enough to rebuild the mental model yourself.
The second catches teams off guard. Session limits, model deprecations, provider outages, sudden pricing changes — any of those can take down workflows you didn't realize were fragile. The teams that recover fastest are the ones who actually understand what their AI is doing, not just that it's running.
Same underlying principle though. You can't diagnose a broken AI workflow if you never understood how it worked to begin with. The muscle memory of reading your own system — tracing what's happening step by step without a black box in the way — is what makes the difference.
The calculator analogy holds either way: you still need to know what calculation you're asking for.
Great framing. I'd add one more recovery scenario: what happens when your AI team goes down, not just your AI coding assistant.
I run 7 AI agents as my actual business operations team — they handle finance, marketing, sales, engineering, research. When I hit my Claude Max session limit and the fallback LLM wasn't calibrated, I didn't just lose a coding helper. I lost my entire operations team for 40 hours.
The recovery wasn't "go back to writing code manually." It was: which business-critical tasks need a human fallback? Which can wait? How do I triage when 50 cron jobs suddenly have no brain behind them?
The dependency isn't just on AI for coding anymore. It's AI for running the business. The recovery guide for that is very different.
Great point! AI, tokens, and credit cards are the new bottleneck
Hot take: There's going to come a point where coding by hand just isn't how things are done in the real world. Just like it's often quicker to use a calculator -- if you can do it in your head that's great, but no one is going to give you a medal (or a raise!) for doing so.
The article is great and I appreciate the tips! I'm just saying that AI will eventually be responsible for the writing the vast majority of code in professional settings, and "dependence" is going to be less a "disability", and more a simple side effect of practical reality.
Good point!
I think the framing of "AI dependency" as a problem is slightly off. We're not "dependent" on calculators — we just use them for math. The concern should be: are you using AI as a thinking substitute or a thinking accelerator?
If you can't articulate what you want the code to do before asking AI to write it, that's a problem. If you know exactly what you want and use AI to skip the typing, that's just efficiency.
The key diagnostic: can you read the AI's output and know whether it's correct? If yes, you're fine. If no, slow down.
You're right! We still need our judgment to tell whether AI is wrong
Agreed. Building stuff on your own will not only strengthen your coding skills but also allow you to better guide the AI on the next AI-aided project.
This is a true refresher! It's like in a long timeless journey, you stop, you look back, you understand what's going on and take action to being you again in the world of ai agents.
This is a comprehensive and healthy list of practices to adopt when learning a new language or concept. Adding some friction can feel like slowing down, but putting in the hard work pays dividends in the long term as it unlocks a deeper level of thinking. Thanks for sharing this guide!
Super good article to remind us that it's still a good investment to build everything on our own, not relying on tools, especially for fundamentals. Nice one!