K Srinivas Rao@sriniously
ai coding assistants make programming easier. They do. But they also make programmers worse, and not for the reasons you might expect.
The problem isn't that AI does too much. It's that it does too little of the right thing. When you use AI to generate code, you skip the most important part of programming, the thinking.
Programming isn't typing. Any decent programmer spends more time thinking than typing. The typing is just the final step, like a pianist playing notes they already worked out in their head. What makes someone good at programming is the same thing that makes someone good at any kind of problem solving, they can hold a complicated problem in their head and work through it.
This is harder than it sounds. To understand a program well enough to modify it, you have to load a lot of context into your head. You need to understand not just what each piece does, but how it fits with everything else. The more of the program you can hold in your head at once, the better you can work on it.
AI assistants prevent you from developing this skill. When AI generates code for you, you never have to figure out how all the pieces fit together. You become dependent on something else to do the thinking. It's like using a calculator for arithmetic. You can get the right answer, but you never develop number sense.
The effect is subtle at first. AI-assisted programmers often seem productive. They ship code fast. But look closer and you'll notice they have trouble debugging. When something breaks, they can't figure out why. They throw random fixes at the problem. They ask AI to generate different versions until something works.
This happens because they never learned to think in code. They learned to prompt instead. But programming is not about generating syntactically correct code. It's about solving problems. And you can't solve problems without understanding them deeply.
The good ones, the smart programmers are incredibly picky about understanding every line of code they work with. They'll spend hours reading through a codebase before making any changes. They can spot bugs just by looking at code. They know why things are written the way they are.
These programmers don't avoid AI tools entirely. They use them strategically, for tasks like writing boilerplate or reformatting code. But they never let AI do their thinking for them. They understand that the thinking is the valuable part.
The danger isn't that AI makes bad code. Modern AI actually generates pretty good code most of the time. The danger is that it produces programmers who can't think through hard problems. They can prompt AI to generate a solution, but they can't verify if it's right or modify it when requirements change.
This matters more than you might think. Programming isn't just about writing code that works. It's about writing code that can be maintained, debugged, and extended. Code that solves the right problem. Code that fits well with existing systems. These skills require deep understanding, not just code generation.
The solution isn't to not use AI tools, obviously. That would be like banning calculators. They're useful for what they're good at. But just as we still teach arithmetic even though calculators exist, we need to make sure programmers learn to think through problems without AI.
The best way to learn programming is still the same as it's always been, work on hard problems that interest you, and don't give up until you understand every piece. Use AI to handle the tedious parts, but do the thinking yourself. Because in the end, thinking is what separates programming from typing.
