Using AI to Accelerate Development Without Losing UnderstandingUsing AI to Accelerate Development Without Losing Understanding
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AI made me a faster developer.
Then I noticed something I didn't like.
I was sometimes building faster than I was learning.
I could ask AI to generate a route, build a component, structure an API, or fix an error—and suddenly the feature worked.
But “it works” isn't the same as “I understand it.”
That difference becomes obvious when the happy path breaks.
A request starts failing only under certain conditions.
Two operations touch the same data at almost the same time.
A third-party API returns something unexpected.
A bug appears somewhere between the frontend, backend, database, and the assumptions connecting them.
At that point, another prompt isn't always the answer.
You need to understand the system.
So I've changed how I use AI.
I still use it a lot.
But I make the important decisions myself:
→ Architecture → Data models → API behaviour → System boundaries → Trade-offs
Then I use AI to explain, challenge, debug, test ideas, and speed up implementation.
The goal isn't to become the developer who writes code the fastest.
It's to become the developer who understands what they're building well enough to fix it when everything stops going according to plan.
AI can accelerate the implementation.
You still have to own the system.
How do you use AI in your development workflow without letting it replace your own understanding?
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