AI speeds up coding, but experience determines *what* to build and *how* to break it into maintainable pieces—shifting the developer bottleneck from typing to judgment.
The story
When I tell an AI, “Ship the whole app,”
it smiles and hands me code with hidden snags
When I slice the work into crisp little parts,
the output gets calmer, fewer future nags
🟢 The problem: “If AI can code, do I still need experience?”
AI is lowering the barrier to entry. It can spit out component code, TypeScript interfaces, unit tests, even documentation stories, if you give it clear intent.
So it’s tempting to think experience is now optional, like seatbelts in a bumper-car arena.
But the data vibe is mixed: 52% of developers either do not use agents or keep to simpler AI tools, and 38% say they have no plans to adopt them. Translation, plenty of people are still navigating what this stuff is *for*.
And here’s the sneaky part: when AI speeds up coding, the bottleneck often moves. Netflix noticed that if code gets generated faster, then review, integration, and release have to accelerate too, or your “fast” code just sits around waiting on slow tests.
🟢 The solution: shift from “typing” to “judgment”
Can anyone write good software with AI? For small stuff, often yes.
For maintainable, scalable, secure software? Experience still matters, because you need the brain muscles for architecture: chunking problems, modularizing, respecting constraints, and spotting where failures like to hide.
AI is the power tool. Experience is knowing where to cut, and where to *not*. What do you want to build, a demo… or a system you can live with?
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