AI can generate code faster than ever, but if you're not steering
AI can generate code faster than ever, but if you're not steering, you're not shipping.
I've tested what happens when you let AI do most of the coding.
At first, it feels magical: Boom, functions, classes, entire APIs scaffolded in seconds.
But the deeper I went, the more I realized: • Fast code ≠ good code. • Code generation ≠ system design. ...a car with beautiful fresh paint job but a rotten engine.
Here's the reality: You spend more time managing AI than coding. It's like working with an unfocused offshore team, endless instruction, vague outputs, and surprises everywhere.
There's no mental model of the project. Just disjointed blocks. It works until you try to debug or extend it, and then the chaos reveals itself.
Code quality is inconsistent. You'll get functional snippets, but conventions break, cohesion vanishes, and technical debt compounds fast.
But it's not all bad, AI shines at: • Self-contained utility functions • Boilerplate scaffolding (routing, forms, API wrappers) • Inline edits (tab-complete a change and replicate it across sections)
Where it fails is context. AI doesn't know your architectural intent. It doesn't grasp business logic, scalability, or long-term maintainability.
Bottom line: You should still own the codebase, not just the prompts.
The most effective developers today don't outsource the thinking to AI. They use it to accelerate execution after the thinking is done.
AI is your power tool, not your architect. Use it with direction, or risk building something you can't even explain.
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