When I first tried AI coding, I was bored out of my mind. I’d type in a prompt… and think ‘guess I’ll wait?’ A minute later, some half-baked code would appear. I’d ask for a refactor. More waiting. Another tweak. More waiting. Eventually I’d close the tab and move on.
When the Magic Trick Falls Flat
The hype told us AI would be like waving a wand: type a prompt, get production-ready code. So when the output is clumsy, we don’t ask ‘What did I miss?’—we jump straight to ‘This thing is dumb.’
You’re not alone if you’ve felt that way—nearly half of developers don’t trust AI’s accuracy according to the 2025 Stack Overflow Survey.
AI is just a tool—am I the problem here?
Here’s the shift: AI isn’t magic. It’s a tool. And tools only become powerful once you learn how to use them. These days, I’ll hash out a technical plan chatting with AI—what the interfaces look like, where the code should live, how the algorithm should work. Once the plan feels solid—something the size of a PR milestone—I send it off. The agent spends twenty minutes or more grinding through implementation while I'm free to move on to something else. That’s when AI stopped boring me and started being empowering.
Are you delegating the thinking?
I'll quote my colleague Mat Brown
We shouldn’t merely give the AI a goal; we should describe the code we want to see at the level of individual functions, data structures, control flow structures, and so on. “Use detailed prompts” is commonplace advice for users of AI tools, but this goes beyond optimizing the AI’s output. Our prompts should be detailed because we shouldn’t delegate the thinking to the AI.
Tell the AI what code you want it to write. That oughta fix most concerns of code quality.
Stop Babysitting, Start Leading
Now I want to challenge you. If you’re prompting AI to refactor a few lines at a time, you’re babysitting. This is the uncanny valley you must leave!
Your goal is to get your agent to “one-shot” a large chunk of work independently over a meaningful period of time. Aim for at least 20 minutes.
If it fails? Don’t patch its mistakes, jump on git reset --hard. Do it as often as you need.
Ask yourself: what context was missing? Can I update AGENTS.md, add some rules, or just refine my prompt with more clarity? Do those edits and start over. Don't give up until that code output is close to perfection.
You'll find yourself in no time preparing much better prompts. And you'll find your agent much smarter.
Determinism Always Wins
One more tip: AI is probabilistic. Request deterministic workflows whenever you can. For example: Codemods, other AST transformation, linting rules, a small jq command or even a grep/sed combo, are predictive operations.
You can ask the agent to generate the script, review it, and then run it with confidence.
Don’t Forget the Craft
Once the AI has cranked out code that's complete and well architected, ditch the prompts and dive back into your IDE. Prompting to refactor gets you back into babysitting mode. It's slow and expensive.
At that point, edits should be minor and simple. Don't overthink it, grab that IDE, get in the flow. Use your uniquely human taste and judgement to shape the final code.
That last 10% of engineering—the craftsmanship—still belongs to us.
Your Move
Silence the hype, there's no magic. If you treat AI as a tool that gets better the more you learn to use it, you’ll find yourself less bored and more empowered. Don’t settle for babysitting. Push AI to work for you, reset when it fails and iterate until you improve. Keep the final touches for yourself; that’s where the fun lives.
Top comments (1)
This lives rent free in my head since I first read it.