My AI-assisted workflow, step by step
Everyone says AI makes you faster. Far fewer show the actual workflow. Here's mine, step by step — the loop that made a whole team faster, not just flashier.
1. I start with a scoped prompt, not a wish.
Not "build the checkout." → "Add a service that takes this validated input, does X, returns this shape. Here are the existing patterns." Vague in, garbage out — every time.
2. I let it draft, and I read every line.
The speed is real. So is the confident nonsense. I never merge code I haven't read and understood — if I can't explain it, it doesn't ship.
3. I review it like a junior's pull request.
Great junior: fast, capable, occasionally very wrong about the thing that matters. Same posture. I check the edge cases it glossed over and the abstraction it picked.
4. Tests before trust.
AI is genuinely good at first-draft tests. I use that — then tighten them around the paths users actually hit. The tests are what let me move fast without hoping.
5. I own the result.
"The AI wrote it" is not a defense in a code review or an incident. My name's on the commit. That mindset is the whole game.
Done this way, standardizing these tools across a 3-engineer team cut our delivery time by ~30% — not because we trusted the AI more, but because we reviewed it harder.
The tool is a force multiplier for judgment. If the judgment isn't there, it just multiplies the mess.
What's the one step in your AI workflow you'd never skip?