How AI cut our delivery time by ~30% — and why it wasn't the code
I cut my team's delivery time by ~30% using AI — but not the way most people think.
Everyone's talking about AI writing code. The real win wasn't the code. It was everything around it.
Here's what actually moved the needle when I rolled Claude Code + Cursor into our daily workflow:
- Prompting conventions, not vibes. We standardized how we ask — context, constraints, examples — so output was consistent across the team, not a lottery.
- AI-assisted code review. A first pass before human review caught the boring stuff (edge cases, naming, missed tests) so engineers spent their time on architecture, not nitpicks.
- Killing boilerplate. Test scaffolding, TypeScript types, repetitive CRUD — generated in seconds, freeing hours for the hard 20%.
And where it's bad? Architecture decisions and debugging novel issues. AI confidently suggests wrong things — you still need engineers who know when to say no.
The result: ~30% faster delivery, without dropping quality (we held 95% test coverage the whole time).
AI didn't replace the team. It removed the friction so the team could do the work that matters.