Placeholder text. The final essay is still being written.

Every team I talk to is moving faster than it was a year ago. Code gets written in minutes. Designs come back in an afternoon. Release notes grow longer each month.

What I hear far less about is whether any of it is better. Speed is easy to measure, so it is what we report. Quality is harder to see, so it slips quietly.

What we measure is what we get

If the dashboard shows tickets closed and features shipped, teams will point AI at volume. That is not a failure of the tools. It is a failure of what we ask them to do.

Speed is a tool. Quality is the goal. Confusing the two is how good teams ship worse work sooner.

The fix is simple to say and hard to do: for every speed measure, add a quality measure next to it, and give someone the job of defending it.

Design should hold the bar

Design is well placed to be that someone. We already think in terms of the person on the other end. When AI saves us time, the question for design leaders is where that time goes next: more output, or better output.

Drafted with Claude, shaped and edited by Amit Dangwal.

Push back.

This is a point of view, not a verdict. If your team has made AI faster and better at the same time, I want to hear how.

Tell me where I'm wrong

What would change my mind

  • Evidence that teams using AI heavily are seeing fewer incidents, not more
  • Quality measures that improve as fast as speed measures
  • Users saying the products got better, not just more frequent