Notes from building an AI design collaborator · part 3
I turned my design process into a dozen small skills, not one giant prompt
· 4 min read
The first version of my design workflow was one enormous prompt. Thousands of words describing every step of how we design. I was pretty proud of it. It held together for about three steps and then quietly fell apart.
Not with an error. It failed the way a big prompt always does. The model lost the thread halfway down, blended two steps into one, skipped the one in the middle, and handed me something that looked like process but wasn't. And I couldn't fix it, because touching one part broke three others. One block of text, no seams.
The deeper problem was worse than maintenance. A single prompt gave the AI nowhere to stop. It ran from requirements straight to a prototype in one breath, sailing past every point where a human should have said "wait." It was automating the exact thing I'd promised to keep human.
Think of it as a team, not a prompt
The fix was to stop treating it as a prompt and start treating it as a team. A team isn't one person holding the whole job in their head. It's small roles with clear handoffs, and a check before the next person picks it up. Obvious if you've built software. It wasn't obvious to me, and I learned it the slow way, watching that giant prompt collapse under its own weight.
So I cut our process into its actual steps. At Xflow that's nine of them. Requirements, research, user stories, information architecture, lo-fi wireframes, a validation pass, UX copy, prototype, and the handoff into Figma.
Each step got its own skill. A small file that knows one job. What it reads, what it makes, when it's done. On top sits a thin orchestrator that doesn't know how to do research or draw a wireframe. It only knows the order, that research comes after requirements, and hands off between the skills.
The part that actually mattered
Three things came out of the split. The first two I expected. I can rewrite the research step without touching the other eight. And I can run one step on its own to check it still behaves.
The third one is the whole point. Every skill ends at a checkpoint. The AI makes its thing, stops, and asks. Requirements done? It shows me and waits. I say yes, and only then does research start. The gates aren't a nicety. They're where the judgment lives. It's the augment-don't-automate rule turned into structure, because the AI physically can't roll past a decision when the step ends right before one.
The small thing that made it feel like a collaborator
There's a little state file for each project. Which steps are done, what's approved, what's next. Sounds boring. It's the thing that flipped this from a tool into a collaborator.
Because now I can shut the laptop mid-flow, come back a week later, and the AI reads that state and picks up exactly where we stopped. No re-explaining, no "remind me where we were." If you read the earlier post, this is the re-explaining tax finally paid off. The process remembers itself.
What does one step look like? Take wireframes. The skill reads the approved information architecture and the real product, the captured HTML from the honest-design post, then builds grayscale wireframes by editing that real page instead of inventing a layout. It stops at its gate and offers to iterate. Read context, do one job, stop, hand off. Every skill has the same shape.
You don't need nine skills and an orchestrator to start. Take the longest prompt you use today and find the first natural seam, the spot where you'd genuinely want to check the output before going on. Cut it there. Put a plain "does this look right before I keep going?" between the two halves.
That's your first gate. You just turned a monologue into a workflow.
Part of a series on building an AI collaborator for our design team at Xflow. Each post stands on its own, and I'll link the rest as they go up.
Earlier: I gave the AI my design process, not my design decisions.
- ai
- design-process
- agents
The rest of Notes from building an AI design collaborator
- 1. I stopped describing my product to AI. I just gave it the HTML.
- 2. I gave the AI my design process, not my design decisions
- 4. I built a free tool that gives your AI your real product
- 5. I taught the AI to push designs into Figma. Then it quietly stopped.
- 6. We rebuilt our Figma design system out of the code, not the other way round
- 7. We ran our design process on itself, and it broke in useful ways
- 8. How do you teach an AI your taste?
- 9. It worked great on the smart model. Then I ran it on a cheaper one.
- 10. The AI told me our brand colour with total confidence, and it was wrong
- 11. A screen list lies. I found a whole feature I didn't know we shipped.
- 12. Our documentation updates itself, because updating it is the AI's job
- 13. I sat down to turn my workflow into a swarm of agents. Most of it refused.
- 14. Every modal in our app shared one URL. Our analytics couldn't tell them apart.
- 15. My AI's rules only worked because one tool bothered to read them
- 16. Six designers, one GitHub account, and a script that saves us from ourselves
- 17. "Out of scope" usually means "we'll repaint this in six months"