AI tools in the team
Review errors −30%, research coverage 98%, knowledge-sharing ×3.
Today I'd do it this way
Rolling out AI tools to a design team is no longer about licenses and training. It's about configuring skills around the team's actual workflow + measuring baseline → new metric in 6 weeks. The selection and adoption itself compresses from 3 months to 3 weeks.
tool-rollout-playbook
In progressTeam audit + skill configuration + before/after metrics.
- 12-question audit: where the team loses time, what's automatable with skills
- Baseline measurement on 5 metrics before rollout
- 6-week tracker with 'continue / roll back / pivot' triggers
How it was done then
Summary
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Designers were getting tight deadlines with no time for research or proper testing. I mapped where exactly time leaked and worked with the team to pick a focused AI toolset — Mobbin for UX references, Pathway for fast research, AI tools for product and graphic design.
After rollout: review errors down 30%, research coverage up to 98%, knowledge-sharing initiatives tripled. The team shifted from "ship fast" to "ship well".
What I'd do differently today
Today I wouldn't buy a SaaS stack. I'd write Claude Code skills for each designer — design-review agents reading their own Figma frames via MCP, research-prompts generating interview guides for specific products, pattern-analyst scanning flows against the design system. SaaS gives an averaged tool. Skills give designers a lever they configure for themselves in one evening.