Step01
Set the Stage for Success
Choose the behavior the event should change, capture baseline tool usage and confidence, provision approved tools, and publish prototype data and security rules before the day.
IntermediateOperations
How to Run a Company-Wide AI 'Builder Day' to Drive Tool Adoption
Run a focused builder day that gives every function approved tools, a relevant starting track, live support, and time to produce a real prototype, then measure whether usage continues afterward.
Source episode · 28:00
How I AI: Webflow CPO Rachel Wolan's AI Chief of Staff & Org Adoption Playbookwith Claire Vo
Rachel shows sustained tool usage after Webflow builder days, then explains the cross-functional tracks, warmup, support channels, executive judging, prizes, and feedback survey behind the event.
Before you start
What you need
- Executive sponsorship and a full-day calendar block
- Approved tools with provisioned licenses
- Function-specific tracks and a simple warmup
- Support owners, judges, and prototype handling rules
- Baseline adoption data and a follow-up survey
What you’ll make
A set of demonstrable prototypes, broader confidence using approved AI tools, and clear evidence about which practices continue after the event.
Tools used
- CursorVisitCursor
AI-first code editor
Step by step
The workflow
Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.
4 steps
Step02
Make It Fun and Engaging
Create short tracks for product, design, research, analytics, and engineering, plus one warmup that everyone can finish. Staff a shared support channel with tool experts and engineers.
Step03
Measure the Impact Quantitatively
Run the day around building and showing, not presentations. Give teams milestones for problem, first working path, iteration, and demo; use judges, recognition, and prizes to keep the finish concrete.
Example prompt
Define a one-day prototype for [team]. User: [user]. Problem: [problem]. By the first checkpoint, show one working end-to-end path using only approved tools and synthetic data. Before demo time, record what worked, what failed, and the next practical use at work.
Step04
Gather Qualitative Feedback
Collect demos, reusable prompts, technical lessons, and survey feedback. Compare tool usage and confidence after one week and one month, and turn the strongest practices into recurring sessions or team standards.
Example prompt
Measure confidence before and after the event, tool usage frequency, prototypes completed, blockers, intended next use, and whether the behavior continued after one week and one month. Ask permission before attributing any quote.
What good looks like
- Participants can access the tools and starter materials before the event begins.
- Every track produces a demo or documented learning, not only a concept slide.
- Sensitive data and production systems stay outside the prototype environment.
- Usage and confidence are measured again after the initial event spike.
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After the steps
Runbook notes
How to recover when the loop fails and where human judgment helps.
Recover
If it goes sideways
- Participants lose time to licenses, logins, or local setup
- Provision accounts early, run a setup clinic, and provide a no-install fallback for every track.
- Teams choose projects too large to demonstrate in one day
- Require a narrow user, problem, and demo path, and give coaches authority to cut scope during kickoff.
- A prototype uses customer data, secrets, or production access
- Use synthetic or approved datasets, sandbox credentials, and explicit prototype data rules.
- Tool usage rises for one day and immediately disappears
- Schedule follow-up demos, publish reusable examples, assign community owners, and compare usage several weeks later.
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