Case Study · July 17, 2026 · 2 min read

Fifteen Minutes at a Time

At Avidity the AI policy was written by Legal, IT, and my team. Then I personally trained more than half the company on it, fifteen minutes at a time, because a policy that cannot be understood is functionally not a policy.

ScopeThe Re-Aligned Enterprise InterventionEnablement OutcomeTranslational capacity FunctionCompany-wide EvidenceFirsthand operator account

The facts behind A Policy Is Only as Good as It Is Understood: the enterprise rung, from the inside, at Avidity.

What happened

At Avidity, where I was the VP of AI, Legal, IT, and my team wrote an AI policy we believed in: the data tiers and where each was allowed to go, the position that there is no AI work product, and practical guidance on everyday questions. Writing it was the part everyone expects to be hard. It was not.

The hard part was that a policy is worthless until the people it governs understand it well enough to act. So I taught it personally, to more than half the company, hundreds of people, in fifteen-minute increments. Not a recorded module or a memo from Legal, but in the room, walking each group through what the tiers meant for their actual Tuesday. Fifteen minutes at that scale is a large amount of a VP’s calendar, and spending it was the message: this mattered, and the person accountable for it would answer your question to your face.

What it produced

The teaching went both ways. Every session surfaced things the policy had not anticipated; I turned them into FAQs and carried them back to refine the policy. It got better because I was explaining it.

At first almost everyone defaulted to responsible conservatism, not using the tool to be safe, which looks like caution and is really just slowness. Teaching the reasoning, where the real risk lived and where it did not, broke the freeze, and people began to blossom. The person who would not touch a transcript in week one was, a month later, rethinking how their team ran meetings. Eventually it became self-sustaining: AI-policy acceptance went into standard onboarding and held, because a new person with a question could ask the colleague at the next desk. The organization could teach itself, which is the quiet signal that adoption is real.

The conditions that made it work

  • Senior time, spent visibly. It had to be taught by someone senior enough that the hours themselves carried the message. If no one senior will spend them, you have a PDF, not an enablement plan.
  • The questions refine the policy. The rule got stronger because it was said out loud to skeptical people who found its weak spots fast.
  • Responsible conservatism is information-hunger, not resistance. The answer was never pressure. It was information, delivered by someone they trusted.

The argument for why a policy has to be taught, not shipped, is in A Policy Is Only as Good as It Is Understood.

How this was measured. The reach (more than half the company) and the adoption arc are the operator’s firsthand account; behavior change was observed in the room, not independently or quantitatively measured. A directional firsthand account from a single organization.

Cheers,
-Titus

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