Six hours in the room, five hours of building. You leave with software that runs and a written rule for what your AI is never allowed to touch.
Dates are being confirmed. Tell us which edition you want and we will hold you a seat.
Same spine every time: build in the morning, govern in the afternoon, sprint and demo before the hard out at 16:00. What changes is whose rules we work to and what you take home.
What differs per edition is the room, the afternoon governance module, the sprint briefs, and the take-home document.
Owners and operators of small and mid-sized businesses, mixed industries.
Vendor risk: what to ask before an AI tool touches your data.
Take home: A one-page AI use policy covering what it may touch, what it may never touch, and who signs off.
Practice managers, clinic administrators, revenue cycle and prior authorization leads, small provider groups, digital health founders.
Business associate agreements that explicitly cover AI training, model inputs and downstream use.
Take home: A PHI boundary map naming which workflows may see identified data, which may see de-identified data only, and which may see neither.
Solo practitioners and small firm partners, legal operations, paralegals, in-house counsel of one.
ABA Formal Opinion 512 and its six duties.
Take home: A firm AI policy mapped to the six duties, plus an engagement letter clause and a citation verification protocol.
RIA principals and chief compliance officers, broker-dealer supervision and operations, community banks, credit unions, independent lenders, insurance agencies, fintech founders.
FINRA's position that generative AI creates no new obligations, and existing ones simply apply.
Take home: A supervision and archiving map, plus a written AI description for client materials.
Owner-operators and very small teams: shops, trades, studios, restaurants, local services, and anyone who does the admin themselves after hours.
The one rule that protects your customers: what your AI may never see.
Take home: A one-page AI use rule for your business and a checklist for the next tool you sign up for.
People learning AI for themselves: career changers, retirees, students, parents, hobbyists, and anyone who wants to build something of their own rather than watch someone else do it.
Your own data: what to share with an AI and what to keep to yourself.
Take home: A personal AI rulebook and a working project you can keep building at home.
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