Most AI governance conversations stall at the policy level — frameworks everyone nods along to but nobody knows how to apply to their actual use case. This tutorial fixes that. You'll bring a real (or sample) AI use case from your organization and take it end-to-end: build a live blueprint of the initiative, layer in real context through guided questions, run it against a customizable risk framework grounded in standards like NIST AI RMF and ISO 42001, and generate the guardrails and policy-as-code output your engineering team would actually need to build against. You'll leave with a working risk profile, a starter framework you can adapt for your own org, and a takeaway deck summarizing what you built — ready to bring back to your team. Built for AI/ML engineers, risk and compliance leads, and anyone accountable for getting an AI initiative through governance without slowing it to a crawl. No AI governance background required — just a use case and a laptop.