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Browse published episodes on AI workflows, safety, compliance, and implementation. Clearly labeled program previews show what is planned but not yet recorded. Real practitioners on camera. No synthetic presenters, no synthetic voices, no generated footage.
Episode 000 is being prepared with video, transcript, and source bibliography before it appears here.
These pages describe the intended audience, decision, content, and practical takeaway. They do not represent recorded or published episodes.
Start with the first listed preview: Before Go: Anatomy of an Async GLP-1 Launch Review.
How should a team separate launch momentum from the evidence needed for a bounded Go, Hold, or Refuse record?
Intended takeaway
The planned artifact is a question file that keeps owners, open items, confidence, expiry, and flip conditions visible.
When does an intake workflow move from collecting answers to influencing, constraining, directing, or acting?
Intended takeaway
The planned artifact is a responsibility and action ladder for locating where decision rights change.
Can the team reconstruct what happens from a synthetic failure trigger through detection, stop, fallback, recovery, and a bounded decision?
Intended takeaway
The planned artifact is a failure-path deck that connects each break to evidence, an owner, and the next review question.
How can a team translate a public board question into a portable evidence question while keeping unresolved local details with the right owner?
Intended takeaway
The planned artifact is a two-layer question file that keeps source wording, limits, evidence, and local follow-up separate.
What must the team define and test before a polished demo can inform a Buy, Build, Integrate, or Refuse call?
Intended takeaway
The planned artifact is one evidence rail for comparing paths, recording open items, and naming the conditions that would change the call.