Artifact: Riskiest-Assumption Triage — Kestrel AI Suggestions

The four big risks triaged for "AI auto-schedule suggestions" -- exercises co-06. Kestrel is a fictional product; every quoted number, question, or finding here is an illustrative, constructed example, not real data or a real transcript.

• Value risk: will managers actually want and trust a suggested schedule enough to act on it? Unconfirmed -- interviews so far only established the underlying pain (scheduling takes 40-60 minutes), not demand for an AI-generated answer to it.
• Usability risk: can a manager understand and quickly edit a suggested schedule? Lower uncertainty -- Kestrel already has an editable schedule grid; a suggestion just needs to pre-populate it.
• Feasibility risk: can the team generate a legal, conflict-free, availability-respecting schedule automatically? Real but well-understood -- constraint-solving for shift scheduling is a known, solvable problem.
• Business-viability risk: does this justify its build cost given Kestrel's pricing model? Depends entirely on the answer to the value question above.

Riskiest, chosen first: value risk -- it's the most uncertain, and every other risk (and the viability question) is downstream of it.

Cheapest test: a concierge (Wizard-of-Oz) pilot with 5 managers -- a human manually builds a "suggested schedule" each week and presents it as if auto-generated, then tracks how many managers actually use it versus rebuild from scratch. Costs a few hours a week for 5 managers, no ML engineering required.