Get ahead of quarterly planning.
Anna talked about the data team doing discovery before proposals reach the train meetings, so they arrive prepared rather than as surprise data requests.
Prototype quickly, then govern what persists.
Anna sees value in scrappy, source-connected prototypes, but not in leaving them as lasting, ungoverned dashboards.
Keep AI agents behind explicit gates.
The discussion highlighted agents missing small but critical instructions—including a child session bypassing Shane’s commit gate—and the need for tests, human checks, and coordination as parallel work scales.
“That’s not what I wanted.”
“But that’s what you asked for.”
Shane runs a one-day workshop on the Information Product Canvas, a repeatable way to gather data requirements in 30 minutes. The approach he actually uses with his stakeholders, not a textbook version that falls apart on contact with messy data and vague stakeholder requirements.
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