The four-week sprint.
Most AI projects begin with assumptions. Our work begins with evidence.
Teams often commit to platforms, vendors, and production plans too early. They don’t yet know if customers want the product, the data is usable, the prediction risk is acceptable, or the business case is real. Snowball Sprint™ builds a working application and tests those assumptions before the investment grows.
The use case is still an assumption.
The sprint finds a thin, valuable slice that can be tested with real customers.
The data hasn’t been proven.
The sprint uses actual or representative data to expose feasibility, quality, and risk early.
The product hasn’t earned demand.
The sprint puts a working application in front of customers before the team scales the build.
The path to production is unclear.
The sprint reveals what must change, what can scale, and where architecture or governance comes next.
The work moves fast.
You need a system you can evaluate.
Ideate
Identify the customer problem, define a valuable thin slice, and name the assumptions to test.
Frame
Shape the product, data, workflow, prediction risk, and business case into a testable working system.
Iterate
Build with real data, test with customers, and refine the experience until the evidence is clear.
Scale
Advance, change direction, or stop. Then define what architecture, governance, and production readiness need next.
Validate the opportunity. Then design the system around the intelligence.
We prove whether an AI product deserves to move forward. It surfaces what production requires before it becomes hidden risk.
Workflow and decision architecture
Clarify how work moves, where decisions occur, and what AI may recommend or perform.
Authority and governance
Define oversight, intervention, escalation, accountability, and recovery conditions.
Enterprise readiness
Translate a validated product into an operating system the organization can sustain and evolve.
What the sprint needs from your team.
Access to accountable people
The people who own the problem, the work, and the consequences.
Access to the workflow
Real steps, real handoffs, real exceptions, and the places where work actually breaks.
Access to useful data
Enough information to test behavior in conditions that resemble reality.
Time to make decisions
A committed working group that resolves ambiguity instead of postponing it.
Permission to learn
The sprint must be allowed to reveal that the original assumption was wrong.
Decks don’t run. Working systems do.
Certified UX for AI Professional
uxforai.com · 2026
Snowball Sprint™ was created by Greg Nudelman and is delivered by Ray Butler as a certified practitioner.