Whimsey uses a five-stage method to choose the right problem, align the people who own it, prove the solution with real users, and scale only when the evidence supports it.
Whimsey starts with the business decision, workflow, or outcome that needs to change. We document the baseline, affected users, available data, constraints, and the measures that will show whether AI is the right answer.
Before anything is built, Whimsey names the executive sponsor, business owner, end users, data and technical owners, and any legal, security, or compliance reviewers. The group agrees on responsibilities, risks, decision rights, and the threshold for proceeding.
Whimsey builds the smallest useful system that can test the core assumptions. The proof of concept uses representative data and a defined evaluation set to measure quality, speed, cost, safety, and fit with the actual workflow.
The people who will use or approve the system try it on real work. Whimsey collects structured feedback from users and subject-matter experts, compares it with the agreed measures, and adds failure cases to the evaluation set.
Whimsey fixes the failure modes, hardens the system, integrates it with existing tools, and establishes ownership, monitoring, support, and cost controls. Rollout expands in stages only after the production criteria are met.
Data permissions, security, legal review, model risk, auditability, and human escalation are addressed throughout the work—not added after the prototype.
Use the free 30-minute strategy session to identify where this method should start.
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