Mathematical validation engines and intelligence repositories for technical product leadership.
As a PhD in Systems Engineering, I prioritize statistical power over anecdotal evidence. This engine calculates 95% Confidence Intervals using standard error distributions to determine if product discovery findings are ready for engineering commitment.
In high-velocity AI and Defense environments, "guessing" is a liability. By establishing an 80% lower-bound threshold for task success, I saved an estimated **$200K in development rework** across a single 60-day rapid validation sprint.
Evidence: 4/5 participants failed to complete authentication during initial sandbox testing.
Evidence: Qualitative feedback indicates SOC operators lose trust when UI lag exceeds 200ms.