Trust Your AI Analytics: Know When the Number Is Right
Part of Agentic Analytics: Validation and Context
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Hosted by Shane Butler, Sravya Madipalli, and Hai Guan
Wed, Oct 14, 2026
5:00 PM UTC (1 hour)
Virtual (Zoom)
Free to join
Go deeper with a course

Wed, Oct 14, 2026
5:00 PM UTC (1 hour)
Virtual (Zoom)
Free to join
Go deeper with a course

What you'll learn
Spot the confident but wrong answer
Run the checks that need no answer key
Match the rigor to the stakes
Decide when the number is good enough to ship
Why this topic matters
You'll learn from
Shane Butler
Co-founder, AI Analyst Lab
Shane Butler is a Co-Founder of the AI Analyst Lab. Previously he led evaluation strategy for AI product development in the legal tech domain. He has more than ten years of experience in product data science and causal inference, with prior roles at Stripe, Nextdoor, and PwC. Shane is also the co-host of the AI podcast Data Neighbor, where he interviews product, data, and engineering leaders who are pioneering the next generation of data science and analytics in an AI-driven landscape.
Sravya Madipalli
Senior DS Leader (Ex-Microsoft)
Sravya Madipalli is a Senior Manager of Data Science with 14+ years of experience helping teams make better decisions with data. She has built and led data science and product analytics teams at Microsoft, eBay, Nextdoor, and Superhuman (prev. Grammarly), working closely with product, engineering, marketing, and leadership. Her expertise spans experimentation, metrics design, modeling, analytics, and translating complex user behavior into clear, actionable insights.
Hai Guan
Head of Data at Ontra, Ex-LinkedIn
Hai Guan leads the data organization at Ontra, the leading legal tech AI solutions for private markets. He previously led Data Science & Analytics at LinkedIn, Nextdoor, Pinterest, and Meta. He's spent a decade teaching product development teams how to ask questions that actually drive decisions—and now teaches how to combine that judgment with AI to move 10x faster.