Learn How to Run and Assess Experiments with AI

Hosted by Sravya Madipalli, Hai Guan, and Shane Butler

Wed, Mar 4, 2026

8:00 PM UTC (30 minutes)

Virtual (Zoom)

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AI Analytics for Builders
Shane Butler, Sravya Madipalli, and Hai Guan
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What you'll learn

Running experiments with a clear, decision-focused framework

Learn a practical framework to design experiments that are aligned to real decisions, not just statistical outcomes.

How to run experiments using a clear, decision-led framework

Use AI to review experiment setup, metrics, assumptions, and results to assess trustworthiness and actionability.

Identify gaps and risks before acting on experiments with AI

Learn how AI helps surface design flaws, metric issues, and interpretation risks, to know when to ship, iterate, or stop

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Why this topic matters

Running experiments is not just about detecting statistical significance. It is about making the right decision with confidence. Strong experimentation requires applying a clear framework to design tests, assess validity, and interpret results in context. This lesson teaches that framework and shows how to use AI to practice applying it, assess execution quality, and improve decision-making.

You'll learn from

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.

Shane Butler

Principal Data Scientist at Ontra

Shane Butler is a Principal Data Scientist at Ontra, where he leads 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.

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