Develop North Star Metrics with AI

Hosted by Sravya Madipalli, Hai Guan, and Shane Butler

Fri, May 29, 2026

7:00 PM UTC (1 hour)

Virtual (Zoom)

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Automate AI Evals with Claude Code
Shane Butler
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What you'll learn

Pick a North Star that captures customer value

Use 7 criteria (customer value, revenue, gaming resistance, actionability) to evaluate any metric.

Decompose your North Star using BDEF

Break any North Star into 3-5 input levers across Breadth, Depth, Efficiency, and Frequency.

Use Claude Code to evaluate and analyze metrics

Apply a custom AI prompt to score your metric, then watch Claude Code build a full North Star report.

Why this topic matters

Most teams track metrics that look impressive but don't drive decisions. AI makes it easier to measure everything, which makes it easier to measure the wrong things. Learn the North Star + Inputs framework used by Airbnb, Slack, and Netflix to focus on what actually matters, and see how AI accelerates evaluation and analysis without replacing judgment.

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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