Analyze Metric Trade-offs in Claude Code

Hosted by Sravya Madipalli, Hai Guan, and Shane Butler

Fri, Apr 24, 2026

7:00 PM UTC (1 hour)

Virtual (Zoom)

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Build AI Analysts in Claude Code
Shane Butler, Sravya Madipalli, and Hai Guan
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What you'll learn

Pair success metrics with the right guardrails

Learn which guardrail to attach to common success metrics so you catch trade-offs before they ship.

Detect trade-offs in experiment results

Know when a win on your success metric is hiding a loss. Conversion up but AOV down. Activation up but churn spiking.

Automate guardrail checks in Claude Code

Watch Claude Code analyze an experiment, flag guardrail violations, and surface the trade-offs automatically.

Why this topic matters

Every success metric has a shadow metric that can go wrong. Conversion up but AOV down. Activation improved but churn spiking. Most teams celebrate the win and miss the trade-off. This teaches how to pair success metrics with guardrails and demos Claude Code flagging violations automatically.

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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