Claude Code 101: Ground Claude in Your Business Data

Hosted by Shane Butler, Sravya Madipalli, and Hai Guan

Wed, Sep 2, 2026

5:00 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

Write down what your metrics really mean

Turn fuzzy terms like "active user" or "churn" into plain definitions Claude can apply the same way every time.

Give Claude your tables and terms

Point Claude at your schema, key tables, and business glossary so it stops guessing what your data means.

Get answers that match how you actually work

Watch answers go from generic to grounded once Claude knows your metrics, filters, and edge cases.

Keep the context from going stale

Set up a simple file so your definitions live in one place and stay current as your business changes.

Why this topic matters

AI does not know your business until you teach it. Ask a fresh model about your numbers and it guesses what "active" means, invents a table name, or answers the wrong question. The fix is not a better prompt every time, it is giving Claude your context once: your tables, your terms, and what your metrics mean. This session shows you how, live, and you leave with a starter kit for your own setup.

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.

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