Turn Insights to Action in Claude Code

Hosted by Sravya Madipalli, Hai Guan, and Shane Butler

Fri, May 8, 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

Build action plans from analysis findings

Use the Close-the-Loop checklist to turn every recommendation into an owned, measurable next step.

Generate structured plans with Claude Code

Watch Claude Code take analysis findings and produce action plans with owners, metrics, and deadlines.

Stop insights from dying after the meeting

Add baselines, targets, check-back dates, and fallback plans so every recommendation has teeth.

Why this topic matters

Most analyses die after the presentation. Recommendations get a nod in the meeting and nothing happens. This lesson teaches a 6-field checklist that forces every insight into an action plan with an owner, a success metric, a baseline, a target, a deadline, and a fallback. Claude Code builds the plan live.

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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