Design Metrics That Don't Lie with AI

Hosted by Hai Guan, Shane Butler, and Sravya Madipalli

Wed, Feb 18, 2026

6:30 PM UTC (45 minutes)

Virtual (Zoom)

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151 students

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

Distinguish vanity metrics from decision metrics

Identify metrics that create action vs. those that just look good in reports

Apply the Metric Spec Framework

Transform vague success criteria into precise, measurable specifications that AI can operationalize with confidence

Validate metric quality with analytical judgment

Master the workflow to define metrics with AI, sanity-check edge cases, and know when your metrics tell the truth

Join AI Builders Slack Community. Link: bit.ly/ai-connect

Learn Agentic Analytics workflows and AI Eval design. Get feedback on what you’re building from other AI builders.

Why this topic matters

Most teams track metrics that look impressive but drive little decisions. AI makes it easier to measure everything - which makes it easier to measure the wrong things. The gap between high performers isn't data literacy; it's metric judgment. Learn the framework that helps you define what actually matters, so you can trust your metrics to guide real product decisions.

You'll learn from

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.

Sravya Madipalli

Senior Manager, Data Science @Superhuman (Prev. Grammarly)| 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.

Previously at

Ontra
Nextdoor
LinkedIn
Pinterest
Meta

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