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Can AI Actually Answer Your Data Questions?

Hosted by Shreya Shankar and Hamel Husain

Wed, Jul 22, 2026

7:00 PM UTC (45 minutes)

Virtual (Zoom)

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AI Evals For Engineers & PMs
Hamel Husain and Shreya Shankar
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What you'll learn

How to eval data agents

Shreya will show you how simulate the most common failure modes and create high fidelity synthetic data (re: privacy)

How to make data agents reliable

How to provide better structure through tools, workflows and verification strategies.

Common traps when building data agents

Learn the counter-intuitive areas where data agents fail, including how different harnesses and models fail differently.

Why this topic matters

Asking business questions of your data is the hottest enterprise AI use case, and one of the hardest to evaluate. Shreya Shankar & her colleagues built a benchmark that emulates real business scenarios, replicating what trips agents up: scattered systems, messy join keys, answers buried in text. She will share strategies you can use immediately in your workflows to improve performance.

You'll learn from

Shreya Shankar

AI researcher; incoming CS Professor at Carnegie Mellon

Shreya builds open-source systems for AI-powered data processing. She is a final-year PhD candidate at UC Berkeley and, in 2027, will join Carnegie Mellon University as an Assistant Professor of Computer Science. Shreya created DocETL, an open-source system for analyzing unstructured text at scale, deployed across journalism, law, medicine, policy, finance, and urban planning. Her research has been published at top computer science venues including VLDB, SIGMOD, and UIST (including a Best Paper award), and has influenced systems at Snowflake, BigQuery, LangChain, and OpenAI. Before her PhD, Shreya worked as a machine learning and data engineer at startups. She holds a BS in Computer Science from Stanford University.

Hamel Husain

ML Engineer with 25+ years of experience

Hamel Husain is a ML Engineer with over 20 years of experience. He has worked with innovative companies such as Airbnb and GitHub, which included early LLM research used by OpenAI, for code understanding. He has also led and contributed to numerous popular open-source machine-learning tools. Hamel is currently an independent consultant helping companies build AI products.

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