In this episode of the Building AI Products podcast, I interview Sasha Laundy, who was the Director of Data Science at Warby Parker.

Sasha is one of those wonderful high-IQ, high-EQ, left-right-brained people who's both super technical and a great people manager.

At Warby Parker (or "Warby" for those in the know), she ran a centralized team that did statistical modeling, BI training and analyst support, and machine learning.

In this episode, we discuss:

👓 Shape Up, a framework for shipping in six-week cycles that turns out to be perfect for data science teams

👓 Powerful questions to build the right thing for stakeholders, especially stakeholders who don't "speak data"

👓 Why everyone asks for a dashboard, but nobody actually needs one

👓 How a centralized team of data scientists can work with data analysts embedded in vertical business teams

Show links:

• Find Sasha's coaching practice here: https://sashalaundy.com/
• Basecamp's book on the Shape Up framework, by Ryan Singer: https://basecamp.com/shapeup
• Sasha's consulting company, Polynumeral, published a book called Thinking with Data (by Max Shron) that talks more about working with stakeholders and scoping projects: https://www.oreilly.com/library/view/thinking-with-data/9781491949757/

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AI hype is outrageously high. Michal Bloch Ron, former PM at Microsoft AI and Teams, helps us cut through the hype by sharing what learned about grounding AI products in concrete user needs. Michal's first role as a PM was to find product applications of the Cortana speech model and text model — one of the most widely-used AI technologies from before the advent of transformers. Currently spending a year at the Stanford GSB, she also gives us a sneak preview of the research she's doing on the future of productivity.

Follow Michal Bloch Ron on LinkedIn: https://www.linkedin.com/in/michal-bloch-ron-3395721b/

Welcome to Building AI Products, a practical podcast for people who build AI and data science products. In this show, we'll interview the folks in the trenches who are discovering what's working and what's not as they design, build, and ship AI products that touch people's lives.