No Priors: Artificial Intelligence | Technology | Startups
Using AI to evaluate employee performance with Rippling’s COO Matt MacInnis
At this moment of inflection in technology, co-hosts Elad Gil and Sarah Guo talk to the world's leading AI engineers, researchers and founders about the biggest questions: How far away is AGI? What markets are at risk for disruption? How will commerce, culture, and society change? What’s happening in state-of-the-art in research? “No Priors” is your guide to the AI revolution. Email feedback to show@no-priors.com.
Sarah Guo is a startup investor and the founder of Conviction, an investment firm purpose-built to serve intelligent software, or "Software 3.0" companies. She spent nearly a decade incubating and investing at venture firm Greylock Partners.
Elad Gil is a serial entrepreneur and a startup investor. He was co-founder of Color Health, Mixer Labs (which was acquired by Twitter). He has invested in over 40 companies now worth $1B or more each, and is also author of the High Growth Handbook.
Show Notes
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In this episode of No Priors, Sarah and Elad sit down with Matt MacInnis, COO of Rippling, to discuss the company’s unique product strategy and the advantages of being a compound startup. Matt introduces Talent Signal, Rippling’s AI-powered employee performance tool, and explains how early adopters are using it to gain a competitive edge. They explore Rippling’s approach to choosing which AI products to build and how they plan to leverage their rich data sources. The conversation also delves into how AI shapes real-world decision-making and how to realistically integrate these tools into organizational workflows.
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Show Notes:
Introduction
Rippling’s mission and product offerings
Compound startups
Evaluating human performance with Talent Signal
Incorporating AI evaluations into decision-making at Rippling
Leveraging work outputs as inputs for models
How Rippling chose which AI product to build first
Building out bundled products
Merging and scaling diverse data sources
Early adopters and integrating AI into decision-making processes
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