No PriorsNo Priors Ep. 83 | With Rippling COO Matt MacInnis
Episode Details
EPISODE INFO
- Released
- September 25, 2024
- Duration
- 31m
- Channel
- No Priors
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
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. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Stanine Show Notes: 0:00 Introduction 0:32 Rippling’s mission and product offerings 2:13 Compound startups 3:53 Evaluating human performance with Talent Signal 13:19 Incorporating AI evaluations into decision-making at Rippling 14:56 Leveraging work outputs as inputs for models 18:23 How Rippling chose which AI product to build first 20:53 Building out bundled products 23:26 Merging and scaling diverse data sources 25:16 Early adopters and integrating AI into decision-making processes
SPEAKERS
Sarah Guo
hostMatt MacInnis
guestElad Gil
hostNarrator
other
EPISODE SUMMARY
In this episode of No Priors, featuring Sarah Guo and Matt MacInnis, No Priors Ep. 83 | With Rippling COO Matt MacInnis explores rippling’s Talent Signal Uses AI To Grade Employee Work, Not Vibes Rippling COO Matt MacInnis discusses the company’s compound-startup strategy and unveils Talent Signal, an AI product that evaluates employees based on their actual work output rather than managerial impressions. The system ingests work product data from tools like GitHub and Salesforce, combines it with HRIS data such as role and level, and produces a calibrated signal on new hires after 90 days. MacInnis argues this can surface overlooked high performers, flag struggling employees earlier, and reduce biased, vibe-based performance reviews. He also emphasizes cautious rollout, strict internal policies against AI-only employment decisions, and openness to scrutiny around bias and ethical use.
RELATED EPISODES
