The CTO Podcast with Fexingo · 2026-07-10 · 11 min
In episode 103 of The CTO Podcast, Lucas and Luna explore the architectural overhaul behind Spotify's podcast recommendation system. They break down how Spotify moved from a music-first collaborative filtering model to a neural network that understands spoken content, processes 500 million daily listening events, and serves 100 million podcast listeners. The conversation covers the shift from sparse audio features to NLP embeddings, the decision to abandon user-item matrices for two-tower neural nets, and how the team solved cold-start problems for new shows. Lucas explains why podcast recommendations require fundamentally different engineering than music, and Luna challenges whether personalization trades off against serendipity. A focused look at one of the most complex recommender systems in the world. #Spotify #PodcastRecommendation #RecommendationEngine #MachineLearning #NeuralNetworks #NLP #AudioEmbeddings #CollaborativeFiltering #ColdStartProblem #Personalization #TwoTowerModel #Technology #Business #FexingoBusiness #BusinessPodcast #CTOPodcast #TechLeadership #EngineeringArchitecture Keep every episode free: buymeacoffee.com/fexingo
Other episodes covering the same guests and topics, from across The B2B Podcast Index.
Episode 40: The Economic Reality of AI: Friction, Talent, and the Future of the FirmHigh Signal · on natural language processing97 / 100
CMMC Is an HR Problem, Not an Enclave Problem - Here's the ProofSecure Talk Podcast · on natural language processing95 / 100
Unlocking Venture Growth Equity in AI: Al Tarar and Rizwan Muhammad of Quartus Capital PartnersATLalts · on natural language processing85 / 100
62: How an ALS Diagnosis Inspired an AI Companion (with Kirstin Maurer)AI Product Leader · on natural language processing80 / 100
What Customers DO Tells You More Than What They SAYColorado Tech People · on natural language processing80 / 100
The CXLive! Episode 98: The Insight Flywheel: Making EBC Conversations Count in The Age of AI with Dmitry RisukhinThe CX Live! · on natural language processing78 / 100
How Airbnb Rebuilt Its Search for 100 Million Listings72 / 100How GitHub Migrated 100 Million Repositories to a New Storage Engine76 / 100How Dropbox Rebuilt Its Sync Engine for 700 Million Users85 / 100How Skyscanner Migrated 300 Microservices to Event-Driven Architecture85 / 100How Palantir Rebuilt Its Foundry Ontology for Government AI Deployments85 / 100