Retrieval After RAG: Hybrid Search, Agents, and Database Design — Simon Hørup Eskildsen of Turbopuffer
Turbopuffer came out of a reading app. In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive…
We score an episode from what we can actually measure — its reach and engagement, what listeners say about it, and what it covers. We don't have those signals for this one yet, so it doesn't get a number.
Buzzmeter says it's buzzing across platforms — the Hive Vote says whether the people who actually listened liked it.
Rate this episode
Add your vote to the Hive — listeners rate every episode after they finish.
- No reviews yet — be the first.
More from Latent Space: The AI Engineer Podcast
See all episodes →
64%🔬Scaling Past Informal AI - Carina Hong, Axiom Math
34%🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)
Runway’s WorldPrompt and the Engineering of Real-Time Worlds
Similar episodes from other shows
More like Latent Space: The AI Engineer Podcast →
The evolution and promise of RAG architecture with Tengyu Ma from Voyage AI
Data augmentation with LlamaIndex
Building Search for AI Agents with Exa CEO Will Bryk
#327 Baris Gultekin: The Next Phase of AI - Agents That Understand Your Company's Data
One great episode in your inbox, daily — free.
One email a day, unsubscribe anytime. No spam, ever.