

Guaranteed quality and structure in LLM outputs - with Shreya Rajpal of Guardrails AI
Tomorrow, 5/16, we’re hosting Latent Space Liftoff Day in San Francisco. We have some amazing demos from founders at 5:30pm, and we’ll have an open co-working starting at 2pm. Spaces are limited, so please RSVP here! One of the biggest criticisms of large language models is their inability to tightly follow…
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 →
🔬Scaling Past Informal AI - Carina Hong, Axiom Math

🔬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 →
Controlled and compliant AI applications

Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google, and Amazon

10 OpenClaw Lessons for Building Agent Teams

EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper
One great episode in your inbox, daily — free.
One email a day, unsubscribe anytime. No spam, ever.