
technologyFeb 25, 202532:45pending
OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents
About this episode
OpenAI’s Isa Fulford and Josh Tobin discuss how the company’s newest agent, Deep Research, represents a breakthrough in AI research capabilities by training models end-to-end rather than using hand-coded operational graphs. The product leads explain how high-quality training data and the o3 model’s reasoning abilities enable adaptable research strategies, and why OpenAI thinks Deep Research will capture a meaningful percentage of knowledge work. Key product decisions that build transparency and trust include citations and clarification flows. By compressing hours of work into minutes, Deep Research transforms what’s possible for many business and consumer use cases.
Hosted by: Sonya Huang and Lauren Reeder, Sequoia Capital
Mentioned in this episode:
Yann Lecun’s Cake: An analogy Meta AI’s leader shared in his 2016 NIPS keynote
Get every episode summarized
Each time Training Data publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Training Data

Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
Training Data
Sep 1, 202652:27pending

Parallel’s Parag Agrawal: Building a New Web for AI Agents
Training Data
Aug 25, 202655:18pending

Rich Sutton and Khurram Javed: Why AI Models Stop Learning, and How to Start It...
Training Data
Aug 18, 202653:43pending

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem
Training Data
Aug 4, 202647:22pending