OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents
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
00:00 - Introduction
01:45 - What is Deep Research?
06:22 - Surprising use cases
13:02 - End-to-end training
20:49 - Deep Research and Operator
23:47 - Where to go from here?
28:45 - Lightning round
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
00:00 – Introduction
01:45 – What is Deep Research?
06:22 – Surprising use cases
13:02 – End-to-end training
20:49 – Deep Research and Operator
23:47 – Where to go from here?
28:45 – Lightning round
