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On this episode of No Priors, Sarah sits down with Isa Fulford, one of the masterminds behind deep research. They unpack how the initiative began, the role of human expert data, and what it takes to build agents with real-world capability and even taste. Isa shares the differences between deep research and OpenAI’s o3 model, the challenges around latency, and how she sees agent capabilities evolving. Plus, OpenAI has announced that deep research is free for all US users starting today.
Sign up for new podcasts every week. Email feedback to [email protected]
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @IsaFulf
Show Notes:
0:00 Deep research’s inception & evolution
6:12 Data creation
7:20 Reinforcement fine-tuning
9:05 Why human expert data matters
11:23 Failure modes of agents
13:55 The roadmap ahead for Deep Research
18:32 How do agents develop taste?
19:29 Experience and path to building a broadly capable agent
22:03 Deep research vs. o3
25:55 Latency
27:56 Predictions for agent capabilities
By Conviction4.4
119119 ratings
On this episode of No Priors, Sarah sits down with Isa Fulford, one of the masterminds behind deep research. They unpack how the initiative began, the role of human expert data, and what it takes to build agents with real-world capability and even taste. Isa shares the differences between deep research and OpenAI’s o3 model, the challenges around latency, and how she sees agent capabilities evolving. Plus, OpenAI has announced that deep research is free for all US users starting today.
Sign up for new podcasts every week. Email feedback to [email protected]
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @IsaFulf
Show Notes:
0:00 Deep research’s inception & evolution
6:12 Data creation
7:20 Reinforcement fine-tuning
9:05 Why human expert data matters
11:23 Failure modes of agents
13:55 The roadmap ahead for Deep Research
18:32 How do agents develop taste?
19:29 Experience and path to building a broadly capable agent
22:03 Deep research vs. o3
25:55 Latency
27:56 Predictions for agent capabilities

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