Isa Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released.
Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. “The number of people who were DMing me made us pretty excited,” says Fulford.
Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.
“Deep Research has written 6 reports so far today,” Patrick Collison, the CEO of Stripe posted on X a few days after the product was released. “It is indeed excellent. Congrats to the folks behind it.”
“Deep Research is the AI product that really got a meaningful chunk of the policymaking community in DC to start feeling the AGI,” wrote Dean Ball, a fellow at George Mason University who specializes in AI policy.
Deep Research is available as part of all paid ChatGPT plans, although most users are capped at 10 queries per month. (People on the $200 ChatGPT Pro plan get 120 queries per month.) It takes a query, such as “Write me a report on the Massachusetts health insurance industry,” or “Tell me about WIRED’s coverage of the Department of Government Efficiency,” and then comes up with a plan, searching for relevant websites, combing through their content, and deciding what links to click and what information deserves further investigation. After exploring for sometimes tens of minutes, it synthesizes its findings into a detailed report, which may include citations, data, and charts.
Many tools currently branded as AI agents are essentially chatbots connected to simple programs without much sophistication. The Deep Research model itself goes through an artificial kind of reasoning before devising a plan and moving forward with each step. The model provides details of this reasoning behind its research in a side window.
“Sometimes it’s like ‘I need to backtrack, this doesn’t seem that promising,’” says Josh Tobin, another OpenAI researcher involved in building Deep Research. “It’s pretty cool to read some of those trajectories, just to understand how the model is thinking.”
OpenAI evidently sees Deep Research as a tool that could take on more office work. “This is a thing that we can scale,” Tobin says, adding that the agent could be trained to complete specific white-collar work. An agent with access to a company’s internal data could quickly prepare a report or presentation, for instance. Tobin says the longer goal is to “build an agent that is not just good at building reports through searching the web, but is good at many other types of tasks too.”
Because Deep Research was trained to analyze and summarize human-written text, Tobin says his team was surprised to see many people using it to generate code. “It’s an interesting thread to pull,” he says. “We’re not totally sure what to make of it.”
