OpenAI’s ChatGPT agent team discusses the origin, design and ambitions of this new system that unifies research and operator capabilities for more powerful, flexible automation. The episode highlights both the technical advances and the collaborative approach that enabled the rapid development of this multi-tool agent—and emphasized the challenges and opportunities as AI agents become more capable and integrated into real workflows.
Combining specialized agents unlocks new capabilities: By merging the strengths of Operator (visual, GUI-based actions) and Deep Research (text browsing and synthesis), the team achieved a system that can handle diverse, end-to-end tasks—everything from online shopping to spreadsheet automation.
Shared state and tool orchestration are key breakthroughs: The agent’s ability to switch seamlessly between tools—browser, terminal, APIs and more—with shared state mimics how humans use computers, dramatically increasing flexibility and efficiency.
Human-in-the-loop and collaborative design matters: The system allows for ongoing, interruptible interaction, enabling users to clarify, redirect or take over tasks mid-process, which leads to more robust and user-aligned outcomes.
Safety and real-world integration introduce new challenges: Granting agents the power to take actions with real-world effects required substantial investment in guardrails, monitoring and cross-team safety processes, especially given the risks of automation and internet interaction.
Small, cross-functional teams with rapid iteration can drive major leaps: The project was delivered by a surprisingly small, tightly integrated team, with blurred lines between research and engineering, showing that ambitious AI initiatives can move quickly through deep collaboration and clear product grounding.