Product & Strategy
The Agentic AI Research Frontier
The open problems shaping more capable, efficient, secure, and understandable autonomous systems.
Reliable long-horizon work
Small errors compound across many steps, and current agents often lose track of goals or evidence. Better planning, state representation, verification, and recovery remain central challenges.
Learning from interaction
Researchers are exploring how agents improve from tool feedback, human corrections, and prior trajectories without preserving unsafe behavior or private data.
Control and understanding
More capable agents increase the need for interpretable state, calibrated uncertainty, robust permissions, and evaluation under adversarial conditions. Progress in capability and control must be measured together.