Agents
Chip Huyen
Intelligent agents built on foundation models can perceive environments and act through tools to accomplish multi-step tasks like website creation, data gathering, and trip planning. Agent accuracy decreases with task complexity, dropping from 95% per step to 60% over 10 steps and 0.6% over 100 steps, requiring more powerful models. Agent success depends on tool access and planning capability, with tools providing knowledge augmentation, capability extension, and environmental action.
Why it matters
Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unprecedented capabilities of foundation models have opened the door to agentic applications that were previously unimaginable. These new capabilities make it finally possible to develop autonomous, intelligent agents to act as our assistants, coworkers, and coaches. They can help us create a website, gather data, plan a trip, do market research, manage a customer account, automate data entry, prepare us for interviews, interview our candidates, negotiate a deal, etc. The possibilities seem endless, and the potential economic value of these agents is enormous. This section will start with an overview of agents and then continue with two aspects that determine the capabilities of an agent: tools and planning. Agents,
