Source URL: https://simonwillison.net/2025/Jun/5/wrecking-its-environment-in-a-loop/#atom-everything
Source: Simon Willison’s Weblog
Title: An agent is an LLM wrecking its environment in a loop
Feedly Summary: Solomon Hykes just presented the best definition of an AI agent I’ve seen yet, on stage at the AI Engineer World’s Fair:
An AI agent is an LLM wrecking its environment in a loop.
I collect AI agent definitions and I really like this how this one combines the currently popular “tools in a loop" one (see Anthropic) with the classic academic definition that I think dates back to at least the 90s:
An agent is something that acts in an environment; it does something. Agents include worms, dogs, thermostats, airplanes, robots, humans, companies, and countries.
Tags: ai-agents, llms, ai, generative-ai
AI Summary and Description: Yes
Summary: The text discusses a novel definition of an AI agent as presented by Solomon Hykes, emphasizing its implications within the context of LLMs (Large Language Models) and their interactions with environments. This perspective is significant for professionals in AI, particularly those focused on the operational dynamics and potential impacts of AI agents.
Detailed Description: The text showcases Solomon Hykes’ insightful definition of an AI agent, which presents a provocative view on how such agents interact with their environment. This understanding is paramount for security and compliance professionals working with AI technologies.
– **Definition Context**:
– Hykes defines an AI agent as “an LLM wrecking its environment in a loop,” which captures the dynamic interaction agents have with their surroundings.
– This definition marries two concepts: the contemporary notion of “tools in a loop” (as seen in the works of companies like Anthropic) and the foundational academic understanding of agents.
– **Broad Scope of Agents**:
– The definition draws from classic academic principles stating that an agent is “something that acts in an environment,” which broadens the spectrum of what can be considered an agent to include not just AI entities but also natural and artificial constructs like worms, dogs, thermostats, airplanes, robots, humans, companies, and even nations.
The relevance of this discussion lies in the increasing importance of understanding AI agents’ behavior and implications, especially as organizations integrate them into operational workflows. Understanding agents as dynamic entities can aid in better risk assessment and development of compliance frameworks as AI systems become more integral to business operations.