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LLM Powered Autonomous Agents

Named practitioner synthesis

#238

T3digested

Canonical URL: https://lilianweng.github.io/posts/2023-06-23-agent/
Topic: Agent Evaluation
First seen: 2026-07-16 19:08:00
Last seen: 2026-07-16 19:08:00

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Blog / Newsletter2026-07-16 19:07:22
LLM Powered Autonomous Agents
<p>Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as <a href="https://github.com/Significant-Gravitas/Auto-GPT">AutoGPT</a>, <a href="https://github.com/AntonOsika/gpt-engineer">GPT-Engineer</a> and <a href="https://github.com/yoheinakajima/babyagi">BabyAGI</a>, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.</p> <h1 id="agent-system-overview">Agent System Overview</h1> <p>In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:</p> <ul> <li><strong>Planning</strong> <ul> <li>Subgoal and decomposition: The agent breaks down large tasks into smaller, manageable subgoals, enabling efficient handling of complex tasks.</li> <li>Reflection and refinement: The agent can do self-criticism and self-reflection over