Introduction to LLM Agents

• Introduction to LLM Agents: This post introduces LLM-powered agents and discusses their components and functions in enterprise applications.

• What is an AI agent?: An AI agent is a system that can use an LLM to reason through a problem, create a plan, execute the plan, and re-evaluate it if necessary. It consists of an agent core, memory module, tools, and planning module.

• Agent core: The agent core is an LLM that follows instructions, sets goals, uses tools, and accesses memory. It can also be assigned a persona to imbue a personality or behavioral descriptions.

• Memory module: The memory module stores logs of the agent's thoughts and interactions with users. It is used to refine the execution plan generated by the agent.

• Agents for enterprise applications: LLM-powered agents have various applications in enterprise settings, including question-answering agents, swarm of agents, recommendation and experience design agents, customized AI author agents, and multi-modal agents.

• Question-answering agent: A question-answering agent uses a question-decomposition module, a RAG pipeline, and memory modules to answer complex questions by breaking them down into sub-questions and retrieving specific information.

Overall, LLM-powered agents have the potential to generate personalized answers and content in a variety of enterprise applications through their reasoning, planning, and execution capabilities.