AI & ML

AI Agents

Autonomous AI systems that use LLMs to plan, reason, and execute multi-step tasks by calling tools, APIs, and other services.

AI agents are autonomous systems built on top of LLMs that can plan and execute multi-step tasks. Unlike simple chatbots that respond to individual messages, agents can break down complex goals into subtasks, use tools, and iterate until the task is complete.

An AI agent typically has several components: a language model for reasoning, a set of tools it can call (APIs, databases, code execution), a memory system for maintaining context, and a planning loop that decides what action to take next.

Popular frameworks for building agents include LangChain, LlamaIndex, CrewAI, and AutoGen. These provide abstractions for tool calling, memory management, and agent orchestration.

Use cases include customer support automation, code generation pipelines, research assistants, data analysis workflows, and DevOps automation. Key challenges include cost management (agents can make many LLM calls), reliability (handling tool failures gracefully), and safety (preventing unintended actions).

Related Terms

Large Language Model (LLM) Prompt Engineering Retrieval-Augmented Generation (RAG) Function Calling

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