A deep learning model trained on massive amounts of text data that can understand and generate human-like language. LLMs like Claude, GPT, and Gemini serve as the reasoning engine behind AI agents, enabling them to understand instructions, process information, and generate intelligent responses.
Related Terms
AI Agent
An autonomous software system powered by a large language model (LLM) that can perceive its environment, make decisions, and take actions to achieve specific goals. Unlike simple chatbots, AI agents can use tools, access external data, maintain context across interactions, and chain multiple reasoning steps together.
RAG (Retrieval-Augmented Generation)
A technique that enhances LLM responses by retrieving relevant information from external knowledge bases before generating an answer. RAG grounds AI responses in real, up-to-date data — reducing hallucinations and enabling agents to answer questions about proprietary or domain-specific content.
Prompt Engineering
The practice of designing and optimizing the instructions given to large language models to elicit desired behaviors and outputs. Effective prompt engineering is critical for building reliable AI agents — determining how well they reason, follow instructions, use tools, and handle edge cases.