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AI Chatbot Glossary: 25 Terms Explained

Updated July 9, 2026 · 7 min read

Quick answer

This glossary defines the core AI chatbot terms in plain language: large language model, token, prompt, context window, RAG, agent, hallucination, fine-tuning, multimodal, and more.

Core model terms

These terms describe the technology under a chatbot.

  • Large language model (LLM): a neural network trained to predict text, the engine behind a modern chatbot.
  • Token: a chunk of text, such as a word or part of a word, that a model reads and writes.
  • Context window: the maximum number of tokens a model holds at once in a conversation.
  • Parameters: the internal values a model adjusts during training; more can mean more capability.
  • Multimodal: a model that handles more than text, such as images, audio, or video.

Behavior and quality terms

  • Prompt: the text you send to a chatbot, plus any hidden instructions it adds.
  • Hallucination: a confident answer that states wrong information.
  • Grounding: connecting a model to source data so answers stay accurate.
  • Reasoning model: a model that works through steps before it answers, for harder problems.
  • Temperature: a setting that controls how varied a model's output is.

Training and tuning terms

  • Pretraining: the first training stage, where a model learns to predict text from a large body of data.
  • Fine-tuning: further training on curated examples to shape behavior for a task.
  • Alignment: safety and feedback training that steers a model toward useful, safe answers.
  • Open weights: model files a provider releases so others can run or tune the model.
  • Distillation: training a smaller model to copy a larger one for lower cost.

Application terms

  • RAG (retrieval-augmented generation): a method where a chatbot pulls from documents and answers from that content with citations.
  • Agent: a chatbot that takes actions across steps and tools, not just replies.
  • Knowledge base: the approved content a business chatbot answers from.
  • Handoff: the moment a chatbot passes a conversation to a human agent.
  • Answer engine: a search-first chatbot that returns cited answers, such as Perplexity.
  • System prompt: hidden instructions that set a chatbot's role and rules.
  • API: an interface that lets software send prompts to a model and receive responses.
  • Fine print on privacy: the data policy that states whether a tool trains on your inputs.
  • SSO (single sign-on): a login control common in enterprise chatbot plans.
  • Deflection: a support metric for tickets a chatbot resolves without an agent.

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