AI Glossaryapplications

Chatbot

An AI application that conducts conversations with users through text or voice, handling questions, tasks, and interactions in natural language.

How It Works

Chatbots are the most common AI application. Modern chatbots powered by LLMs are fundamentally different from the rule-based chatbots of the past. Instead of matching keywords to scripted responses, they understand context, handle follow-up questions, and generate natural responses. Building one requires: an LLM API (OpenAI, Anthropic, or Google), conversation history management, and a user interface. The technical architecture: (1) User sends a message, (2) Your app prepends a system prompt (defining the chatbot's personality and rules), (3) Previous messages are included for context, (4) The LLM generates a response, (5) The response is streamed back to the user. Use OpenAI's Conversations API or maintain your own message history. Add RAG for knowledge-grounded responses and function calling for action-taking capability. Production chatbot considerations: system prompt design (defines quality), conversation length management (truncate or summarize old messages to stay within context limits), safety filters (prevent prompt injection and harmful outputs), fallback handling (escalate to humans when the AI cannot help), and analytics (track conversation quality, user satisfaction, and common failure modes).

Common Use Cases

  • 1Customer support automation
  • 2Product recommendations
  • 3FAQ and knowledge base access
  • 4Onboarding and guided experiences
  • 5Personal AI assistants

Related Terms

Large Language Model (LLM)

A neural network trained on massive text datasets that can generate, understand, and reason about human language.

RAG (Retrieval-Augmented Generation)

A technique that enhances AI responses by retrieving relevant information from a knowledge base before generating an answer.

Prompt Engineering

The practice of crafting effective instructions for AI models to produce desired outputs consistently.

Streaming

A method of receiving AI model output token-by-token in real time as it is generated, rather than waiting for the complete response.

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