Glossary
AI agent
Software that converses in natural language and takes action (answering questions, qualifying a lead, booking a meeting) from a knowledge base you define. It differs from a chatbot because it does not follow a fixed script: it interprets the question and looks up the answer.
The practical difference from a chatbot is where the answer comes from. A chatbot returns a string somebody wrote in advance and attached to a node in a decision tree. An agent receives the question as text, searches your content for the passage that answers it, and writes the reply from that passage. Nobody has to anticipate the phrasing.
That also changes what maintenance looks like. Improving a chatbot means editing the tree; improving an agent means improving the source content: the page, the FAQ entry, the price list it reads. The work moves from whoever owns the automation to whoever owns the information.
An agent is only worth deploying where the questions vary. For a fixed three-step flow (track an order, reset a password), a form or a scripted bot is cheaper, faster and easier to audit.
See also
RAG (retrieval-augmented generation)
A technique where the agent first retrieves relevant passages from your knowledge base and only then generates an answer based on them. It is what keeps the answer anchored in your content rather than in the model’s generic memory.
Guardrail
A constraint applied to the agent to prevent answers that are out of scope, off-brand or ungrounded in your content. It covers faithfulness checks, topic blocking and masking of sensitive data.
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