AI agents are self-contained bodies of information. They can be used to provide context to Large Language Models (LLMs) and answer questions on a particular topic.
LLMs are trained on a large variety of data. However, to answer a question on a specific topic, or to draw conclusions from a specific topic, they need to be supplied with the context of that topic.
AI agents are an intuitive way to provide that context.
Selecting a agent provides the context of that agent to the LLM. This lets users build agents for specific topics, and then use them to answer questions about that topic, without being “polluted” by information that is not in the agent. This prevents “hallucinations” and answers that are out-of-context.
