Basic Components of an Agentic AI Bot
Written by Product Team
Updated on August 5th, 2026
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Table of Contents
An Agentic AI bot is primarily built using two core components:
System Prompt
Actions
System Prompt
A System Prompt is a set of instructions provided to the Large Language Model (LLM) that defines its behavior, capabilities, and decision-making process. It acts as the bot's foundational guidance and is included with every user interaction.
Since the system prompt is sent with every query, it is recommended to keep it clear, concise, and focused. A shorter prompt consumes fewer tokens, leaving more context available for the user's query and helping reduce the likelihood of hallucinations.
Actions
Actions enable an Agentic AI bot to perform tasks beyond generating text. They allow the agent to interact with external systems and execute predefined operations.
Common use cases for actions include:
Fetching real-time data from external services.
Calling APIs or third-party applications.
Invoking another prompt or a Retrieval-Augmented Generation (RAG) application.
Executing custom business logic or code.
Integrating with enterprise systems and workflows.
An Agentic AI bot can be configured with up to 128 actions, allowing it to handle complex workflows and automate a wide range of tasks.
