Module 1: Introduction to Agent Training

How AI Agents Learn

At its core, an AI agent learns by accessing and interpreting a vast amount of information. This information, which we call the "knowledge base," is a collection of documents, data, and other content that the agent uses to answer questions and perform tasks. The process of providing this information to the agent is called "training."

In the raiaAI platform, training is not about writing code or building complex machine learning models. Instead, it is about curating and organizing the information that the agent needs to do its job. The agent uses a technique called Retrieval-Augmented Generation (RAG) to find the most relevant information from its knowledge base and then uses that information to generate a response.

The Role of the Knowledge Base

The knowledge base is the single source of truth for your AI agent. It can include a wide variety of content, such as:

• Product Manuals: Detailed information about how a product works.

• Frequently Asked Questions (FAQs): A list of common questions and their answers.

• Company Policies: Documents outlining a company's rules and procedures.

• Marketing Materials: Information about a company's products and services.

• Internal Process Documents: Guides for how to perform specific tasks.

The Importance of High-Quality Data

The performance of your AI agent is directly tied to the quality of its training data. A well-curated and organized knowledge base will result in an agent that is accurate, reliable, and helpful. Conversely, a knowledge base that is outdated, inaccurate, or poorly organized will lead to an agent that is confused and provides incorrect information.

As a raiaLabs team member, one of your most important responsibilities is to ensure that the data you use to train our clients' agents is of the highest possible quality. This includes not only the content of the documents but also how they are structured and organized. In the following modules, you will learn the best practices for managing and preparing data to create world-class AI agents.