Module 6: Modular Training with AI Agent Packs

As you start building multiple agents for a client, you will notice that they often share common knowledge. For example, all agents for a particular company should know the company's history, its brand values, and its core products. Repeating this information in every agent's knowledge base is inefficient and difficult to maintain. This is where AI Agent Packs come in.

What are AI Agent Packs?

AI Agent Packs are reusable, modular bundles of training data and instructions. They are designed to provide a centralized source of knowledge that can be shared across multiple agents. A pack can contain:

  • Knowledge Files: Markdown documents with common information.

  • Instructions: Snippets of instructions that can be included in an agent's prompt.

The Benefits of Using Agent Packs

  • Efficiency: Avoid duplicating content across multiple agents.

  • Consistency: Ensure that all agents are working from the same source of truth.

  • Maintainability: Update the information in one place (the pack), and it will automatically be updated for all agents using that pack.

  • Scalability: Easily build new agents with a pre-existing foundation of knowledge.

Common Use Cases for Agent Packs

  • Company Boilerplate: A pack containing the company's history, mission, and brand guidelines.

  • Product Catalog: A pack with information about all of a company's products.

  • Compliance: A pack with legal and regulatory information that all agents must adhere to.

  • Standard Procedures: A pack outlining common procedures, such as how to handle customer complaints.

How to Use Agent Packs in raiaAI

  1. Create a Pack: In the raiaAI Launch Pad, you can create a new Agent Pack and give it a descriptive name (e.g., "Innovate Inc. Company Info").

  2. Add Content: Upload knowledge files and add instruction snippets to the pack.

  3. Assign the Pack to an Agent: In the agent's "Training" tab, you can select which packs you want to assign to it.

  4. Reference the Pack in Instructions: You can then reference the knowledge files from the pack in your agent's routing section, just like any other file in the knowledge base.

By using AI Agent Packs, you can build a scalable and maintainable knowledge architecture for your clients. This modular approach is a key component of the raiaLabs methodology for building enterprise-grade AI solutions.

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