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Course Overview and Prerequisites

In this course, we focus on two of the fundamental system tools provided by the Twinit AI Service: GetNamedUserItemsTool and GetRelatedItemsTool. You will see how these tools are used both in single-agent and multi-agent workflows across different teams. We begin by exploring how each tool works in isolation, then move on to the more important question: how they work together within a single, coherent agent workflow. Rather than treating tools as standalone features, the course emphasises how meaningful behaviour emerges when multiple tools are combined under a well-defined agent strategy.

A key concept we’ll explore is the use of the _background field. This field allows us to provide guiding instructions to an agent, effectively teaching it how and when to use specific system tools. By leveraging this mechanism, we will learn how to coordinate multiple agents and tools toward a shared goal, and how to “glue” their responsibilities together in a clean, maintainable way.

To make these ideas concrete, we will build a complete project from scratch. This includes setting up a new project, securely uploading an OpenAI API key, and preparing the environment using predefined template packages. These templates automatically create a collection and populate it with sample data, upload knowledge bases to the file service, and upload scripts that will be used throughout the course. This lets us focus on agent behaviour rather than boilerplate setup. The sample data consists of fictitious Computer Science lecture details, such as course information and related metadata. Throughout the course, the agent will interact with users and retrieve relevant information from this collection using the system tools we introduce. By the end, you’ll have a clear understanding of how agents, system tools, and structured data come together to power practical, real-world AI interactions within the Twinit AI Service.

Prerequisites#

Before diving into the hands-on lessons in this course, it is important to ensure you have the right setup and foundational knowledge. These prerequisites will help you follow along smoothly, understand the concepts presented, and successfully execute code against the Twinit AI Service.

Prerequisites for This Course:

  1. Completed the 2 | Self-Led Developer Basics course
  2. Completed the 3 | Self-Led Developer Intermediate course
  3. Completed the AI 01 | Introduction to Twinit AI course
  4. A working understanding of APIs, REST APIs, and how they work and how to use them
  5. A working understanding and ability to read asynchronous JavaScript code
  6. A working understanding and ability to read es modules
  7. A working understanding and ability to read JSON

Twinit IDE Extension#

Be sure you are using the latest version of the Twinit IDE Extension before proceeding with the course.

You can check if a newer version of the extension is available by restarting your IDE and clicking on the Twinit IDE Extension. If a newer version is available a message will appear with a link to download the installer.