AI Agents for Support and Ticket Automation

Engineering teams spend countless hours answering repetitive support questions and resolving standard tickets. What if you could automate this workload using intelligent systems? This course teaches you how to build and integrate AI agents directly into your existing codebase. You will learn how to connect language models to your internal documentation and ticketing systems, transforming how your platform handles support requests. What you will learn: Understand the fundamental concepts of AI agents and how they differ from standard scripts; Learn foundational prompt engineering techniques to guide agent behavior and decision-making; Build Retrieval-Augmented Generation (RAG) pipelines using vector databases to give your agent context; Integrate AI models with your codebase to read, analyze, and respond to incoming support tickets; Configure secure external tool calling so your agent can interact with internal APIs safely; Practice writing clean, modular code to maintain and scale your AI automation workflows. The course begins with essential AI terminology and core concepts before moving into practical, text-based coding exercises. You will work through step-by-step written scenarios to construct a functional support agent architecture from the ground up. This material is designed for beginner backend developers and platform engineers looking to explore AI automation, with no prior machine learning experience required. Start building intelligent support solutions today and streamline your engineering workflows.