This workshop guides Java developers from manually building a basic AI agent with LLM integration and conversational memory to transforming it into a scalable, production-ready solution using agent frameworks, highlighting the added benefits of multi-LLM support, observability, and simplified deployment for real-world applications.

Detailed Description

It doesn’t take much to build a simple AI agent — with just basic programming skills, you can create one from scratch without using any frameworks. But moving from a working prototype to a production-ready agent introduces a whole new level of complexity.

In this hands-on workshop, you’ll start by building your own AI agent in Java. You’ll implement LLM integration, tool calling, and manage conversational history — all from the ground up. This gives you a deep understanding of how agents operate under the hood.

With that foundation, you’ll then transition to using an agent framework. You’ll learn how frameworks simplify the development process by handling complexity like multi-LLM support, observability, memory, and deployment. By the end, you’ll have transformed your home-grown agent into one that’s framework-ready and production-capable.

Key Takeaways:

Understand the core components of an AI agent by building one manually.
Learn how to integrate LLMs, tools, and memory in Java.
Gain experience with agent frameworks to support scalability and production use.

Target Audience:
Java developers who are curious about AI agents and want hands-on experience creating, understanding, and scaling them for real-world applications.