Agentic AI Workflows with Embabel

We have all seen the “Hello, World” of Spring AI: sending a prompt and getting a response. But as we move toward production, the real challenge is not the LLM call; it is the workflow. How do you ensure an agent does not loop infinitely? How do you coordinate multiple tools without a mess of “if-else” blocks? And how do we keep our Java-centric domain models at the heart of the AI’s reasoning?

Enter Embabel, a new JVM-based framework from Rod Johnson (creator of Spring) designed to bring discipline to agentic AI. Unlike Python-centric alternatives, Embabel is built on the philosophy of strong typing, OODA loops (Observe, Orient, Decide, Act), and Goal-Oriented Action Planning (GOAP).

In this session, we will go beyond basic RAG and explore how to build “digital workers” that can actually plan. You will learn: How to turn your existing Spring Beans into AI Actions.

The shift from imperative coding to Goal-Oriented orchestration.

How Embabel uses DICE (Domain-Integrated Context Engineering) to give agents true domain knowledge.

Why the JVM is actually the best place to run mission-critical AI agents.

Join us for a code-heavy look at the future of Java backend development. We are moving to a world where our systems do not just respond to requests, but actively work to achieve goals.

About DaShaun Carter

DaShaun is a husband, father of four, volunteer, struggling athlete, former professional cheerleader, Raspberry Pi enthusiast, and Spring Developer Advocate at Broadcom. Deliberately practicing to build, run, and manage, better software, faster.

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