Resources

Rod Johnson's Blog Posts

• Embabel: A new Agent Platform For the JVM - Introduction to the Embabel agent framework, explaining the motivation for building an agent platform specifically for the JVM ecosystem. Covers the key differentiators and benefits of the approach.
• The Embabel Vision - Rod Johnson’s vision for the future of agent frameworks and how Embabel fits into the broader AI landscape. Discusses the long-term goals and strategic direction of the project.
• Context Engineering Needs Domain Understanding - Deep dive into the DICE (Domain-Integrated Context Engineering) concept and why domain understanding is fundamental to effective context engineering in AI systems.

Examples and Tutorials

• Creating an AI Agent in Java Using Embabel Agent Framework by Baeldung - A nice introductory example, in Java.
• Building Agents With Embabel: A Hands-On Introduction by Jettro Coenradie - An excellent Java tutorial.

Embabel Agent Examples Repository

The Examples Repository is a comprehensive collection of example agents demonstrating different aspects of the framework:

• Beginner Examples: Simple horoscope agents showing basic concepts
• Intermediate Examples: Multi-LLM research agents with self-improvement
• Advanced Examples: Fact-checking agents with parallel verification and confidence scoring
• Integration Examples: Agents that use web tools, databases, and external APIs

Perfect starting point for learning Embabel development with hands-on examples.

Java Agent Template

Template repository for creating new Java-based Embabel agents. Includes:

• Pre-configured project structure
• Example WriteAndReviewAgent demonstrating multi-LLM workflows
• Build scripts and Docker configuration
• Getting started documentation

Kotlin Agent Template

Template repository for Kotlin-based agent development with similar features to the Java template but using idiomatic Kotlin patterns.

Sophisticated Example: Tripper Travel Planner

Tripper - AI-Powered Travel Planning Agent

Tripper is a production-quality example demonstrating advanced Embabel capabilities:

Features:

• Generates personalized travel itineraries using multiple AI models
• Integrates web search, mapping, and accommodation search
• Modern web interface built with htmx
• Containerized deployment with Docker
• CI/CD pipeline with GitHub Actions

Technical Highlights:

• Uses both Claude Sonnet and GPT-4.1-mini models
• Demonstrates domain-driven design principles
• Shows how to build user-facing applications with Embabel
• Practical example of deterministic planning with AI

Learning Value:

• Real-world application of Embabel concepts
• Integration patterns with external services
• Production deployment considerations
• User interface design for AI applications

Goal-Oriented Action Planning (GOAP)

• Here’s an Introduction to GOAP, the planning algorithm used by Embabel. Explains the core concepts and why GOAP is effective for AI agent planning.

Small Language Model Agents - NVIDIA Research

• This Research paper discusses the division between "code agency" and "LLM agency" - concepts that inform Embabel’s architecture.

OODA Loop - Wikipedia

Here’s a Background on the Observe-Orient-Decide-Act loop that underlies Embabel’s replanning approach.

Domain-Driven Design

• Martin Fowler’s Foundational concepts of Domain-Driven Design provides a good summary of Embabel’s approach to domain modeling.

Domain-Driven Design: Tackling Complexity in the Heart of Software

• Eric Evans' seminal book on DDD principles. Essential reading for understanding how to model complex domains effectively.

DDD and Contextual Validation

• Advanced DDD concepts relevant to building sophisticated domain models for AI agents.