Building and Orchestrating Production-ready Agentic AI Systems
summary
Showcases a Java-based car-rental demo that actually runs: image and text inputs are analyzed by modular agents and routed to cleaning, maintenance, or disposition with a human-in-the-loop for high-value vehicles. Uses LangChain forJ to compose sequence/parallel/conditional agent patterns, an A2A agent for agent-to-agent messaging, RAG plus dockling for document context, and containerized deployment to Kubernetes with health metrics, tracing, and autoscaling proving the system works in production-like clusters.
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chapters (13)
- 0:00Agentic AI and enterprise adoption
- 1:27From AI services to agentic systems
- 5:02Connecting AI to legacy systems
- 6:09Retrieval Augmented Generation
- 7:56Enterprise requirements for production AI
- 9:20Frameworks and design patterns for agentic AI
- 11:06Multi-agent systems with LangChain4j
- 14:37Demo: Agentic AI in car rental
- 21:01Orchestrating agents with Java patterns
- 24:14Deploying agentic AI to Kubernetes
- 27:28Production considerations for agentic AI
- 29:54Key capabilities and next steps
- 30:37Q&A
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