Unleash the Power of AI Agents with Java Building Intelligent Application
summary
Shows Java code that actually builds RAG pipelines, vector search and agents using LangChain4j and Spring AI, stores embeddings in Oracle AI Database with a native vector data type, and loads 35 Oracle error codes to prove retrieval works. Demos include RAG with PDF + embeddings, agents with memory and moderation (violent message triggers a policy exception), an in‑memory quantized embedding model, and a multi‑tool Quarkus agent that sends mock emails — all runnable and demonstrated live.
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chapters (13)
- 0:00🚀 Build Stuff Conference – Get Your Tickets!
- 0:40Introduction: GenAI for Java Developers
- 4:10What is Generative AI? Concepts & Evolution
- 8:30AI as a Commodity: Cloud + APIs
- 12:10Embeddings, Vector Search & Semantic Search Explained
- 17:20Oracle AI Database & Vector Data Types
- 22:00Retrieval-Augmented Generation (RAG) in Practice
- 26:40LangChain4j & Spring AI: Building AI Apps in Java
- 31:10AI Agents: Tools, MCP & Autonomous Behavior
- 35:00Demo: RAG with PDF + Vector Embeddings
- 38:10Demo: Agents with Memory & Moderation
- 41:00Demo: Multi-Tool Agent with Quarkus
- 42:30Final Thoughts: The Future of AI Development
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