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Join the maintainers of LangChain4j for a fast-paced tour of its latest features and how to use them in real-world apps. We’ll demo an AI researcher agent for drug discovery while covering concepts like guardrails, observability, multi-LLM orchestration, agents, and testing for non-deterministic systems. We’ll also explore advanced RAG, basic RAG’s less clumsy big brother, to give your models access to data from documents, databases, and the web. By the end of this talk, you'll be ready to take your AI-powered proof-of-concept to production.

Devoxx

A conference talk covering production-grade patterns for building AI features with LangChain4j in Java. Topics include advanced RAG techniques (query compression, routing, reranking), tool calling best practices (dynamic tools, max invocations, MCP servers), agent orchestration patterns (sequential, parallel, loop, supervisor), guardrails for input/output validation, human-in-the-loop workflows, typed POJOs for control and testability, observability, and a live demo of an enterprise help desk system that triages tickets, finds related docs, and auto-generates bug-fix PRs with human approval gates.

Level Up Your LangChain4j Apps for Production by Lize Raes