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# Integrating AI into Your Java Applications: Spring AI Deep Dive with RAG by Christian Tzolov

**[Devoxx](https://daily.dev/sources/devoxx)** · 99 min read · 1 upvotes · 0 comments

## Summary

A deep-dive conference talk by Christian Tzolov, lead of the Spring AI project, covering core patterns for building AI applications in Java using Spring AI. Topics include the advisor/interceptor pattern for pre/post LLM call hooks, chat memory for stateful conversations, RAG with vector stores, structured output with self-correction, tool calling and the tool-search advisor for progressive disclosure, guard rails, LLM-as-judge evaluation, explainable agents with inner-thought augmentation, agent skills (progressive disclosure of instructions), to-do task tracking for long-running agents, user clarification questions, and sub-agent orchestration patterns. All patterns are shown to build on the same primitives: context stuffing, LLM completion, and intercepting input/output.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=48Ht5lE1jno>

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---

Tags: [#java](https://daily.dev/tags/java), [#ai-agents](https://daily.dev/tags/ai-agents), [#rag](https://daily.dev/tags/rag), [#spring-ai](https://daily.dev/tags/spring-ai)

[View this post on daily.dev](https://daily.dev/posts/integrating-ai-into-your-java-applications-spring-ai-deep-dive-with-rag-by-christian-tzolov-swwa2zrua)

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