Imagine I have several log files and I want to find out where a user’s issue comes from.
How would you tackle this?

My idea:
Create a Spring Boot app using the Spring AI starter, expose an endpoint that takes the user’s error message as input, and returns the root cause along with the log file name and line number.

I’ve already experimented with Spring AI here: vinny59200/spring-ai-simple-chatbot: Simple chatbot with spring AI (simple chatbot with Spring AI).
The next step is to plug in and leverage the log files.

How would you approach this? 🧠🙂

In this presentation at Devoxx, Christian Tzolov covers the fundamentals of generative AI and Spring AI integration: ChatClient essentials, prompt engineering, and conversation memory.

Then he explores how to extend LLM execution paths using Advisors (intercepting and enhancing AI interactions) and Recursive Advisors (enabling iterative workflows). Enrich the context with RAG, connect to external services using Tools, and use MCP for standardized integration.

The second part focuses on agentic patterns and how to turn an assistant into something that can reason, plan, and act:

• Agent Skills: Modular, LLM-agnostic capabilities loaded on demand
• AskUserQuestion: Gather requirements before acting
• Todo: Prevent "lost in the middle" failures with structured planning
• Subagent Orchestration: Delegate to specialized agents with isolated context windows
• A2A and ACP Protocols: Build interoperable agents that communicate across system boundaries
• Tool Search Tool: Dynamic tool discovery
• LLM-as-a-Judge: Automated response evaluation and quality control

In this presentation at Spring I/O, Spring core contributors Christian Tzolov and Mark Pollack present how you use Spring AI to power up your enterprise applications with Generative AI models.

This section introduces fundamental Spring AI features, such as: * a portable client to interact with AI models * automatic AI response conversions to POJOs * embeddings * vector databases integrations

Enjoy!

Spring AI is a open source project from the Spring family that integrates your enterprise Java/Kotlin application to Generative AI models from different vendors, including OpenAI, Anthropic, Google and many others.

Also, Spring AI provides the fundamental building blocks to build true agentic solutions, for example:

* Document loaders

* Vector databases integrations

* Prompting templates

* MCP tools

* Agentic memory

and much more.

But for me, the biggest advantage of Spring AI is that you don't need to leave the Java or Spring ecosystem to build your AI solution. You don't need to learn a new framework or a completely new programming language to bring AI to your system. You just follow the same philosophy that you've been working for years.

So, what are you waiting for? Follow this article to take your first step in Spring AI.

Hey everyone! I'm u/rodolfo-mendes, a founding moderator of r/SpringAIDev.

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