Not every cache hit requires an exact match. With semantic caching, Spring AI can recognize when two differently worded questions mean the same thing and serve a cached response instead of calling the LLM again. #SpringAI #AI
https://medium.com/@thetalkingapp/spring-ai-recipe-semantic-caching-548274a1733a
Python isn’t the only way to build #AIAgents anymore. With #SpringAI, #Java apps get memory, RAG, tools & model switching—all behind one #API. Same code runs from local Ollama to AWS Bedrock.
Bezsonov Yuriy & sascha242 show how: https://javapro.io/2026/04/30/building-production-ready-ai-agents-with-java-and-spring-ai/
A well-stocked toolbox is useful. That is, until you have to dig through dozens of tools to find the one you need. The same is true for MCP servers, where exposing fewer tools can often make an AI application faster, cheaper, and more focused.
https://medium.com/@thetalkingapp/spring-ai-recipe-controlling-mcp-tool-visibility-18258e66f278
Confused by the exploding number of #AI tools in the #JVM ecosystem? Teams mix #SpringAI, #LangChain4j, MCP & #Ollama without understanding the layers underneath. Artur Skowronski explains what each part of the #Java AI stack is actually for: https://javapro.io/2026/06/03/the-gen-ai-iceberg-java-tooling-edition/
@langchain4j
It’s been a busy week in the #Java ecosystem!
Highlights include:
➤ Lifecycle changes with two of the JEPs that were targeted for JDK 27; the GA release of Koog 1.0; point releases of Hazelcast, Quarkus, Hibernate and JHipster; the 8th milestone release of Spring AI 2.0; and introducing Endive, a JVM-native WebAssembly (Wasm) runtime.
🔗#InfoQ News Roundup: https://bit.ly/4vIiYxB
#JDK27 #SpringAI #Quarkus #JHipster #Hibernate #WebAssembly #Wasm
Not every tool can return a result immediately. When an MCP tool needs extra time to complete, progress notifications allow the server to keep the client informed, providing visibility into long-running operations and a better overall user experience.
https://medium.com/@thetalkingapp/spring-ai-recipe-mcp-tool-progress-474a080621e5
MCP tools don't always have everything they need to do their job. With MCP Elicitation, a tool can pause, gather additional context from the client, and then continue with a more complete understanding of the task at hand.
https://medium.com/@thetalkingapp/spring-ai-recipe-mcp-elicitation-cdfed4dd213e
🚀 Jakarta EE + Spring AI + AWS + Agentic AI
Enterprise software is rapidly evolving beyond traditional CRUD applications.
Modern enterprise AI systems increasingly use:
✅ Jakarta EE backend
✅ Spring AI orchestration
✅ AI Agents + RAG
✅ AWS cloud infrastructure
✅ Autonomous workflows
#Java #JakartaEE #SpringAI #AWS #AgenticAI #EnterpriseAI #AI #SoftwareEngineering #CloudComputing
MCP tools usually serve LLMs. But with sampling, the tools can turn around and ask the LLM for help. In this recipe, you’ll see how MCP Sampling enables a server-side tool to collaborate with the client’s LLM to produce richer, more intelligent results.
https://medium.com/@thetalkingapp/spring-ai-recipe-mcp-sampling-87b3db2a58da
🤖 Testing & observing AI agents shouldn't be an afterthought. If you wait until production to see how your agents behave, you're playing a risky game.
3 expert speakers will demonstrate how to build robust agentic apps using Spring AI, and show you how to take control of the chaos.
🔗 Save your seat today: https://www.linkedin.com/events/7460341650775605248/
#AIagents #SoftwareTesting #SpringAI #OpenTelemetry #ModelContextProtocol
CrAIg Walls
JAVAPRO
InfoQ
myexamcloud
Microcks