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A deep dive into Spring AI 2.0's core updates — with a hands-on airline assistant project showing how to build AI agents in Java using Tools, MCP, and Skills.

How can Java developers successfully transition to AI Agent engineers? A complete hands-on roadmap covering API operations, prompt engineering, RAG, Function Calling, and production deployment skills.

How can Java backend engineers transition to AI Agent development? This guide covers the evolution from Chat to Agentic AI, ReAct decision-making, MCP tool calling, and multi-Agent orchestration with Spring AI.

Java developers can build AI apps too! Learn LangChain4j fundamentals including RAG, Agents, Function Calling, and hands-on projects — no Python required.

How can experienced Java and backend developers pivot to AI? This deep-dive explains why the Agent direction is the best fit — skills transfer well, market demand is high, and the path from "using frameworks" to "understanding source code" is clear.

A complete Spring AI 2.0 guide for Java developers covering unified API abstraction, RAG, tool calling, MCP protocol, and enterprise projects to build AI Agents.

Deep dive into Spring AI Alibaba Agent framework covering core architecture, tool calling, RAG integration, multi-agent collaboration, and production deployment for Java developers.

A systematic 6-week Java backend interview prep roadmap covering JVM internals, Spring Boot, Redis, microservices, plus Spring AI, LangChain4j, and RAG for AI Agent development.
TutorialsDeep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
TutorialsA dedicated AI learning roadmap for Java developers covering Spring AI, LangChain4J, RAG, and Agent development — from fundamentals to production deployment.
TutorialsAn open-source project implementing Claude Code's core features in Java. Master AI Agent architecture, tool calling, task decomposition, and multi-Agent systems through 12 progressive lessons.
Product ReviewsIn-depth testing of Google Jules AI coding agent with a real Java backend project, revealing code generation quality, hallucination issues, and capability boundaries.
TutorialsA systematic guide for Java developers entering AI Agent development, covering core concepts, Workflow vs. Agent architecture comparison, Spring AI Alibaba selection, and resume positioning strategies.
Product ReviewsDeep dive into OpenClaw4J, an intelligent Agent framework built on Java 21 virtual threads and Spring AI, supporting tool calling, memory management, and multi-Agent collaboration for enterprise Java developers.

Learn how AI LLMs paired with MCP servers can fully automate Unity digital twin construction without manual operations. Covers MCP setup, Claude Code integration, and auto-generated conveyor scenes.

A systematic breakdown of the four-stage AI + penetration testing learning roadmap, covering Agent fundamentals, Web vulnerability discovery, enterprise automation, and advanced practice.

Hands-on review of Cline, a free open-source AI coding agent. Covers installation, Gemini API setup, building a to-do app with one prompt, and comparison with Copilot and Cursor.

Deep dive into DeepSeek Harness agent framework's "Everything is a Plugin" philosophy, comparing Rally, Standard, and PTC modes with real token consumption data and setup guide.

GitHub Trending Aug 26: ponytail teaches AI Agents to write less code, Anthropic launches official Claude Code plugin directory, and hister brings personal search sovereignty back.

Learn how to use LLMs like GPT and DeepSeek to automate browser environment patching in APP reverse engineering, compressing hours of manual work into minutes.