#Spring AI
18 related articles
Java Developer's Guide to AI Applicati…
·3 min
Java Developer's Guide to AI Application Development: Career Path, Skills, and Hands-On Strategy
A practical guide for Java developers transitioning to AI app development. Includes a 45-day learning plan covering Spring AI, RAG, Agent skills, plus resume and interview strategies.
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Tutorials·2 min
How AI Coding Skills Work: From Function Call to Sub-Agent Implementation
Deep dive into how AI coding Skills work: from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
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Tutorials·2 min
How AI Coding Skills Work: From Function Call to Sub-Agent Implementation
Deep dive into how AI coding Skills work technically, from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
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Tutorials·1 min
Spring AI Alibaba Agent Framework: Three-Layer Architecture and Learning Path
Deep dive into Spring AI Alibaba Agent Framework's three-layer architecture: Spring AI foundation, Graph framework, and Agent Framework, with a recommended learning path for Java developers.
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Tutorials·2 min
Getting Started with Spring AI Alibaba: Best Practices for Java Developers to Integrate LLMs
Deep dive into Spring AI Alibaba's positioning and value, using a JDBC analogy to help Java developers understand how to integrate LLM capabilities into existing microservices architecture.
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Tutorials·3 min
Java Developers Transitioning to AI Engineers: New Interview Trends and Learning Roadmap
Deep analysis of interview trends for Java developers transitioning to AI engineers, covering LLM integration, RAG, Spring AI framework practice, with a complete learning roadmap.
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Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
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Tutorials·3 min
Getting Started with Spring AI Alibaba: The Go-To Framework for Java Developers Integrating LLMs
A deep dive into Spring AI Alibaba's core positioning and advantages, helping Java developers quickly understand how to integrate LLMs through this framework.
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Tutorials
Spring AI + MCP Protocol in Practice: …
·3 min
Spring AI + MCP Protocol in Practice: Tool Calling, Security Authentication, and Enterprise Deployment
Deep dive into Spring AI and MCP protocol integration, covering tool calling, OAuth security, horizontal scaling, and context optimization for enterprise AI Agent services.
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Deep Dives
Deep Dive into Cursor Skills: From Fun…
·4 min
Deep Dive into Cursor Skills: From Function Call to Practice
Deep dive into Cursor Skills' underlying principles, from Function Call and MCP protocol to Workflow Agent, with Spring AI Alibaba practical demo for any LLM.
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Tutorials
Spring AI Alibaba MCP Integration in P…
·3 min
Spring AI Alibaba MCP Integration in Practice: Full Workflow from Server Setup to Client Invocation
Learn how Java developers can build MCP Server and Client using Spring AI Alibaba, define tools with @Tool annotations, and integrate with AI clients like Trae for LLM-powered business data access.
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Tutorials
Spring AI Agent Utils: A Java Agent To…
·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep 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.
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Tutorials
MCP Protocol Practical Guide: The Stan…
·2 min
MCP Protocol Practical Guide: The Standard Interface for Connecting LLMs to Everything
Deep dive into MCP (Model Context Protocol) principles and practical applications. Learn how LLMs connect to external tools via MCP to become agents, covering Java tech stacks, MCP Server ecosystem, Cherry Studio demos, and A2A protocol comparison.
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Tutorials
The Complete Guide to Spring AI: A Ful…
·3 min
The Complete Guide to Spring AI: A Full Learning Path for Java Engineers Building AI Applications
A comprehensive guide to Spring AI covering LLM integration, prompt engineering, RAG knowledge bases, and five AI Agent patterns, with three enterprise projects for Java engineers.
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Tutorials·3 min
Getting Started with Spring AI: How Java Developers Can Integrate Large Language Models
Spring AI is the LangChain for Java, helping Java developers integrate LLMs using Spring Boot conventions. This guide covers its 6 core features, setup requirements, and enterprise positioning including RAG, Tool Calling, and Chat Memory.
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Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
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Deep Dives·4 min
The Four Stages of AI Agent Evolution: A Complete Guide from Copilot to Multi-Agent Collaboration
Deep dive into the four stages of AI Agent evolution: Chat, Copilot, Agent, and Agentic AI. Covers ReAct framework, Spring AI stack, and multi-Agent architecture design for 2025.
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Deep Dives·4 min
From Copilot to Agentic AI: A Complete Guide to Multi-Agent Collaboration Architectures
Deep dive into AI's four-stage evolution from Chat to Agentic AI, covering multi-Agent architectures, ReAct framework, and MCP protocol for developers.
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