42 related articles

Build an enterprise RAG knowledge base Q&A system using Spring AI 2.0, Cursor AI programming, Ollama local deployment, and Redis vector storage. Runs on just 4GB VRAM.

Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, Tools parsing moving up, a built-in Agentic mechanism, MCP switching to Streamable HTTP, and an on-demand tool Advisor.

Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, lifted Tools parsing, built-in Agentic mechanism, MCP switch to Streamable HTTP, and an on-demand tool-loading Advisor.

Spring AI 2.0 brings five core updates: mandatory Spring Boot 4 upgrade, Tools parsing moved up, built-in Agentic mechanism, MCP switch to Streamable HTTP, and on-demand tool-loading Advisor.

A deep dive into Spring AI 2.0: provider-agnostic APIs, RAG with vector databases, and how Java developers can build LLM apps using the Spring ecosystem.

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.
教程攻略Build a RAG enterprise knowledge base Q&A system from scratch using Spring AI 2.0 and Cursor AI. Covers Ollama local LLM deployment, Redis vector database, document parsing, vectorization, and intelligent retrieval.

An in-depth look at the Log4Shell vulnerability from a core Log4j maintainer's perspective, exploring open source sustainability, supply chain security, and the burden on volunteer maintainers.

A deep dive into the Log4Shell incident from the perspective of Log4j's core maintainers. Exploring the open source sustainability crisis, supply chain security awakening, and the challenge of volunteers maintaining critical infrastructure.

Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.

Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.

From the fatal Apollo 1 fire to Apollo 8's daring lunar orbit to Apollo 11's successful landing—revisiting the disasters, fears, and compromises of the Apollo program and their lessons for today's return to the Moon.

A ten-year open source maintainer shares how to build a universal tag-to-release GitHub Action, covering its opinionated design philosophy, dogfooding validation, and AI-assisted development.

Discover why beginners study SpringBoot for six months without getting started. Learn the 'focus on the big picture' methodology and evolve a simple Java project into a runnable enterprise-level SpringBoot application step by step.

Discover why beginners study SpringBoot for six months without getting started. Learn the 'focus on the big' methodology, and evolve a simple Java project step by step into a runnable enterprise application with IDEA.

A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.

A deep dive into ByteDance's Coze platform: tool categories, positioning vs. Dify, skill store, multi-agent collaboration, and workflow building — your AI Agent selection guide.

Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.

How can new graduates transition from software engineer to platform engineer? This article breaks down the path of joining as a Grad SWE first, then transferring internally, analyzes C# vs Python trade-offs, and offers a 14-month prep plan for AI/ML infrastructure.

A practical guide for Java developers to build AI apps without switching to Python. Learn LangChain4j, RAG, Function Calling, and MCP through an airline customer service project.