#Java
43 related articles
Zero to One: Java + DeepSeek in Practice — A Programmer's Guide to Transitioning into AI Large Model Development
Based on a Bilibili livestream tutorial, this article explains how Java programmers can transition into AI large model development from zero, covering skill paths, building your first Java AI app, resume packaging, and job-hunting strategies to help you seize opportunities in the large model era.
Spring Boot + LLM: Ship AI Features Without Building a Python Service
Integrate LLM features directly into your existing Java API with Spring Boot and Spring AI for ticket auto-classification: structured output, enum guardrails, deadlines, concurrency budgets, retry pitfalls, fallback, and a launch checklist.
Java Programmers Transitioning to AI Large Model Development: A Zero-Basics Practical Guide
A zero-basics AI large model application development guide for Java programmers, covering core Bilibili course content: large model API calls, prompt engineering, RAG from scratch, Spring AI and LangChain4j framework applications, and vibecoding project practice paths.
Building Semantic Search and RAG with pgvector + Java: No Separate Vector Store Needed
pgvector turns PostgreSQL into a vector store: build semantic search and RAG with Java and Spring Boot, no separate vector database. Covers HNSW indexes, JDBC vector queries, RAG pipelines, tenant isolation, and recall evaluation.
Three Lessons from Building a Java Repair Tool with Local LLMs
A developer shares practical lessons from building a Java code repair tool with local LLMs: context window management, structured prompt design, and a compile-verify loop for AI programming tools.
Can Java Still Land You a $300K Salary? A JP Morgan Engineer Breaks Down the Truth About Backend Job Hunting
JP Morgan SDE2 Robin Gautam breaks down backend job hunting: DSA vs. development, common student mistakes, payment systems, Java in the AI era, and a roadmap to $300K+.
Spring AI Practical Guide: Building a RAG + MCP Intelligent Engine with Java
A practical Spring AI guide for Java developers: integrate RAG knowledge bases, real-time web search, and MCP tools to build enterprise-grade AI applications.
What Is Spring AI Alibaba? A Beginner's Guide to the Bridge Framework Connecting Java and LLMs
What is Spring AI Alibaba? Using a JDBC analogy, this guide explains how Spring AI Alibaba bridges Java microservices and LLMs — a must-read for Java developers.
Getting Started with Spring AI: A Large Language Model Integration Framework for Java Developers
Spring AI is a Java framework for LLM integration, similar to Python's LangChain. Learn its core features: structured output, Chat Memory, RAG, Tool Calling, and MCP protocol.
Java 27 Deep Dive: How Default Changes Are Quietly Reshaping Production Environments
Java 27 has just 9 JEPs but changes key defaults: compact object headers on by default, G1 as unconditional default GC, Flight Recorder redaction, and built-in post-quantum TLS 1.3.
Java 27 Released: OpenJDK Official Ann…
Java 27 Released: OpenJDK Official Announcement and Community Buzz
OpenJDK officially releases Java 27, sparking discussion on Hacker News. Covers the six-month release cadence, language feature maturity, GC improvements, and upgrade recommendations.
LangChat ai-tutorials: A Beginner's Guide to AI App Development for Java Developers
LangChat ai-tutorials is a beginner-friendly Java AI tutorial series built on langchain4j, covering RAG, Agent, and MCP for Java developers entering AI development.
TutorialsSpring 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.
TutorialsJava + UniApp in Practice: Full-Stack Development of a Stray Pet Rescue Mini Program
A detailed guide on building a stray pet rescue WeChat Mini Program with Spring Boot and UniApp, covering C2C adoption flow, WebSocket chat, and review mechanisms.
TutorialsJava 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.
TutorialsComplete 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.
TutorialsJava Full-Stack Beginner's Guide: Application Domains, Three Major Platforms & Learning Path Explained
A beginner's Java full-stack guide covering Java's origins, real market position, enterprise server-side strengths, Java SE/EE/ME platforms, and a complete learning path from basics to full-stack.
TutorialsSpring 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.
TutorialsSpring 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.
TutorialsThe 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.