Su San, former staff at several leading tech companies, is a top creator on Juejin and a premium creator on CSDN, and runs the free coding practice site www.susan.net.cn.
The article explains how to implement a Loop automation system using three essential Markdown files—AGENTS/CLAUDE, STATE, and SKILL—detailing their roles, safety rules, verification steps, prompt commands (/loop and /goal), and a step‑by‑step setup from zero to a near‑unattended AI‑driven workflow.
The article explains why AI coding tools like Claude Code need a concise CLAUDE.md onboarding file, details what should be included, offers concrete best‑practice tips such as keeping the file under 200 lines, using positive directives, leveraging Hooks and AGENTS.md, and provides troubleshooting steps and team‑collaboration strategies.
ZCode is positioned as the official development environment for GLM‑5.2, offering a desktop AI programming workspace that integrates model connection, task management, Git tracking, remote control, and a Goal mode to streamline long‑running coding tasks across macOS, Windows, and Linux.
The article explains why deep nesting of if…else statements harms readability, maintainability and testability, and shows how the Java Easy Rules engine can extract business logic into reusable rule objects with multiple definition styles, lightweight architecture, and integration options.
The article benchmarks three Chinese multimodal large models—Step 3.7 Flash, MiniMax M3, and Qwen 3.6‑flash—across two real‑world tasks, measuring output quality, API latency, and token cost, and concludes that Step 3.7 Flash consistently offers the best speed‑cost trade‑off for production use.
The article explains why AI tasks suffer from long‑lasting, blocking calls, and shows how Apache RocketMQ 5.5.0’s LiteTopic transforms synchronous multi‑agent workflows into asynchronous, non‑blocking pipelines, boosting throughput, preserving session state, and providing smart GPU scheduling.
This article compares LangChain4j and LangGraph4j, explaining that the former is an AI capability integration layer for Java while the latter is a state‑graph workflow engine, and guides developers on when to use each based on features such as model access, tool calling, multi‑agent orchestration, conditional routing, checkpointing, and version maturity.
The article analyzes how enterprise AI has shifted from generating answers and reports toward agents that can understand business goals, integrate with organizational processes, and drive concrete decisions, emphasizing the need for synchronized technical and organizational systems to turn insights into actions.
This article explains FastAPI’s core concepts, compares it with Spring Boot and Flask, shows why its ASGI‑based architecture delivers superior performance, provides step‑by‑step setup, code examples, benchmark results, pros and cons, and practical use‑case recommendations for Java developers.
OpenAI quietly unveiled the GPT-5.6 series on June 26, introducing three variants—Sol, Terra, and Luna—with new Max and Ultra modes, striking benchmark scores, a steep pricing structure, and a government‑mandated limited rollout that restricts access to about 20 approved partners.
