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OpenWork is an open-source alternative to Claude Cowork built on opencode with TypeScript. With 17,000+ GitHub stars, it offers data privacy, flexible model switching, and deep customization.

Deep analysis of LLM agent long-term memory security threats, covering persistence, statefulness, and propagation of memory poisoning, with a six-stage lifecycle defense framework.

A detailed guide to OpenAI Codex coding agent: understand how it differs from ChatGPT, how AI agents autonomously generate, debug, and test code, and why developers need to learn this new paradigm.

A systematic guide to AI Agent development covering core modules, framework selection, tool calling, data preparation, and production deployment to help developers build production-ready Agent applications.

A senior Java developer shares 7 years of IntelliJ IDEA configuration tips: JVM tuning, AI-assisted coding, Testcontainers testing, debugging tricks, and Spring toolchain setup.

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A detailed guide on building a full-process HR recruitment Workflow Agent with Spring AI Alibaba Graph, covering resume parsing, multi-dimensional screening, tiered questions, human-in-the-loop, and state rollback.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM basics, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM fundamentals, prompt engineering, and RAG to LangChain and multi-agent collaboration.

How Pinterest engineers built Medic for Apache Spark — a multi-agent auto-diagnosis tool — covering the evolution from a single ReAct agent, observability, log denoising, and end-to-end testing.

A developer tests Fan Browser Agent on a real Korean visa application: autonomous flow planning, filling 30+ form fields automatically, and handling upload errors.

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 focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.

A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.

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.

Multica is an open-source AI Agent management tool that unifies Claude Code, Codex, Cursor and more into one visual dashboard with kanban, task queues, and cloud deployment support.

A deep dive into the Agent Loop: how agents autonomously cycle through think→act→think, the difference from regular LLMs, ReAct paradigm origins, and how to implement one from a while loop.

Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.

A deep dive into ASE's core mechanism — the STATE_SYNC checkpoint token — and how it transforms stateless LLMs into stateful AI systems for complex multi-turn workflows.