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TutorialsA systematic four-stage learning roadmap for programmers transitioning to AI Agent development, covering core theory, ReAct and classic paradigms, Prompt engineering, and hands-on projects.
Deep DivesWhy do longer Prompts make AI Agents less stable? This article explains the control flow first architecture, replacing natural language control flow with code orchestration to boost multi-step reliability from 40% to over 90%.
Product ReviewsTesting ChatGPT, Manus, and Kimi on the same investment analysis task reveals how multi-agent architecture, fault tolerance, and parallel workflows define the real capability boundaries of AI Agents in professional finance.
TutorialsDeep dive into Huawei's 100-page Hermes Agent manual: five-layer memory architecture solving AI amnesia, self-evolution loops for continuous optimization, and multi-agent collaboration engineering.
TutorialsHow to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
TutorialsLearn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.