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A systematic AI Agent development learning roadmap covering LLM API calls, ReAct framework, memory mechanisms, and multi-agent collaboration across four stages with timeline and project suggestions.
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A systematic guide to LangChain LLM application development, covering environment setup, core components (RAG, Chain, Memory), and Agent development to help developers master LLM app building.
Product ReviewsDeep dive into OpenSwarm, an open-source multi-agent system where 8 specialized agents collaborate to generate complete deliverables—research, charts, slides—from a single prompt.
TutorialsDeep dive into how EasyLLM CLI modifies Gemini CLI to support any LLM including local models, solving account barriers, model lock-in, and data security issues with code-level API integration.
TutorialsLearn how to build a ChatBI data analysis Agent from scratch using LangGraph + multi-MCP architecture, covering centralized-to-decentralized evolution, NL2SQL, agent orchestration, and enterprise deployment.
Deep DivesA systematic breakdown of AI's four-stage evolution from Chat Mode to Agentic AI, covering multi-agent architectures, ReAct framework, and MCP protocol.
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%.
TutorialsComplete guide to building AI Agents on Dify with zero code, covering tool integration, ESA search configuration, time awareness solutions, and Agent design best practices.