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TutorialsA complete beginner's guide to LLM application development: learn the three key directions (API calling, RAG, Agent), master frameworks like LangChain, and follow a step-by-step learning path to become an AI application developer.
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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.
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TutorialsDecode LLM naming conventions, understand 32B parameters & AWQ/GGUF quantization formats, with 4-bit VRAM estimation formulas, MOE model pitfalls, and model selection by GPU tier.
Product ReviewsA deep cost comparison between AI coding appliances and cloud LLM APIs. A 20-person team spending ¥480K/year on tokens can deploy 4 local OnePanel units at ¥99K each, breaking even in 2.5 months.
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TutorialsDeep dive into enterprise AI Agent four-layer architecture design (User, Gateway, Agent Service, Capability layers) with PDCA optimization methodology and dual manual+automated evaluation for production-grade Agent systems.
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TutorialsA systematic breakdown of seven core LLM learning modules covering environment setup, Prompt Engineering, RAG, Agents, dev frameworks, fine-tuning, and hands-on projects for developers.
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TutorialsDeep dive into OpenAI Codex plugin system architecture (Skills, Apps, MCP Server), four installation methods, and a macOS app development case study showing how plugins boost AI coding efficiency.
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Industry InsightsZhipu AI partners with Game of Thrones to create immersive AI interactions using GLM models for role-playing, branching storylines, and political intrigue.
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TutorialsLearn how to build a Mini-OpenClaw Agent framework using Vibe Coding with zero code, covering OpenClaw's architecture, LangChain integration, and AI-assisted development workflows.
TutorialsMost developers still copy-paste with AI coding tools. This guide covers the evolution from Copilot to Claude Code, detailing CLAUDE.md, Skills, and MCP to achieve Non-Interactive automated workflows.
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