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OpenGCUA Guide: The Open-Source Approach to Letting AI Actually Use a Computer
OpenGCUA is an open-source generalist computer-use agent from the Tongyi-MAI team. This guide breaks down its accessibility tree, code execution, and background operation design, checks the paper's 82-task numbers, and gives macOS install steps, three adoption paths, and an isolation plan for its arbitrary-code-execution risk.
Build Your First AI Agent in Seven Steps: from environment to a minimal production pass
Adapted from the MIT-licensed awesome-agentic-ai-zh integrated tutorial: one 'paper assistant' project wires up environment setup, your first LLM call, the four-part prompt, tool use, the agent loop with reflection, RAG memory, evals with observability, and the smallest interface. Every step ships minimal runnable code and safety rails; the local Ollama path costs 0 in API fees.
After You Press Enter: From 0.03 s to 0.85 s, What Your Question Goes Through
One real API call dissects the full chain of a question: 35 ms to establish the connection, microseconds to tokenize, 474 ms for the model to read your whole question, 380 ms generating it token by token — 854 ms in total. Includes the complete reproducible measurement method, and one counterintuitive conclusion: 96% of the time is not in the network but inside the model.
Copying Commands from the Web into the Terminal: Why It Often Fails
You copy a command from a tutorial, paste it into your terminal, and get a syntax error or command not found — this article explains the four most common reasons: smart quotes, truncated multi-line commands, invisible whitespace characters, and pasting into the wrong shell. Each comes with an immediate verification method.
Your First LLM API Call: Tokens, Billing, and Common Errors
Send your first LLM request with Python's openai SDK: understand the division of labor among system, user, and assistant message roles; the trade-offs of temperature, max_tokens, and streaming; token billing concepts and usage estimation; and finally, a troubleshooting guide for the errors every beginner will meet.
Set Up Your LLM Dev Environment in Five Minutes
Build a development environment that can call an LLM API from scratch: installing Python, virtual environments, getting an API key, and managing environment variables, then verifying the whole chain with a single curl command. Complete commands for both macOS and Windows, with a focus on keeping your key safe and out of git.
Your First Agent: A Hello World That Uses Tools
Hand-write an Agent that actually does things, without any framework: it checks the weather, does arithmetic, and loops on its own until the task is complete. A step-by-step breakdown of the six steps of the Agent loop, its termination conditions, and the common pitfalls — once you've written it, you'll understand what frameworks do for you.
What Is LangGraph: From Linear Chains to State-Machine Agents
Using kitchen and subway-map metaphors plus five diagrams, this guide explains LangGraph states, nodes, and edges, with a complete runnable example.
Complete LangChain Tutorial 2026: Building Enterprise-Grade LLM Applications from Scratch
The most detailed LangChain 2026 tutorial: covering LCEL, RAG, Agent, LangGraph, LangSmith. From installation to production deployment, with complete code examples.
A Complete Tutorial for Open Multi-Agent (OMA): A TypeScript Multi-Agent Orchestration Framework from Goal to Task DAG
An in-depth look at OMA (open-multi-agent) v1.8.0: a TypeScript-native multi-Agent orchestration framework with Goal-Driven Task DAG, Checkpoint resume, Consensus verification, and support for 10+ LLM providers. Includes complete code examples and a hands-on tutorial.
Build Complete Infrastructure for Your AI Agent in Half an Hour: The Complete Agentic Infrastructure Ten-Piece Guide
From zero to fully running: ten prompts to establish a gate pair, vector memory, skill curation, and scheduled inspection. Solves the skill-skipping problem caused by LLM confidence bias, so your Agent never loses its memory again.
Webb-Site: The Essential Hidden Treasure for Hong Kong Stock Research, a One-Click Tool to Get Annual Report PDFs for All Listed Companies
David Webb's independent Hong Kong stock database webb-site.com is an overlooked treasure. It directly provides PDF links from hkexnews.hk, listing on one page all annual reports and interim reports of a company from listing to present, completely bypassing hkexnews's internal stock ID restrictions. This article includes a complete usage tutorial, a known ID mapping table, and a batch download solution.
A Complete Tutorial for Matt Pocock Skills: The 115K Star AI Coding Engineering Discipline System, a Full Walkthrough of 15 Skills from Installation to Practice
mattpocock/skills: 35 Agent Skills released by TypeScript legend Matt Pocock from his own .claude directory, with 115K+ Stars, 2.7M+ installs, and 60K newsletter subscribers. This is not vibe coding; it is an AI coding discipline system condensing decades of software engineering experience.
MemoryHub Practical Installation and Complete Usage Guide: From Zero to Four Platform Automatic Memory Capture
A step by step guide to installing MemoryHub v2.0: from Docker environment preparation, one click pip installation, four platform MCP configuration, Dashboard usage tips, to the complete process of daily maintenance and troubleshooting.
Complete Guide to 14 Financial Services AI Skills: From Deal Sourcing and M&A Models to Catalyst Calendars
A complete introduction to the 14 OpenClaw financial skills derived from Anthropic Claude for Financial Services, covering three major areas: investment banking (7), private equity (6), and equity research (1), including each skill's command meanings, use cases, and hands-on tutorials.
A Deep Dive into Claude Code
From installation and configuration to advanced techniques, fully master the Claude Code CLI tool, actually powered by DeepSeek V4 / ModelStudio, to boost everyday development efficiency.
DeepSeek V4 Flash / V4 Pro API Best Practices and Performance Comparison
Complete guide to the DeepSeek V4 series models: comparing performance, pricing, and use cases of V4 Flash vs V4 Pro, with API call examples and cost estimates.
Three-Layer Framework LLM API Configuration Summary: DS V4 Pro, Qwen 3.6, oMLX Local
A complete guide to configuring DeepSeek V4 Pro, Qwen 3.6-Plus, and oMLX local Qwen3 Coder Next across Hermes Agent, OpenClaw, and Claude Code.
Complete Development Environment Setup on Mac Studio M3 Ultra
Build an AI development environment from scratch on Mac Studio M3 Ultra (512GB RAM): system configuration, Homebrew installation, basic toolchain, and performance tuning.