#Windows AI setup
488 related articles
·4 min
NRF52840 Bluetooth Keyboard Development: Hardware Selection and AI-Assisted Project Setup
Building an NRF52840 Bluetooth left-hand keyboard from scratch: why NRF52840+ZMK, AI-assisted project init, pin assignment, and real-world debugging of Bootloader offsets and Kconfig configuration.
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·3 min
Free Claude Opus 4.6 Access: Complete Guide to Connecting Antigravity via CLIProxyAPI
Use CLIProxyAPI to connect Antigravity's free models to Claude Code, Cline, and more. Access Claude Opus 4.6 Thinking and Gemini 3 Pro at zero cost. Full setup guide included.
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·2 min
Heap Code: The Open-Source VS Code AI Coding Assistant That Truly Supports Local Models
Heap Code is an open-source VS Code extension supporting local models via Ollama and LM Studio, plus OpenAI-compatible APIs. Features completions, chat, inline edit, and agent mode — zero telemetry, no account required.
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·3 min
Zero-Code Research: Using AI Agents to Run Complete Machine Learning Experiments
No coding required: use AI agents like Codex and Claude Code to complete full ML experiments via natural language. A real case study with a heart disease dataset.
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·3 min
No-Code Research: Using AI Coding Tools to Complete the Full Machine Learning Pipeline
No coding skills? No problem. Learn how AI tools like Codex and Claude Code let researchers complete ML workflows — data cleaning, model training, visualization — using only natural language.
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·3 min
OpenClaw Multi-Agent AI Programming Workflow in Practice: From Coder to Manager
Deep dive into OpenClaw multi-agent AI programming workflows: context layering, CMUX parallel terminal management, work trees, and manager-perspective debiasing for scalable AI dev automation.
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·3 min
GPT-5.6 Real-World Test: The True Capability Limits of AI-Assisted Game Development
A creator tests GPT-5.6 Codex on two real projects: an Android MAUI app and a tower defense game prototype. Zero code written for the app; the game demo surfaces multiple bugs. Honest look at AI coding's real limits.
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·3 min
AI Testing in a Closed Loop: Full Pipeline from API Collection and Test Case Generation to Agent-Driven Execution
Full breakdown of a real AI testing pipeline: API collection, doc enrichment, AI test case generation, Agent-driven execution, and test reports — with Skills, RAG, and Harness engineering.
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·3 min
Zero-Cost VibeCoding: Complete Guide to Connecting Local Ollama Models to Codex
Step-by-step guide to running local open-source models (Qwen3/Gemma) with Ollama, connecting to Codex via CC Switch for zero-token AI coding. Works on a 6GB VRAM laptop.
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·2 min
Waveloom: An Open-Source Terminal AI Coding Agent Deeply Optimized for DeepSeek
Waveloom is an open-source terminal coding Agent deeply optimized for DeepSeek, with cache hit rates near 99% to drastically cut token costs. Supports Linux, Windows, macOS, and Claude Code Skills.
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·2 min
LangGraph Multi-Agent Architecture in Practice: From Core Components to Production Deployment
A deep dive into LangGraph multi-agent architecture — covering hierarchical, network, and pipeline patterns with three hands-on projects using LangGraph 0.3.
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·1 min
Apple's Vibe Coding Showcase: What Did College Students Build with Mac + AI?
Apple hosted a college AI showcase in Guangzhou where students used Mac and AI tools to build a smart anti-sedentary chair, AR robotic arm, dental simulator, and more. A deep dive into Vibe Coding and Apple's AI hardware strategy.
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·3 min
OpenAI Codex IDE Extension in Practice: A Complete Guide to VS Code Installation and Local Development
A hands-on guide to installing and configuring the OpenAI Codex IDE extension, covering its three working modes and Agent demo. Supports VS Code, Cursor, and Windsurf.
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·3 min
Claude Code Enterprise Guide: Environment Setup, Git Workflows, and Switching to Chinese AI Models
Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.
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·3 min
Cherry Studio + MCP: A Practical Guide to Building AI Agents with Local Deployment
Learn how to build an automated AI agent using Cherry Studio, MCP protocol, and locally deployed models — covering DeepSeek integration, web scraping, and private knowledge base setup.
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·3 min
MCP + Skills AI Reverse Engineering Toolchain: Technical Capabilities and Compliance Boundaries
A technical deep-dive into AI-assisted reverse engineering: how MCP, Skills libraries, and Frida toolchains work together, their real capability limits, and the legal boundaries of iOS/Android/Web reverse analysis.
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·2 min
vLLM Inference Framework Deep Dive: A Practical Guide to High-Concurrency DeepSeek Deployment
A deep dive into vLLM's five core features — KV cache management, continuous batching, and distributed inference — plus a full setup guide for deploying DeepSeek on a cloud server.
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·3 min
AI Coding Agents in Practice: An Efficient Configuration Guide for Cursor and Codex
How to configure Cursor, Codex, Devin, and other AI coding agents for context management, code quality, and cross-tool collaboration. Practical tips on rule files, TDD, and structured context storage.
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·3 min
Cherry Studio + MCP + Ollama: The Complete Guide to Building a Local AI Agent and Private Knowledge Base
A hands-on guide to building a local AI agent and private knowledge base using Cherry Studio, MCP, and Ollama — with web scraping, report generation, and terminal control.
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·2 min
Running Qwen 122B on 8GB VRAM: A Complete Guide to Quantized Local Deployment
A Bilibili creator ran Qwen 122B with 256K context on just 8GB VRAM + 64GB RAM using llama.cpp. Full breakdown of quantization, deployment params, performance, and cost-effective alternatives.
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