202 related articles

Set up an AI coding workstation on NVIDIA Jetson using VS Code + Claude Code. Covers JetPack NVIDIA Skills, token budget management, headless SSH dev, and coding agent best practices.

A complete Python learning path for beginners covering three modules: Fundamentals, Intermediate, and Hands-On Practice — including web scraping, office automation, and data analysis.

Apple's 1-bit compression fits 27B models on iPhone, Meta builds custom chip Iris, China's 100K-GPU cluster goes live, Samsung enters AI PC — a deep dive into AI's new full-spectrum competition.

No coding required! This guide breaks down the complete Claude workflow: custom Projects, batch SEO content, one-sentence tool building with Artifacts, and Claude Code terminal ops—with real traffic-growth cases.

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.

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.

AI agents are revolutionizing JS reverse engineering. This deep dive covers built-in tool chains, automation modes, prompt engineering for e-commerce, and full pipeline automation from parameter extraction to database storage.

A deep dive into AI testing workflows: API capture, test case generation, Agent orchestration, and automated execution. Learn the two core challenges — incomplete information and mandatory human review.
Coasty: API Infrastructure Built for C…
Coasty (YC S26) is an API platform for computer-use agents, wrapping screenshot capture, mouse/keyboard control, and session management into a unified interface so developers can focus on agent logic.

OpenAI merges ChatGPT and Codex into a super app and releases three new GPT-5.6 models: Sol, Terra, and Luna. A deep dive into four hands-on workflows—Computer Use, Loops, and multi-threading—for the AI agent era.
Meta Muse Spark 1.1 Released: A Deep D…
Meta officially releases Muse Spark 1.1, the first model in the Spark series to offer an API, with a focus on strengthening agentic tool calling and computer use capabilities.

As Cursor and GitHub Copilot redefine programming, where do Vim users go? This article analyzes the tension between AI tools and Vim, and three key strategies.

RoughCut is a fully automated AI editing tool generated by Codex, supporting talking-head, unboxing, and commentary modes with a semi-automated publishing system.
Reverse-Engineering Web Apps: A New Ap…
Explore a new approach to AI Agent tool integration: reverse-engineering web apps to turn API-less pages into callable Agent tools, with analysis of MCP synergy and challenges.

In-depth hands-on review of Alibaba's open-source web automation tool PageAgent: three integration methods, script execution analysis, and a full breakdown of current limitations. Add AI Agent capabilities to web pages with one line of JS.

BrowserWing is an open-source browser action recorder (1300+ GitHub stars) with 78 built-in scripts for GitHub, Bilibili, Zhihu, and more. Record once, run repeatedly, and let AI Agents reliably execute fixed web workflows.

APA (Agentic Process Automation) merges LLM agents into RPA, supporting natural language, operation manuals, and video recording to generate scripts—paired with financial-grade security and three-layer protection for enterprise automation.

OpenAI launches the GPT-5.6 family—Sol, Terra, and Luna—alongside ChatGPT Work, a new desktop app, and Sites. AI evolves from a chat tool into a true productivity partner, completing financial analysis, presentations, and cross-platform collaboration in one operation.

The MELTing Point paper is the first to evaluate mobile LLM performance in real user scenarios, covering iPhone, Samsung, Pixel and more, testing TinyLlama, Mistral-7B and others—revealing GPU inference gains, 47°C heat warnings, and prefill-decode disaggregation.

A developer stress-tested GPT-5.6 for six weeks across 67 projects, burning $180K-$240K in inference. Real cases of task persistence, Rust rewrites, autonomous browser control — plus honest frontend and 3D shortfalls.