111 related articles

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.

A deep dive into building verifiable, self-evolving Agent automation loops with Claude Code and Codex — covering Loop Contracts, four trigger types, three-phase execution architecture, and Evolve Loops.

How should test engineers choose AI tools? This guide breaks down the pitfalls of pure AI solutions and recommends a hybrid strategy using tools like DeepSeek, TRAE, Claude Code, and Skill encapsulation.
Deep Dive into AI Agent Skill Design: …
A deep dive into Skill design philosophy from Anthropic's Claude Code team and Perplexity's Agent team, covering the Tax Test, Gotchas Flywheel, progressive disclosure, and Eval-First practices for building high-quality AI Agent skill systems.
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.

An in-depth analysis of the AI-driven software testing paradigm: with Skill and CLI as the core hub, supporting both platformized management and digital employees, helping testing teams transform from script writers into capability builders.

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.

An in-depth hands-on test of the GPT-5.6 series' three models—Sol, Terra, Luna—compared with Fable and Sonnet 5. Sol wins overall at nearly half the price. Full analysis of prototyping, code debugging, and browser use.

An in-depth guide to installing, logging in, and using OpenAI Codex CLI: call AI directly in your local terminal to modify code, refactor components, and add file and image context, with Git branch management for an efficient local AI coding workflow.

How Base44's product team scaled from a single founding engineer to an 80-person team with Claude Code. Covers AI-assisted onboarding, code review, user evaluation, and QA automation.

GPT-5.6 is officially released, merging ChatGPT and Codex into one app and launching the three-tier Sol, Terra, and Luna models. A detailed breakdown of 16 hands-on tests plus Worker mode and Codex dev upgrades.

OpenAI officially merges its coding agent Codex with ChatGPT into a unified desktop app, adding new coding workflows, a Chrome extension, a built-in browser, and GPT-5.6-powered Computer Use capabilities.

Claude Code is one of the most powerful AI coding agents, running in the terminal to write code, batch operations, build web projects, and more. This guide covers installation, connecting local models via CC Switch, permission modes, CLAUDE.md, Skills, MCP, Subagents, and more.

Fortress is an open-source stealth Chromium built for AI Agents. It eliminates automation fingerprints to bypass Cloudflare and other anti-bot systems.

Breaking down a 10-hour Python course for absolute beginners — covering syntax, OOP, functional programming, web scraping, and automation, with mind maps and exercises.

How can beginners learn Python without getting lost? This guide outlines a 3-stage learning path covering basics, advanced topics, and hands-on practice in web scraping, data analysis, and office automation.

A plain-language guide to how Python web scrapers work: from HTTP requests and responses, HTML tag parsing, to the complete three-step data scraping workflow, with a focus on the three legal red lines and compliance advice.