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Learn how AI Skills are transforming software testing. This guide covers Skill architecture, learning paths, and real-world applications in API automation and WebApp testing.

Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.

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.

awman's --dynamic flag enables cross-framework dynamic workflows with multi-model collaboration. Explore its leader agent architecture, shared context design, and auto fault-tolerance mechanisms.

Learn how to use MCP (Model Context Protocol) to run adversarial tests on AI agents in the terminal, covering prompt injection, privilege escalation, and dangerous command execution scenarios.

Learn automation testing from scratch! This article breaks down a three-stage path: Selenium/Appium tools, Requests+PyTest API testing, performance testing and CI/CD, with real projects—build a complete skill set in 21 days.

Andrew Ng partners with JetBrains on a new course systematically teaching Spec-Driven Development. By writing high-quality specs, developers can precisely control AI coding agents, eliminate context decay, and boost intent fidelity.

Hugging Face's open-source ml-intern autonomously reads papers, writes training scripts, and finetunes LLMs, deeply integrating the HF ecosystem and smolagents. Explore its features and impact on ML careers.

A deep dive into pytest patterns: layered fixture management, parameterized coverage, mock isolation, coverage gates, and CI integration — upgrade your team from scattered scripts to a maintainable automated testing framework.

Can't make pure AI work? This guide explores the Semi-AI approach to API automation testing, covering key challenges, enterprise framework design, and how AI and frameworks work together for maximum impact.

Learn how to build an AI-driven API automation testing framework using Agent+Skill architecture with Claude Code, covering test case generation, script execution, and report output.

Learn how to build 6 testing agents using AI Skills for test case generation, Xmind mind maps, performance reports, JMeter scripts, and more — saving 3-4 hours daily with no coding required.

In-depth hands-on review of Anthropic's Claude Code terminal coding tool, demonstrating its complete workflow of code understanding, natural language development, auto test fixing, and Git commits through a Next.js project.

A complete 3-month learning roadmap for switching to AI software testing from scratch, covering fundamentals, Python automation, AI-powered testing, and career guidance.

A comprehensive comparison of Cursor, Windsurf, and Trae across five dimensions including coding, Agent autonomy, and pricing, with detailed scores and recommendations.

A detailed guide to AI-driven automated testing: from Python basics to PyTest, covering API automation, Playwright UI testing, and AI-assisted coding for beginners.

Complete guide to getting started with OpenAI Codex, covering ChatGPT account setup, client installation and login, and sandbox environment configuration.
TutorialsA deep dive into engineering Claude Code for API test automation, covering environment setup, Skill development, tool encapsulation, and Harness Engineering methodology.
TutorialsExplore the semi-AI approach to API automation testing: why pure AI fails, framework design principles, technology choices, and clear human-AI division of labor for practical implementation.
Industry InsightsIn-depth analysis of front-end, back-end, operations, and other IT roles, with insights into software testing career paths and specializations for IT professionals considering a transition.