AI Testing Skills: The Evolution Beyond RAG and MCP
Learn what AI testing skills are and how they differ from RAG, MCP, and tool calling. A practical guide to building efficient AI testing agents with reusable playbooks.
Read articleLearn what AI testing skills are and how they differ from RAG, MCP, and tool calling. A practical guide to building efficient AI testing agents with reusable playbooks.
Read articleWhy AI coding is moving back to the terminal. A practical look at AI CLI agents and terminal-based AI coding assistants, multi-repo workflows, microservices, architecture-first thinking, and verification-driven development.
Read articleLearn AI faster with three paths: theory-first student, power-user workflows, and builder tooling. Understand LLM fundamentals, prompting, agents, and how to connect them.
Read articleDiscover agentic testing: how AI agents can test applications through white-box code analysis and black-box exploration using Playwright MCP, Chrome DevTools MCP, and terminal tools. Learn practical examples with Java Spring Boot and React, explore benefits and challenges, and see how coding agents are becoming testing agents.
Read articleLearn how to build Retrieval-Augmented Generation (RAG) with Gemini File Search.
Read articleLearn practical strategies to test and validate Large Language Model (LLM) systems. Discover how to ensure reliability, evaluate AI outputs, and maintain quality in real-world LLM-powered applications.
Read articleDiscover Test-Driven AI Development (TDAID) — a modern approach that merges Test-Driven Development (TDD) with AI-powered software engineering. Learn how to apply TDD principles to AI coding agents, build reliable feedback loops, and prevent regressions in non-deterministic systems. This guide explains why TDD is making a comeback in the AI era, how to structure agentic workflows around tests, and what practices help teams deliver high-quality, maintainable code with AI tools like Claude, Cursor, and Gemini.
Read articleA deep dive into Playwright Agents and the Model Context Protocol (MCP) — how Microsoft’s latest AI-powered Playwright release automates test planning, script generation, and self-healing browser tests across Chrome, Firefox, and WebKit.
Read articleHow DevTools MCP enables AI agents to record real performance traces (LCP/CLS/TBT), analyse them, and apply fixes—bringing Lighthouse-style audits into an iterative debugging session. Notes on INP (field) vs TBT (lab) included.
Read articleHow to use Mermaid diagrams to create human and AI-friendly architecture as code.
Read articlePlaywright Agentic Coding Tips for writing/generating API and UI tests.
Read articleA landscape of AI tooling for developers.
Read articleLearn how Playwright MCP combines AI agents, browser automation, and the Model Context Protocol (MCP) to enable intelligent testing, debugging, and documentation. Explore how it works, its architecture, and real-world use cases.
Read articleHow I use AI to code, learn, write and generate content.
Read articleReflections on "vibe coding", context windows, tips, and the real costs of AI-driven development, plus a live case-study building a websocket traffic monitor with Cursor and Sonnet agents.
Read articleA comprehensive guide to evaluating AI-powered IDEs based on live code suggestions, LLM chat integration, RAG performance, and agent capabilities for enhanced development workflows.
Read articlePersonal insights on effectively using AI tools for software development, highlighting practical tips for prompt engineering, understanding LLM limitations, and leveraging AI-powered coding assistants.
Read articleEssential tips for software testers using ChatGPT effectively, covering data privacy, bias awareness, prompt engineering, and decision-making strategies with AI assistance.
Read articleExplore how ChatGPT transforms test engineering with practical examples of test generation, CI configuration, tool comparison, and creative testing scenarios.
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