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A technical, plain-language guide to agentic development, AI agent teams, governance, framework choices, real workflows, and why companies are moving from assistants to governed agents.

A plain-language guide to MCP servers, Model Context Protocol, and how AI agents connect to tools like Figma, GitHub, DevTools, docs, databases, Jira, Drive, and local…

A practical GH-600 Agentic AI Study Platform with lessons, quizzes, labs, flashcards, scenarios, and an exam simulator for GitHub Copilot, MCP, guardrails, evaluation, and responsible AI.

AI agents should not be treated as magic workers that can freely read files, call tools, change code, query systems, create pull requests, send messages, or…

Keyboard and Focus Order is the evidence area for focusable element discovery, sequential tab-stop capture, deterministic focus findings, manual verification, and exportable focus evidence. A list…

The Dashboard is the reviewer’s starting point. It tells you what was scanned, what evidence exists, whether the current page state is fresh, and what should…

Manual Checks is the review queue for checks automation cannot safely classify, including tester instructions, expected observations, selectors, and evidence requirements. This section is where the…

Language Mismatch reviews declared page language, visible mixed-language evidence, inline language signals, and confidence-bound output. Language detection can get messy quickly, especially with short labels, names,…

Scan Results is the main triage surface. It turns automated WCAG findings, responsive comparison data, and issue evidence into something a reviewer can verify and hand…

Metadata Check reviews page title, H1/title relationship, canonical URL, social preview metadata, structured data, viewport metadata, and baseline document signals. Good metadata helps people understand where…