AI Software Testing for Beginners: QA Career with No Coding

Learn to tame ai in qa by applying the Craft framework—context, role, action, format, and target audience—using defensive prompts, guardrails, and a three-step refinement loop for reliable, autonomous testing.

Engineer deterministic QA prompts for testers using costar and craft frameworks to generate structured, edge-case test cases in Gherkin, reducing AI hallucinations and delivering production-ready tests.

Understand large language models (LLMs) and AI agents in software testing, including prompts, tokens, and context windows, and learn a divide-and-conquer approach for crafting tests.

Discover why you should never blindly trust ai, as hallucinations can mislead tests; maintain human in the loop and harness strong prompts and ai agents.

Set up four free tools, plan tests with AI, and run your AI augmented test using Playwright and VS Code on a demo e-commerce app to validate login and checkout.

Learn how to troubleshoot setup errors with AI assistance, install tools like node.js across Windows, Mac, and Linux, and use cloud queries to resolve issues, boosting software testing productivity.

Learn how to turn plain English requirements into AI-driven automated tests with AI agents for self-healing and rapid execution, even with no coding background, to build in-demand automation testing skills.

Explore how AI agents drive the browser to generate many tests, enable self-healing of flaky tests, and publish reports using cloud code, Copilot, and Playwright MCP.

Apply the 30-40-30 rule to automate tests with playwright code gen, blending automated scripts and 30% manual editing, while mitigating token use with MCP server setup and cloud code.

Set up a VS Code project by creating a local folder, opening it in VS Code, and installing the cloud code extension to connect a paid account.

Set up a new Microsoft Playwright project in VS Code using cloud code, connect your paid account, choose a language, enable GitHub actions, and install the mcp server.

Set up and configure your VS Code project folder with an mcp server, access cloud code via terminal, and create a QA automation agent using Playwright and mcp tools.

Set up a VS Code folder for AI software testing by creating skills.md files, configuring agents, and building a page object model with MCP Playwright for login and signup automation.

Create login and sign-up test scripts with an AI agent, guiding end-to-end web automation from login to account deletion using Playwright and VS Code.

Explore how an orchestrator agent acts as a virtual team lead to delegate tasks to specialized playwright qa automation, business analyst, and designer agents, enabling multi-agent coordinated testing.

Learn how worker agents generate and validate playwright tests from clear requirements, acceptance criteria, and edge cases, guided by an orchestrator and specialized QA agents.

Coordinate a multi-agent Playwright workflow end to end, with specialist agents handling requirements, code, tests, and deployment, all managed by an orchestrator for automated task delegation and traceability.

Create custom subagents in Claude code to orchestrate playwright tests and delegate tasks via an orchestrator in a multi-agent system with cloud code and cloud.md context.

Build a multi-agent system with an orchestrator and subagents—business analyst, code reviewer, and front-end developer—to design, implement, and QA a landing page using Claude code.

Discover how agile principles drive adaptive planning and continuous improvement, compare Scrum sprints with Kanban, and learn how to use agile boards with columns like to-do, in progress, and done.

Explains core Jira terms for agile software testing, including stories, epics, issues, and projects, and shows how to structure and customize them in kanban and scrum contexts.

Compare team-managed and company-managed projects in Jira, detailing scope, permissions, and how issue types stay within each project. Explore templates and Kanban boards plus licensing impacts on access.

Explore the Jira interface, including your work, dashboards, filters, and issues, with emphasis on recent and starred items. Navigate with the app switcher, create issues, and manage permissions and notifications.

Learn to create issues in Jira for team-managed projects using the create window and keyboard shortcut C. Customize fields, add custom issue types, and assign or filter issues on boards.

Discover how to set up and use rovo, the Jira AI tool, to filter bugs, create dashboards and charts, generate JQL queries, and track open issues for better team compliance.

Master smoke testing and sanity testing to catch defects early, using shallow and wide checks for new builds and deep, narrow verification for fixes.

Discover regression testing as re-executing tests to ensure stability after changes. Build a strategy that combines automated, risk-based testing with visual regression to catch UI issues before production.