A comprehensive training program on implementing Git-based test management. Equip your team with the knowledge to migrate from traditional test management tools to a Git-native approach, leveraging markdown artifacts, version control workflows, and AI-assisted test generation.
GTM starter repository template
10 hands-on exercises
Private community access
Certificate of completion
A comprehensive training program on implementing Git-based test management using the GTM (Git Test Management) system. This course equips QA engineers and test leads with the knowledge to migrate from traditional test management tools to a Git-native approach, leveraging markdown artifacts, version control workflows, and AI-assisted test organisation.
Whether you’re looking to eliminate expensive SaaS licensing fees, gain true version control over your test artifacts, or prepare your test documentation for AI-assisted generation, this course provides the methodology and hands-on practice you need.
Most test management training teaches you how to click through legacy web tool interfaces. This course teaches you a methodology that works with any Git platform, costs nothing to operate, and positions your test artifacts for AI-assisted generation and maintenance.
You'll learn patterns used by teams who've eliminated five-figure annual licensing fees while gaining capabilities their previous tools couldn't match. Capabilities that include true version control, AI test generation, and tests that live alongside the code they verify.
GTM Training Syllabus
A syllabus designed to take you from understanding why Git-native test management matters to implementing advanced team workflows and CI/CD integration
Why traditional test management tools fall short and how Git solves these problems.
Understanding the data model that powers effective test management.
Organizing test artifacts for scalability and maintainability.
Creating and managing test cases that are both human-readable and AI-ready.
Recording test activities with full auditability.
Scaling GTM for enterprise teams and CI/CD integration.
Leveraging AI tools to accelerate test case creation from multiple source types.
Using AI agents to maintain test case quality and catch gaps at scale.
Project 1: Test Repository Setup
Project 2: Execution Workflow
No programming is required for Modules 1-6. The course focuses on markdown files and Git commands, not code. Modules 7-8 involve AI tool configuration but no coding—just prompt engineering and tool setup.
You should be comfortable with clone, commit, push, pull, and basic branching. We'll cover advanced Git workflows in Module 6, but foundational knowledge is expected.
Yes. Many teams run GTM in parallel during migration. You can export from tools like TestRail and gradually transition test cases to GTM format using the migration patterns covered in the course.
GTM works with any Git platform like GitHub, GitLab, Bitbucket, Azure DevOps, or self-hosted Git servers. The methodology is platform-agnostic.
Both. GTM manages test case documentation regardless of execution method. Module 6 covers patterns for linking GTM artifacts to automated test results from frameworks like Playwright or Cypress.
Yes. You'll have permanent access to the GTM starter repository, all templates, and the private community for ongoing support and updates.
Module 7 covers Claude with MCP (Model Context Protocol) for Jira integration, Docling for document processing, and screen recording for test flow capture. Module 8 covers building custom review agents and ElevenLabs for voice-based test case review sessions.
The labs can be completed with free tiers of most tools. We'll discuss which features require paid plans and provide alternatives where possible.
Ready to eliminate test management tool fees and supercharge your workflow with AI? Join the growing community of QA professionals who've made the switch to Git-native test management. Enroll now and build a test management system that scales with your team, integrates with your AI tools, and costs nothing to operate.
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