QA & Test Engineering AI Journey
A 12-week learning journey to transform testing and quality assurance using AI tools. Six sprints from context engineering to capstone.
Context Engineering
Write CLAUDE.md files that describe test architecture, coverage maps, and testing conventions so AI generates relevant test cases.
Weeks 1-2
Workflow Automation
Generate complete test suites with AI: edge case detection, test data generation, and automating test boilerplate.
Weeks 3-4
Agentic Patterns
Build agentic testing workflows where AI runs tests, analyzes failures, proposes fixes, and re-runs until green.
Weeks 5-6
Integration & Systems
Integrate AI into CI/CD: auto-generate tests on PRs, AI-powered quality gates, visual regression testing.
Weeks 7-8
Advanced Application
Tackle legacy codebases with no coverage, cross-service integration testing, and AI-assisted performance testing.
Weeks 9-10
Capstone & Transfer
Build a reusable testing tool, test generation template, or CI/CD configuration for other QA engineers.
Weeks 11-12