AI for Quality Engineers: SDET to AI QA Architect with Afzal

Traditional automated testing is hitting a ceiling. Brittle scripts, high maintenance overhead, and constant UI changes consume engineering hours that should be spent on strategic quality engineering.

This program bridges the gap between traditional QA automation and modern AI-driven quality engineering. You will learn how to design, build, and deploy intelligent testing systems—moving from basic test scripting to architecting autonomous QA agents and evaluating AI-native software.

What You Will Master

• Generative AI for Test Engineering:
  • Prompt engineering patterns for zero-shot and few-shot test case generation.
  • Automating boundary-value and edge-case discovery from requirements and user stories.
  • Generating complex, schema-compliant synthetic test datasets (JSON, SQL, mock APIs).
• Intelligent UI & Visual Automation:
  • Implementing self-healing test automation scripts that adapt dynamically to DOM changes.
  • Integrating visual AI engines to detect layout shifts and pixel regressions across viewports and mobile form factors.
• Agentic Testing & Autonomous Workflows:
  • Architecting goal-based autonomous testing agents that navigate user flows without hardcoded scripts.
  • Building event-driven testing loops triggered by CI/CD commits and pipeline events.
  • Optimizing regression runs using risk-based predictive test selection.
• Testing AI & LLM Systems (AI Eval):
  • Evaluating RAG pipelines, prompt reliability, and output hallucinations.
  • Industry-standard evaluation metrics, scoring frameworks, and safety guardrails.

Who This Is For

• Automation Engineers & SDETs looking to future-proof their skill sets and implement AI-first testing pipelines.
• QA Leads & Engineering Managers aiming to increase team velocity, reduce regression cycles, and cut locator maintenance.
• Manual QA Professionals with foundational scripting knowledge ready to jump directly into modern, agentic workflows.