The podcast highlights the importance of risk-based testing, manual expertise, and the MEST framework in QA, while stressing the balance between automation and foundational skills. It emphasizes ethical testing practices, critiques AI overuse, and underscores global QA initiatives and collaborative strategies to enhance software quality.

How To Test This?

interview episodes where Mamadou N’diaye talks with with software testing experts

• https://podcasters.spotify.com/pod/show/spidey1944
• https://www.youtube.com/@HowToTestThis
• https://www.linkedin.com/in/mamadou-ndiaye-consultant/

Episode Details

• Show Notes: https://podcasters.spotify.com/pod/show/spidey1944/episodes/How-to-Test-with-METS---Greg-Paskal-e3llmnd
• Published: 2026-07-05T00:17:58Z
• Duration: 01:01:01
• Author: Mamadou N’diaye

Overview

The podcast delves into software testing, emphasizing risk assessment, strategic methodologies, and the evolving role of QA professionals. Greg Paschal, a seasoned QA expert, discusses common challenges in the industry, such as inconsistent training, over-reliance on automation without foundational manual testing skills, and a lack of strategic focus on risk reduction. He advocates for the MEST (Mission-critical, Essential, Technical, and System) framework as a prioritization tool for testing, highlighting the importance of structured planning and risk management. Paschal underscores the necessity of manual testing expertise as a prerequisite for effective automation, warning against over-automation and the misconception that it replaces human judgment. He also stresses the value of curiosity, continuous learning, and fostering collaborative cultures to advance QA practices.

The discussion extends to the ethical responsibilities of testers, including prioritizing data security, integrity, and advocating for customer safety. Paschal critiques the misuse of AI in testing, noting its limitations as a tool that replicates existing data rather than driving innovation. He emphasizes methodological rigor over tool selection, preferring Selenium for its reliability. The podcast also explores global QA initiatives, such as Paschals work in Rwanda training women and engineers in automation, highlighting the importance of empowering underserved communities through technical education. Additionally, he addresses the need for QA professionals to focus on risk identification, process improvement, and strategic collaboration, rather than procedural execution, to demonstrate their value in software development. Key themes include the balance between manual and automated testing, the importance of foundational skills, and the role of QA as a risk-driven, collaborative discipline.

What If

• What if you adopted the METS framework as your primary testing strategy for all projects?

  • Move: Implement the METS (Minimal Essential Testing Strategy) framework by categorizing test cases into critical, high, medium, and low priority groups. Use tools like Excel or a lightweight project management tool to track these categories and regularly refine them based on project feedback.
  • Why Now?: The software testing industry often lacks strategic prioritization, leading to inconsistent coverage and wasted resources. METS provides a structured, risk-based approach that aligns with Greg Paschals emphasis on methodology over tool reliance.
  • Expected Upside: Youll reduce testing overhead by focusing on high-risk areas first, improve team efficiency through clear prioritization, and align your testing efforts with real-world risk management principles.

• What if you prioritized manual testing skills before investing in automation?

  • Move: Dedicate 3 months to mastering manual testing fundamentalssuch as regression testing, exploratory testing, and defect identificationusing free resources like Craft of Testing videos. Track progress by creating a manual test plan for one of your current projects.
  • Why Now?: Greg explicitly warns against skipping manual testing, which is foundational for automation success. With AI and automation tools evolving, manual expertise ensures you can identify edge cases and risks that tools might miss.
  • Expected Upside: Youll build a stronger, more analytical foundation for automation, reduce costly errors from over-automation, and position yourself as a versatile QA professional in a competitive market.

• What if you created a simplified MIAI (Mission-Aware AI) framework for your AI tool interactions?

  • Move: Draft a 10-line markdown directive for your AI tools (e.g., ChatGPT, Copilot) that defines collaboration rules, expected outputs, and boundaries. Use it for tasks like generating test cases or documenting processes, revising it weekly based on outcomes.
  • Why Now?: The text highlights risks of over-reliance on AI without structured guidance. Gregs MIAI framework emphasizes alignment between human goals and AI outputs, which is critical as AI tools proliferate in software development.
  • Expected Upside: Youll reduce AI-generated inaccuracies, maintain control over tool usage, and improve the reliability of AI-assisted workflows, making your development process more efficient and error-resistant.

Takeaway

• Implement the MEST Framework for Prioritized Testing: Use the Minimal Essential Testing Strategy (MEST) to categorize tests into critical, high, medium, low based on risk and business impact. Start with a simplified test grid (e.g., e-commerce categories like login, checkout) using tools like Excel, and revisit/refine the framework iteratively to ensure alignment with project goals.

• Build Manual Testing Expertise Before Automation: Prioritize mastering manual testing skills (e.g., identifying patterns, risks, and edge cases) as the foundation for effective automation. Avoid jumping to automation without a deep understanding of core testing principles, as this can lead to flawed methodologies and inefficiency.

• Avoid Over-Automation and Focus on Regression Testing: Use automation strategically for regression testing in stable environments where consistent data trends can be tracked. Resist the urge to automate every test case; focus instead on accuracy, risk assessment, and critical paths. Maintain automation scripts daily to prevent staleness.

• Create a Collaborative QA Culture with Clear Terminology: Define shared terms (e.g., “defect” vs. “bug”) and avoid ambiguous phrases like “happy path.” Foster humility and curiosity among team members, and encourage open dialogue about risks, even if it challenges leadership. Promote cross-functional collaboration (e.g., Dev and QA) for aligned problem-solving.

• Leverage Structured Methodologies Over Trendy Tools: Prefer Selenium over newer tools like Playwright for reliability, and focus on methodology (e.g., MIAI framework for AI projects) rather than tool features. Document test cases with clear, step-by-step instructions to avoid ambiguity in automation, and emphasize risk-aware testing over mere pass/fail outcomes.