Day 9 - Boosting Tester Productivity with Google NotebookLM

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Context:

As a tester, I often deal with large volumes of product and technical documentation. I explored Google NotebookLM to see how AI can simplify this process.

What I Learned:

  • Quickly understand documentation by asking natural language questions.
  • Generate overviews and study guides from dense material.
  • Summarize workflows and identify requirements to derive core and end-to-end test scenarios.
  • Brainstorm test ideas and edge cases using document context.
  • Share structured notes and insights with the team for better collaboration.

Why It Matters for QA / AI Testing:

  • Saves time by reducing manual effort in reading and interpreting documentation.
  • Improves test coverage by uncovering hidden requirements and edge cases.
  • Enhances collaboration through AI-generated summaries and structured insights.

My Takeaway:

AI isn’t just about writing code — tools like NotebookLM can supercharge a tester’s productivity and creativity.

https://notebooklm.google

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