How can automation help balance speed with depth?
How do you balance regression testing depth when a sprint demands quick releases?
How do you prioritize which test cases to automate first when release deadlines are tight?
What’s the hardest trade-off you’ve faced between technical debt and delivery speed?
What metrics actually prove you’ve balanced speed and thoroughness—beyond just sprint burndown?
How do ensure testing keeps pace with rapid sprint delivery?
In agile sprints, how do you stop testing from becoming the “compression zone” at the end?
What’s the biggest compromise you’ve had to make between code velocity and product stability?
What AI tools do you use for test case generation?
anyone know of good AIs that can create test cases based on SRS documentation?
How do you handle situations where product owners push for speed, but the testing signals risk?
How do you handle situations where business pushes for release speed but QA feels the product isn’t ready?
What’s your approach to prioritizing technical debt that slows testing versus delivering new features?
What testing practices help maintain coverage without slowing sprint velocity?
What role does risk-based testing play in balancing speed and depth?
In your view, what should not be automated even in a fast release cycle?
How do you balance the need for experimentation (A/B tests, beta features) with the responsibility of stability?