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Panel Discussion: Mission-Critical Priorities in Quality Engineering: The Leader's Playbook

on YouTube 49m
Panelat TestMu Conference 2026 · 2026-08-19..08-21· [engineering-leadership, testing]

speakers

name:Ali Karnib
links:none on file
name:Hina Saini
links:none on file
name:Akshit Lomash
links:none on file
name:Cem Sever
links:none on file
name:Kumar Gaurav Jain
links:none on file
name:Tenny Agustin
links:none on file

resources

video:https://youtu.be/j10F1MDTxKY
slides:none on file

summary

Bets focus on turning test automation into AI-powered test infrastructure, rebuilding frameworks toward serverless, event-driven pipelines, and democratizing testing so SDEs author and run checks. AI already pays off for test-case/script generation and maintenance, while a consolidation effort around processes (not tools) reduces friction. Executives respond to defect escape and incident-rate trends, not test counts. Correlating production usage with 400,000 config combinations surfaces surprising high-risk targets, observability is still the biggest gap, and teams keep overnight full runs for safety.

AI-written summary · about

chapters (33)

  1. 0:00Mission-Critical Priorities in Quality Engineering: The Leader's Playbook
  2. 1:07The Format: Bet, Sacrifice, Prove, Predict
  3. 7:20What Legacy Practice Did You Deliberately Deprioritise?
  4. 7:54Not Deprioritised - Replaced, and Why the Distinction Matters
  5. 9:26Smaller Cycles, Targeted Risk-Based Testing, Overnight Full Runs
  6. 10:28Exploratory Manual Testing Coming Back - "Go Try to Break This"
  7. 10:58Tool Sprawl: Is Consolidation Actually the Goal?
  8. 11:28Consolidate Processes and Practices, Not Tools
  9. 13:31Tool Consolidation as a Secondary Benefit of Honing Process
  10. 16:04How Do You Stop This Becoming the Wild West?
  11. 18:08Why Agentic Abstraction Changed His Mind on Forced Consolidation
  12. 19:09Guidelines From Security and AI Lab Teams as the Guardrails
  13. 21:10Which ROI Metrics Actually Land With Executives?
  14. 21:40Defect Escape and Incident Rate Over Test Counts
  15. 22:10The Customer Doesn't Care How Many Tests You Ran
  16. 23:40Escape Defect Ratio, Severity Trends and Blast Radius
  17. 24:40What Does True Readiness Look Like Before a Release?
  18. 28:13What They Actually Looked At in the Last Go/No-Go
  19. 29:45Three Levels: Technical, Operational, Organisational
  20. 30:47Can the Platform Handle the Demand? Can the Customer Finish the Journey?
  21. 31:48Did We Test It, Do We Have Evidence, Do We Have a Plan B?
  22. 32:50Which AI Bet Has Already Paid for Itself?
  23. 33:20What Worked, What Fizzled, What Looks Promising
  24. 34:20Correlating Production Usage With 400,000 Config Combinations
  25. 35:21Where AI Is Clearly Helping - and Where It's Still Wait and Watch
  26. 37:25Testing AI Services vs AI Services for Testing
  27. 39:04Q&A: What Happens When Two Agents Disagree?
  28. 40:38Q&A: Ensuring Speed Doesn't Come at the Expense of Trust
  29. 42:08Observability as the Gap: How Fast Can You Reach Root Cause?
  30. 43:09Bold Predictions for Quality Engineering by End of 2027
  31. 45:11Roles Will Evolve; QE Will Own the Trust Framework
  32. 46:14Productivity Will Improve Massively - Become the Domain Expert
  33. 46:46Quality Engineering Will Become Risk Engineering

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