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6.4Key Takeaways
- Allocate testing effort based on risk (business impact x failure likelihood), not code coverage targets
- Use failure history, code complexity, and business impact mapping as inputs to your test strategy
- Score automation candidates across business, usage, churn, and risk dimensions — automate what is most expensive to get wrong, not what is easiest
- Treat production behavior as a first-class risk signal: sessionize logs, mine flows and friction, and let the LLM interpret summaries — never raw logs
- Close the loop — consume operational intelligence from Product, Support, SRE, and engineering through a weekly Quality Review; QA need not own monitoring to use it
- Replace vanity metrics (automation %, test count) with outcome metrics (escaped defects, MTTR, change failure rate)
- Signal-to-noise ratio is the health metric of your test suite — if most failures are flakiness, not bugs, the suite is sick
- The risk matrix is a living document — update it quarterly as the product and risk landscape evolve