My approach is pragmatic: prioritize by business impact and likelihood of failure. First I ask for usage data, SLAs, critical user journeys, acceptance criteria, known technical debt, and rollback plan. With that I map features to risk buckets: critical (payments, auth, checkout), important (major flows used by >20% of users), and low (rare or cosmetic). I allocate test effort to critical flows: automated smoke and API tests first, manual exploratory for unclear behavior, and full regression only for impacted modules. With a 2-person QA team and a 5-day testing window I aim to automate smoke coverage to 90% and cover critical flows end-to-end manually. Trade-offs include deferring low-use features, reducing UI automation scope, and using canary releases to lower user risk.
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