A regression strategy is the plan for ensuring that new changes each sprint don't break previously-working functionality. In Agile, where code changes constantly, this must be largely automated and risk-prioritized because manually re-testing everything every sprint is impossible.
Every sprint adds and changes code, and every change risks breaking something that already worked — that's regression. Manual full regression doesn't scale in Agile's cadence, so the strategy centers on an automated regression suite that runs continuously (ideally in CI on every merge). Because even automated suites have limits on time and maintenance, you prioritize by risk and change-impact: always cover critical business flows (login, checkout, payment), focus extra attention on areas touched this sprint and their dependencies, and use the test pyramid so most regression lives in fast unit/API tests with a lean set of E2E journeys. The suite needs active maintenance — flaky and obsolete tests must be fixed or removed, or the suite loses trust. A common trap is letting regression coverage lag behind feature development (automation debt), so that manual regression creeps back in and slows every sprint; QA must treat keeping the regression suite current as first-class sprint work, not an afterthought.
A team runs a fast automated regression suite in CI on every merge, covering critical flows plus areas changed each sprint. When a refactor accidentally breaks the checkout total calculation, the regression suite fails within minutes on the merge — long before it could reach a release — and the developer fixes it immediately.
Scenario: Your team's manual regression pass takes 3 days and runs at the end of every 2-week sprint, so a quarter of each sprint is consumed by it and regressions still occasionally slip through. Design a sustainable regression strategy.