Smoke testing in production refers to the practice of running tests on actual data from real users in a production environment, extending other testing methods like unit and integration testing. This approach allows for quick assessment of an application's status by running end-to-end tests targeting significant user flows, which are collections of basic and main functionality in the system. Smoke testing is typically run after new deployments and at regular intervals, consisting of many small and quick-to-execute testing blocks to identify production issues as fast as possible. Implementing smoke testing in production involves automating critical flows using tools like Cypress, creating a CI platform such as CircleCI, scheduling pipelines, and monitoring results with services like AWS CloudWatch. By following best practices, such as avoiding data pollution, flakiness, and false positive alarms, developers can ensure that their application behaves as expected in the production environment.