Nail down your initial QA goal: Define a clear, measurable goal for your quality assurance initiative, such as eliminating high-priority bugs reported by customers within a specific time frame. This will help you stay focused and motivated throughout the process.
Use a CI/CD pipeline: Implement a CI/CD pipeline to automate quality checks at defined points in the development process, delivering code frequently and quickly. This will help you catch issues early and prevent them from becoming more significant problems down the line.
Use AI: Have engineers use AI (e.g. Stably AI) to create & maintain the tests and use a third party platform like Stably to execute the tests. This will leverage AI assistance for generating and managing tests while utilizing an external testing service, making the most of limited resources without dedicated QA hires.
Configure your QA environment: Create a production-like QA environment, investing enough to achieve a good balance between fidelity and cost. This will help you identify and address issues that might not be caught in a less realistic environment. Seed test data to create states that facilitate fast and efficient testing. This will help you test a wide range of scenarios without having to start from scratch each time.
Don't test too much: Focus on three types of tests for sufficient test coverage: unit tests, end-to-end tests, and exploratory tests. Avoid overtesting, as it can be costly and time-consuming. Instead, focus on the most critical areas of the product and the most likely scenarios that users will encounter.
