Based on the principle that the Definition of Done (DoD) ensures transparency, quality, and shared understanding of what “done” means, here are tailored DoDs for different product types.

Definition of Done for a Website

• Has the design/approach been discussed and reviewed by one other person?
• Does the code comply with the defined coding conventions?
• Does the database code comply with the defined DB development standards?
• Has the code been tested on all supported browsers?
• Does the code comply with the defined Security Guidelines?
• Has the test cases been written for 100% code coverage for code added/updated?
• Has the code been reviewed by any other member of the team?
• There are no high priority/severity bug
• Does it meet the acceptance criteria
• Has the code been integrated with the CI/CD pipeline and deployed multiple times on QA/UAT environment without any manual steps?

Definition of Done for a Mobile App

• UI/UX design validated against Figma/InVision prototype and approved by the Product Owner.
• App passes accessibility testing (WCAG 2.1 compliance).
• Code adheres to mobile coding standards and best practices.
• App tested on all supported devices and OS versions (Android + iOS).
• Integration with backend APIs tested thoroughly for error handling and edge cases.
• Automated test coverage meets or exceeds 80% for unit and UI tests.
• The app shows zero critical bugs and ≤ 2 medium-priority issues in the final QA report.
• The app complies with Apple App Store and Google Play Store guidelines.
• Release notes prepared and app metadata (screenshots, descriptions) reviewed.
• CI/CD pipeline successfully built and pushed to internal test platforms (TestFlight, Firebase) with no manual steps.

Definition of Done for an AI-Based Product

• Problem statement and hypothesis clearly defined and reviewed by stakeholders.
• Dataset curated, preprocessed, and approved with documented data sources.
• Model performance metrics (accuracy, precision, recall, etc.) meet defined thresholds.
• Bias and fairness analysis performed and documented.
• Model code reviewed and adheres to AI/ML coding standards.
• End-to-end pipeline tested (data ingestion → model training → prediction service).
• Unit tests written for data pipeline and model logic; integration tests in place.
• Model deployed to staging environment with monitoring and rollback in place.
• REST API (or interface) documented and validated for external integrations.
• Data and model versioning maintained (e.g., via DVC, MLflow), and reproducibility confirmed.

Definition of Done for an API-First SaaS Platform

• API design reviewed and approved using OpenAPI/Swagger standards.
• Authentication/authorization implemented per spec (OAuth2, JWT, etc.).
• All endpoints were tested for edge cases, error handling, and rate limiting.
• API test coverage is>90% with automated contract and performance tests.
• API documentation generated and published (Postman collection or API portal).
• CI/CD setup deploys new versions to dev/stage without manual steps.
• Monitoring (e.g., New Relic, Prometheus) enabled for performance and availability.
• Backward compatibility is verified for existing consumers.
• Security vulnerabilities are scanned using automated tools (e.g., OWASP ZAP, Snyk).
• Feedback loop enabled (usage logs, support requests, etc.) and reviewed for continuous improvement.

Definition of Done for an E-Learning Platform (Web + Mobile)

• Course content and quizzes uploaded and reviewed for accuracy and formatting.
• The platform is accessible via both web and mobile with responsive UI tested.
• User roles and permissions implemented and validated (student, instructor, admin).
• Payment and enrolment workflows were tested end-to-end.
• Video and document streaming optimized for various network conditions.
• Security checks passed (e.g., SQL injection, XSS, CSRF).
• LMS analytics integrated (course progress, completion rates).
• Platform performance tested under concurrent user load.
• Help/FAQ section completed with clear onboarding steps.
• Backup and recovery procedures were verified for all user data.

Each Definition of Done is product-contextual. What “done” means for an AI product is different from infrastructure setup. A great DoD promotes transparency, reduces rework, and ensures readiness for release.

It should be owned and evolved by the Scrum team—reviewed frequently, especially when quality issues or delivery gaps are spotted.

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