Launching an AI MVP requires more checks than traditional software. This checklist covers technical, product, security, and business items you need to verify before going live.
Step 1: Technical Infrastructure. Verify deployment pipeline works end-to-end. Confirm database backups are running. Test auto-scaling under load. Verify SSL certificates. Confirm monitoring and alerting is active. Test rollback procedures.
Step 2: AI Model Readiness. Test model outputs against edge cases. Verify prompt engineering handles unexpected inputs gracefully. Confirm fallback behavior when the AI model fails or times out. Test rate limiting and cost controls. Verify model output quality meets minimum standards.
Step 3: Security and Privacy. Verify data encryption at rest and in transit. Confirm access controls and authentication. Test for prompt injection vulnerabilities. Verify PII handling complies with regulations. Confirm audit logging is active.
Step 4: User Experience. Test all user flows end-to-end. Verify error messages are helpful and non-technical. Test on mobile devices and different browsers. Confirm loading states during AI processing. Verify response times are acceptable.
Step 5: Business Readiness. Set up analytics tracking for key metrics. Prepare support documentation and FAQ. Test payment processing if applicable. Prepare communication templates for user feedback. Set up user feedback collection mechanism.
Step 6: Post-Launch Plan. Define success metrics and targets for week 1. Schedule daily monitoring check-ins for the first week. Plan iteration cycle based on user feedback. Prepare scaling plan if demand exceeds expectations.
This checklist is based on launching 50+ AI MVPs at SpeedMVPs. Download the full 47-item checklist with detailed instructions for each item.
