Vibe-Code Audit: From Local MVP to Production-Ready AI Solution

Challenge

In addition to determining whether a rapidly vibe-coded MVP could meet the engineering standards required for a healthcare production environment, our team faced the following challenges:

• We needed to ensure the application met strict security and quality standards before production deployment. Because it processes sensitive health information, even an overlooked code flaw could expose protected health information (PHI), putting patient privacy and regulatory compliance at risk.
• The AI image-processing workflow initially ran in a single thread, limiting how many documents the system could handle at once and creating a bottleneck as processing demands increased.

Checking Dependencies and Security Risks

Due to the highly sensitive and regulated healthcare sector, one of the most critical parts of our vibe code audit was security and dependency checks. Our team reviewed external libraries and their versions, and identified several implementation issues that could affect data security. One of them was PHI appearing in application logs, which could expose sensitive patient information and create serious privacy and regulatory compliance risks. We addressed this exposure so that patient information would not be unnecessarily written to logs and become accessible through operational tooling. We also identified an outdated version of AutoMapper and addressed the dependency as part of the production hardening process.

Strengthening Validation and Reliability

Our team also improved validation for incoming files, fixed miscellaneous field-mapping issues, and investigated unreliable SignalR live updates. Additionally, we conducted comprehensive testing of the configurable AI hints to validate features across different scenarios. These activities made the application more predictable when handling real-world documents and communicating processing results back to users.