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AI is rewriting the rules of healthcare software development, but building a secure scalable healthcare platform still comes down to fundamentals: clear requirements, strong ownership, and serious engineering discipline around HIPAA compliance and PHI protection. We sit down with Ghazenfer Mansoor, founder and CEO of TechnologyRivers, to talk through what’s working right now as digital health teams race from prototype to production.

We get practical about how AI fits into the real build process, including rapid POCs, code generation, and stronger testing through AI-assisted unit tests and code coverage. Then we dig into the part most teams learn the hard way: you can’t treat AI like a simple Google search when the data is sensitive and the scale is real. We talk about why “upload your company docs” breaks down, and how patterns like RAG architecture and vector databases can support safer internal search and analysis without losing control of private data.

We also cover the repeat mistakes that sink health tech MVPs, especially unclear requirements and fuzzy decision-making. From there, we talk UX and UI in healthcare, focusing on designing for patients, clinicians, and admins based on what they actually need to do. Finally, we look at low-code and no-code in healthcare, how to turn white-coded prototypes into production-ready HIPAA compliant software, and what interoperability and emerging ideas like MCP could mean for the next wave of EHR-connected apps.

Subscribe for more conversations on digital health, healthcare IT, and AI in clinical workflows, then share this with a builder on your team and leave a review. What’s the hardest part of shipping healthcare software in your world right now?

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