Will AI "conjure" the end of Open Source in Healthcare IT?

We all see the impressive demos: AI generating code, spinning up web apps, and automating workflows in seconds. It begs the question—do we even need Open Source communities anymore if we can just prompt an AI to build what we need? When it comes to Healthcare IT, my answer is a definitive yes. Working with systems like RIS and PACS, and dealing with legacy integration, you quickly realize that code is only 20% of the job. The other 80% is clinical context, data privacy, and navigating strict standards like DICOM and HL7. AI can write a script, but it can't magically conjure the years of trial-and-error, clinical wisdom, and security testing that the Open Source community has built into its core frameworks. A hallucination in a standard app is a bug; a hallucination in a healthcare system is a patient safety risk. Moving forward, I see a powerful synergy: Open Source providing the secure, auditable foundation, and AI acting as the agile assistant to help us map data, build dashboards, and integrate systems faster than ever. How are you balancing the speed of AI with the need for reliable, peer-reviewed foundations in your projects? Let’s discuss! 🏥💻 #HealthTech #AI #OpenSource #MedicalImaging #SystemIntegration #FutureOfHealth