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What Actually Makes an AI System 'Agentic' Anyway? | Satvik Tripathi | Nagels Consulting Analytics Table

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Everyone at RSNA claims to have an "agentic" AI system these days. Satvik Tripathi says most of them don't actually know what that word means, and he'd know: he co-authored the editorial in Radiology that tried to pin the definition down. In this quick hit from Imaging Informatics Unplugged, Jason and Satvik cut through the noise around agentic AI in radiology, and get into why the term gets thrown around so loosely, what would actually have to be true for a system to earn it, and where the real bottleneck is before any of this becomes production ready in imaging. Satvik walks through the actual checklist for calling something agentic: it needs access to tools, it has to iterate on its own work, reflect on what it's doing, talk to other agents, and operate with some real autonomy. Miss those and you're looking at a chatbot with a fancy label, not an agent. He talks about hiding his badge at RSNA just to see how vendors answer when they think they're not talking to an expert, and honestly, the answers are not encouraging. The conversation gets into where agentic AI in radiology and radiation oncology genuinely has upside (there are a ton of loose endpoints across imaging workflows that could be synchronized), and where it's stuck: connectivity. The tooling, the MCP servers, the infrastructure to actually wire agents into existing radiology IT systems, isn't mature yet. Satvik expects that to shake out over the next two to three years. Jason pushes on a real concern for anyone running imaging informatics: once agents start negotiating with other agents, you lose visibility into why a decision got made. Satvik's answer is refreshingly practical: prompt it right, and the system should be logging every interaction, so you can trace back through the output and find exactly where it went sideways. If you want more from Satvik on this, he's running the Hip versus Hype session at SIIM digging into agentic AI specifically. Worth catching. If conversations like this one are useful for where you're headed with imaging AI and informatics more broadly, that's exactly the ground we cover at nagelsconsulting.com. The Imaging Informatics Primer course is a solid starting point if you're building foundational knowledge, the CIIP Foundations material will get you ready if certification is on your radar, and the hands-on DICOM Learning Lab is there if you want to actually get your hands dirty with the standard instead of just reading about it. Learn more at nagelsconsulting.com

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