Are AI agents actually changing workflows, or are they just better AI tools?
One observation we've made while working on AI-enabled systems is that the conversation is gradually shifting away from individual AI capabilities.
The harder problem isn't getting AI to complete a task. It's enabling AI to coordinate multiple tasks, maintain context, and work across connected systems.
That's where AI agents become interesting.
We put together an article using MedTech as the context, exploring how AI agents differ from traditional AI tools, where they fit today, and what challenges still need to be addressed.
We're curious how others in the community define an AI agent versus an AI-powered application.
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The distinction that matters less is “tool vs agent” and more “does it actually close the loop.” Most AI systems still stop at generation. Agents only become meaningfully different when they can observe outcomes and adjust across systems, not just complete chained steps. In practice, that feedback loop is where most implementations quietly break down.