Justin Fulcher Brings a Founder’s Eye to Federal AI Modernization

Not everyone who writes about AI in government has tried to build technology inside a regulated healthcare environment, then gone to work inside the Pentagon. Justin Fulcher has done both, and the combination gives his recent IT Security Guru piece a specificity that much of the commentary on government modernization lacks.

Fulcher co-founded RingMD, a telemedicine platform that operated across Asia. Healthcare technology, especially at scale and across multiple regulatory environments, demands the same kind of careful design thinking that government systems require: you cannot bolt new technology onto a broken process and expect good outcomes. Workarounds that work in a startup environment fail when the stakes are patient care or national security.

From RingMD to the Pentagon

That background informed Fulcher’s approach when he later served as a Senior Advisor to the Secretary of Defense, focusing on acquisition reform and technology modernization. Justin Fulcher contributed to initiatives that brought software procurement timelines down from years to months. The achievement reflects the principle he articulates in his writing: friction removal, not complexity addition, is what makes technology adoption succeed in environments with heavy compliance requirements.

His diagnosis of the underlying problem is direct. Government modernization is not blocked by a lack of funding or ambition. It is slowed by what he calls institutional drag, the accumulated weight of outdated processes, data silos, and analog-era compliance structures. “Our core systems operate as if it were 1975,” he has written, a phrase that captures both the scale of the problem and the size of the opportunity.

The Case for Discipline

Justin Fulcher argues that AI represents a genuine chance to upgrade institutional capacity without requiring agencies to tear themselves apart and rebuild. But he is clear about what makes that possible. Implementation discipline, realistic scoping, and a genuine willingness to iterate based on user feedback separate the AI programs that produce durable results from those that generate press releases and then disappear. Read this article for more information.

More about Justin Fulcher on https://x.com/JustinFulcher

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