The doctor shortage is not a knowledge problem. It is a capacity problem, and adding more bodies is not working, especially in rural America. Tod Stillson, a family physician who spent 30 years seeing 35 patients a day before building his own AI-supported urgent care, argues the fix is not replacing doctors but scaling one doctor's judgment to reach far more people. The catch: who governs the medicine inside the machine.

⏱️ Chapters:
0:00 Introduction
0:35 The real bottleneck is not knowledge, it is capacity
1:08 Why 35 patients a day is a hard ceiling
2:08 What a doctor in the loop actually means
3:18 The two years it took to codify 30 years of judgment
5:01 What AI triage feels like from the patient's phone
6:33 100 percent accurate vs the 50 percent GPT problem
7:16 The two questions patients ask at Walmart and church
8:42 Will frontier models get good enough to replace doctors
10:36 Why throwing more headcount at this fails
11:21 Who governs the medicine inside the machine
13:34 The billion-dollar startup with 13 employees and no guardrails
17:53 The shortage numbers that should scare rural America
18:49 Take home messages

About this episode:
Tod Stillson, a family physician, medical device inventor, and health care entrepreneur who ran a rural practice for 30 years before founding an on-demand cash-pay urgent care, returns to make the case that AI's real job in medicine is extending a physician's reach, not replacing the relationship. He frames the core problem precisely: medicine is not short on knowledge, it is short on how many times that knowledge can be applied in a day, and a doctor who tops out at 35 patients hits a hard ceiling. He describes spending nearly two years feeding 30 years of experience and national guidelines into software that triages symptoms into four buckets, and reports a 100 percent triage accuracy across 5,000 patients against a cited Nature study showing GPT triage landing near 50 percent. Pressed on whether frontier models will eventually match physicians, he concedes they will improve but holds that the human relationship is the doctor's space, with AI staying in triage and empowerment. He turns to governance as the real obstacle, arguing physicians, not technologists chasing a market, must own the knowledge base that drives these systems. As a cautionary case he points to a direct-to-consumer GLP-1 company profiled in the New York Times that scaled to roughly a billion dollars in revenue with around 13 employees and, in his view, too few guardrails. He closes on the shortage math, 124,000 physicians short by 2027 and 187,000 by 2037, and urges clinicians to stop fearing AI and start using it as a capacity multiplier.

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