No Priors Ep. 130 | With OpenEvidence Founder Daniel Nadler

How does a new technology get adopted by 40% of American doctors in just 18 months? In an era where the golden age of biotechnology has also created a dark age of physician burnout, OpenEvidence found the answer by fundamentally changing how doctors access critical information. OpenEvidence founder Daniel Nadler sits down with Sarah Guo and Elad Gil to discuss how his company solved the semantic search problem in medicine. He talks about the strategy of treating doctors as consumers, striking the balance of keeping patients in the loop in medical conversations, and how technology will reshape both medicine and medical education. Plus, Daniel gives his thoughts on the roots of motivation, as well as his philosophy for recruitment. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EvidenceOpen Chapters: 00:00 – Daniel Nadler Introduction 00:08 – OpenEvidence’s Success 01:54 – How OpenEvidence Works 06:35 – Dealing with Ambiguity 11:37 – Treating Knowledge Workers as Consumers 15:53 – Balancing Keeping Patients in the Loop 19:28 – How Technology May Shape the Future of Medicine 22:12 – How Technology Will Change Medical Education 30:40 – Examining Consumer Adoption of Preventative Health Measures 36:02 – Lessons for Other Fields 37:27 – Rationalism vs. Will 41:13 – Daniel’s Thoughts on Motivation 42:44 – Daniel’s Recruiting Philosophy 44:48 – Conclusion

Sarah GuohostDaniel NadlerguestElad Gilhost

Sep 4, 202544mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

AI-Powered OpenEvidence Becomes Doctors’ Operating System For Clinical Decisions

Daniel Nadler explains how OpenEvidence rapidly became the dominant clinical decision support tool for U.S. physicians by treating doctors as consumer internet users and focusing narrowly on high‑stakes medical decisions. The product semantically interprets complex patient scenarios and routes doctors to precise snippets in top-tier medical literature rather than providing opaque “answers.” Nadler discusses the explosion of biomedical knowledge, why medical education must invert toward continuous learning, and how AI can act as a “curbside consult” to extend specialist-level care into under-resourced areas. He also reflects on patient access to information, cultural determinants of health, and the psychology and motivation behind building impact-driven AI products for knowledge workers.

IDEAS WORTH REMEMBERING

5 ideas

Narrowly target the highest-stakes, hardest problems where AI adds clear value.

OpenEvidence focuses on high-stakes clinical decision support—where a single wrong choice can seriously harm patients—rather than lower-stakes tasks like paperwork or scribing, making its value proposition obvious and adoption urgent.

Design AI tools as semantic routers to trusted sources, not opaque oracles.

By deeply understanding complex clinical queries and surfacing specific snippets from Phase III trials and guidelines—with citations as first-class citizens—OpenEvidence positions itself as a search engine that can be audited, not an answer engine demanding blind trust.

Treat expert knowledge workers as consumers with direct, bottoms-up access.

Letting doctors simply download a free app and adopt it individually, instead of selling only through hospital administrators, broke a long-standing gatekeeper model and led to consumer-style viral growth among physicians.

Build for a world where domain knowledge doubles faster than humans can absorb it.

With top-tier medical literature doubling roughly every five years (or faster by some measures), traditional “front-loaded” medical school is obsolete; products must assume continuous education and help clinicians keep up without dedicating hours a day to reading.

Scope your users to match the epistemic risk: start with professionals, not laypeople.

Limiting OpenEvidence to physicians allows the system to surface ambiguous or conflicting evidence safely, relying on trained MDs to interpret nuance, while serving patients indirectly via doctor-generated handouts and explanations.

WORDS WORTH SAVING

5 quotes

In about 18 months, it's become the operating system for clinical knowledge in the United States.

— Daniel Nadler

The golden age of biotechnology is the dark ages of physician burnout because it's just impossible to keep up with all the new drugs.

— Daniel Nadler

They know that they're not gonna get an answer from OpenEvidence. They're going to get a routing to a source that answers the question.

— Daniel Nadler

We did something that had never been done before ever, which is we treated [doctors] as consumers and as people that could go onto the app store and download a free app and start using it.

— Daniel Nadler

There is only a moderate correlation between freakishly smart and output… you have to find people that have some propulsion system.

— Daniel Nadler

OpenEvidence’s role as high-stakes clinical decision support for physiciansSemantic search over biomedical literature and evidence routing vs. answer generationExplosion and half-life of medical knowledge and implications for medical educationPhysician vs. patient access, ambiguity in evidence, and patient handoutsTreating doctors as consumer users and bypassing traditional healthcare gatekeepersAI as a distributed curbside consult and equity in under-resourced healthcare settingsFounder psychology, motivation, and recruiting highly driven knowledge workers

High quality AI-generated summary created from speaker-labeled transcript.

Get more out of YouTube videos.

High quality summaries for YouTube videos. Accurate transcripts to search & find moments. Powered by ChatGPT & Claude AI.