Where clinical depth meets AI product thinking. Written by Yoram Friedman, MD, physician and enterprise product leader.
Two frontier AI models, an external reviewer, thirty-nine signed rulings, and not one of them ever said stop. I did not fire my agent team for being wrong. Every answer was right. I fired them because no answer ever included the sentence that mattered.
I am working with the best developer of my career. Zero latency, infinite patience, always says yes. It is also the most dangerous working relationship I have ever had. On what happens to product judgment when implementation becomes free, and where the discipline has to live now.
Ten runs of one boring question about fruit teach more about AI than any slide deck. Probabilistic is not a definition; it is something you watch happen to your own keyboard.
Physicians are building their own AI tools, and patient data cannot leave the building. So which local model deserves to be in the room with a chart? Not the biggest one. I measured.
A PM who has never watched an agent work cannot write its spec, its evals, its boundaries, or its intent. The pod model assumes PM, UX, and engineering share an understanding of the product's behavior. For agentic products, only one of the three has it.
Data products were built on a quiet assumption: the designer could anticipate the questions. Agents break that assumption without breaking the discipline. What survives is not the shape we prepared but the honesty of the contract underneath it. Five questions for every data product owner.
Healthcare asks who is accountable for a machine's mistake before it asks what the machine can do, because it has no choice. On 18 August a federal regulator applied that question to generative AI. The framework it produced is not new. It is clinical governance, written down for everyone else.
The word "prompt" was not invented for AI. It was on the screen in 1993, the C colon and the blinking line, waiting for you to learn the machine's language. We are teaching doctors DOS again. The interface will absorb the commands, the way it always does. What it cannot absorb is judgment.
People keep asking how I found time to write four books in a year while doing my day job. The answer is not a tool and not discipline. It is a layered setup where every piece of work is tagged, linked, and ready for the next one. The tools are rented. The brain underneath is the asset.
The operator did not vanish when the agent arrived. She split. What she knew became the agent's context and bounds. What she checked before committing became the supervisory surface. The only casualty was the dashboard, and most agents are being built to generate it.
A new paper rebuilds the DIKW pyramid for medicine and shows where AI actually breaks. Strong on the arrows nobody worried about, weak on the one the structure depends on. The pyramid always assumed you could tell which layer you were standing on. That assumption is gone.
A Cybercab was filmed with no steering wheel. Removing it was the honest part. The rungs below it, hands on the wheel, eyes on the road, ready to take over, were never supervision. They were accountability. Most enterprise AI is still on rung three.