Not Every Problem Deserves an Agent
Most agentic AI failures happen before a line of code is written. The use case was wrong. The cost model was missing. Two frameworks most teams skip, and pay for later.
Product Management
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Prompt Engineering Is a Temporary Skill
A developer, an accountant, a graphic designer, a film director, a composer, and a product manager all use the exact same interface to communicate with AI: a text box. That has never been true of mature technology. It will not stay true for this one.
What You Owe the People Who Will Never Be in the Room
The people most affected by your AI product are almost never in the room when you build it. They don't appear in your analytics. They weren't in the meeting when the roadmap was approved. They will never give you feedback. You owe them something anyway
There Is No Certification for This
AI compresses knowledge. It does not compress experience. The junior PM in your next interview has access to the same tools you do. What separates you now is judgment. There is no course for that. There never was.
Stop Looking for Unicorns
Healthcare AI job postings keep asking for unicorns: 14 years of experience in a field that is three years old, deep AI expertise, deep clinical expertise, deep product expertise. That person does not exist. And even if they did, they would not fix the real problem.
The Context Is the Product
In healthcare, AI can already predict. The hard problem is reasoning, and reasoning depends entirely on context. The physician who takes a complete history, examines carefully, and aggregates everything from the EHR to the nursing home fax is not being thorough. They are building the product.
AI Is Not a Product
People don't buy a drill. They buy a hole. AI is the drill. Every major technology wave produces the same confusion. SQL became infrastructure. Java became infrastructure. Cloud became a checkbox. AI is doing the same thing. We are in the expensive middle of that arc right now.
What Do We Do With the Frameworks?
Twenty years of customer interviews, workshops, and journey maps. Then agentic AI arrived, and every framework I trusted turned out to share one assumption I had stopped noticing: that the human is always smarter than the tool. Here's what breaks when that stops being true.
You're Not a Bridge Anymore: How AI Is Redefining Product Management
For 20 years, I translated between customers and engineers. Now I architect decision systems with AI. But here's the catch: you're designing for two customers: humans and their AI agents. Design for one, forget the other, and it fails.
The House of Cards: Why MVP Thinking Is Breaking Healthtech
MVP was meant to test ideas, not become architecture. Now, we’ve started stacking prototypes into production systems nobody designed as systems. When one layer fails, the whole structure drifts silently. In medicine, that’s not technical debt. It’s patient risk.
Creating Your Own Voice: How to Introduce Yourself to Claude (and Why You Need To)
My first AI-assisted article was polished, accurate, and completely unrecognizable as mine. The problem wasn’t the model. It was that I never taught it how I think. If you want AI to sound like you, you have to externalize your reasoning first.
The Architect Who Should Have Read JAMA
In healthcare AI, policy shifts now appear first in journals like JAMA and NEJM, then quietly become grant conditions and RFP requirements. Many tech teams miss this signal. The winners will be those who translate medical literature into architecture before it becomes mandatory.