Product
9 articles in Product.
Healthcare AI Will Be Won by Verticals. The Recipe Has Been Around for a Decade.
Most healthcare AI companies are failing for the same reason. The ones winning are all running the same playbook — one that Palantir figured out long before anyone called it AI. Forward-deployed engineer. Ontology. Integrations. Then AI tooling, and only then.
Penpal: Dispatch Tool Today, RPG Interface Tomorrow
I built a tool that turns GitHub issues into pull requests using a three-agent pipeline. That's the boring part. The interesting part is what happens when you stop thinking about AI agents as productivity tools and start thinking about them as a workforce — and you build a world for them to live in.
Product Evals in Three Steps (That You'll Actually Do)
Most teams skip evals because the process feels overwhelming. Here is the three-step framework that makes eval-driven development achievable: label a small dataset, calibrate an LLM evaluator to human judgment, then iterate configs against the harness. No excuses left.
Stop Shipping Features: Why AI Products Need an Experiment Mindset
After shipping 12 features in a quarter and moving zero meaningful metrics, I learned the hard way that AI products are not software projects. The roadmap is a hypothesis board, not a delivery schedule.
When English Became a Programming Language
v0 just proved that English plus AI can replace traditional web development for most apps. I've spent 12 years mastering this craft. Here's my honest take on what that means.
The GenAI Strategy Question You're Not Asking (But Should Be)
Everyone asks 'how should we use GenAI?' The honest answer requires a harder question first: does AI's unique capability actually create new value here, or is it just a more expensive way to do something that already worked? A practitioner's framework for getting this right — especially in healthcare.
Every Failed AI Product Has the Same Root Cause
After 12 years in ML and AI, I keep seeing the same failure pattern: teams that ship fast and iterate on vibes instead of building systematic evaluation systems. Evals are not a nice-to-have — they are the core competency of any serious AI product team.
The 6 Ways I've Watched GenAI Projects Fail (And How to Avoid Them)
After 12 years in ML and two years watching GenAI projects go sideways in healthcare — sometimes with real patient consequences — here are the six failure modes I see over and over again, and what to do instead.
The Food Truck Method: Building MVPs That Don't Suck
After building dozens of MVPs, I finally figured out why most turn into dumpster fires. Here's my framework for building fast without the regret.