Innovation and maintenance require fundamentally different capabilities.
MIT research: 95% of enterprise AI projects show zero P&L impact.
A pre-deployment audit for enterprise teams building agentic AI. Eleven checks, a scoring system, and the pattern connecting advisory AI failures to agentic ones.
"This is the first framework that addresses what happens when the AI is right but the physician still won't trust it."
"The override architecture section alone is worth sharing with our entire product team."
// By a VP of Product, Enterprise Healthcare Platform
View in StoryInnovation and maintenance require fundamentally different capabilities. Most companies pretend they don't.
MIT research: 95% of enterprise AI projects show zero P&L impact.
Three design paradigms for agentic systems: orchestration, collaborative decision, and adaptive complexity.
Why consumer UX principles fail in healthcare IT and fintech.
What is first before you build anything.
56% of CTOs getting nothing from AI in enterprise AI.
Six editions exploring why enterprise AI interfaces fail in production. Specific patterns from healthcare IT, fintech, and enterprise SaaS.
Why giving clinicians an override button doesn't solve AI trust.
What 'show your work' actually means in enterprise AI.
43% faster discovery. 60% fewer late-stage revisions.
89% adoption rate. Not from better AI.
Why consumer UX principles fail where mistakes have real consequences.
An interface redesign increased physician adoption from 11% to 68% without changing the underlying AI model
Healthcare AI · Clinical Decision Support · 4 months
Signal · Thirty Two North · Graphic by Bhagyashri, Apr '26
New editions every few weeks. One pattern. One finding. No fluff. Just what we're seeing across 200+ products.
New series · Late April 2026 · One pattern per edition