How I’m mapping enterprise AI risk
As part of an AI transformation effort, I’ve been mapping the enterprise AI market. For risk, three layers are becoming clear: AI governance, agent identity, and content trust.
How far can you get with open-source IoT platforms?
I’m testing open-source IoT platforms for a small IoT toy project. Here are three platforms I found interesting and where I’m starting.
Keeping coding agents running when you leave your desk
AI coding agents can work for hours, but local sessions still depend on the developer's machine. Here are practical ways to keep them running when you leave your desk.
Tacit knowledge is the missing dataset
Industrial AI has plenty of sensor data, but some of the most important context still lives in people's experience. The challenge is capturing that knowledge before it disappears.
A feature request is usually not the problem
Customers are often right about the pain they feel, but not necessarily about the best solution. Good product teams work backward from the request to the underlying problem.
Prediction Is Not the Product
AI predictions create value only when they lead to decisions, actions, and feedback. Predictive maintenance taught me that the real product is what happens next.
Physical AI Needs More Than AI
AI is advancing quickly, but robots still face constraints in actuation, energy, sensing, mechanics, and the physical world itself.
AI Is Getting Easier. The Physical World Isn't.
What I learned going from AI to industrial IoT and back to AI.