July 4, 2026
What a Failing Shrimp Farm Taught Me About AI Projects
For two years I spent over $1M fighting the wrong problem. The lesson from that shrimp farm is the one I bring to every AI project that isn't paying off.
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Practical, no-hype notes on using AI to move the numbers that matter.
July 4, 2026
Faster Horses: The Trap of Chasing the Newest AI Model
Henry Ford didn't build a faster horse. Chasing the newest AI model is the same trap — here's what to optimize instead.
Read →July 4, 2026
AI Doesn't Have a Tool Problem. It Has an Execution Problem.
Most failed AI isn't a technology gap — it's an execution gap. The lesson comes from an industry that had the better product and still lost.
Read →July 4, 2026
The $3 Fix: The Obvious Automation Nobody Builds
The best AI ROI is usually boring and obvious — the automation everyone can see and nobody bothers to build. Here's how to find yours.
Read →July 4, 2026
Deployable AI vs. Moonshot AI: Ship What Works Now
The AI that helps your business this quarter already exists. Chasing the moonshot version means shipping nothing. Choose deployable.
Read →July 4, 2026
Where AI Is Actually Headed for Your Business (No Hype)
I'm genuinely excited about where AI is going — and that's exactly why I tell clients to ignore most of it. The honest big picture.
Read →July 4, 2026
The Real ROI of AI Is Killing Your Process Drag
The biggest AI payoff usually isn't a fancy model — it's removing the process friction quietly draining hours and dollars every week.
Read →July 3, 2026
How to Find Your First AI Use Case (Without Wasting Money)
Most companies shop for AI backwards — tool first, problem later. Here's the operator's process for finding the one use case that pays for itself.
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