Commercial
Coming soonWhy disagreement beats intelligence on the decisions that matter.
One confident model is a liability. What we learned building a system that argues with itself before it commits.
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Insights
Straight talk on AI, operations, and what actually works.
Field notes from doing this for real, in our own companies and our clients'. No hype, no jargon, just what we're learning about where AI creates value and where it doesn't.
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Featured article
I replaced an eight-person team with AI. Here's what actually happened.
The honest account of rebuilding a function around AI: what it took, what broke, what it freed up, and why the judgment mattered more, not less. The essay that started all of this.
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Articles
Point of view
The frontier asked for a speed limit.
What Amodei’s essay, Altman’s yes and the sharpest reply mean for a business that just wants the tools to work. Plus the December deadline nobody is talking about.
Point of view
AI solved the easy problem.
The tools got faster. Then the bottleneck moved. Why the moat was never the model, and what actually decides whether AI works in your business.
The method
The thing most AI projects get wrong.
Most businesses bolt AI onto how they already run. Why that quietly fails, and the order that actually changes the business.
The work graph
The database remembers. The work graph understands.
Every system you own sees a slice of the company. None of them sees the company. What a work graph is, and why it is the first thing we build.
Point of view
Most AI transformation is aimed at the wrong target.
The tool was never the hard part. Why the real work is understanding how a business runs, and applying AI only where it genuinely adds value.
Confidentiality
Your AI is reading your confidential data. The real question is where it goes.
Where your data actually goes when your team uses AI, the four very different answers, and the first move that costs nothing.