Notes from the studio, newest first. Written when there is a lesson or an example worth passing on, not to a schedule. RSS.
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Automation makes the wrong work faster
Automation makes work faster. It does not ask whether the work should happen - and in most organisations the larger cost is not work done slowly, but work that should never have started.
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Why every company will build a brain
On the company brain - why twenty years of trying to build one failed, what changed, and what it means for the shape of the firm.
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Models compress. They cannot invent your company.
A language model is brilliant at turning many facts into one clean answer, and unreliable at turning too little into the truth. That asymmetry - not the model's cleverness - is the real constraint, and it is why grounding matters more than scale.
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Most AI spend never reaches the P&L
The failure rate isn't a model problem. It's an operating-model problem - and it has a specific cause.
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What ai-native actually means
The market defines ai-native by birth certificate - the firms born with the model. The truer definition is structural, not chronological, and it is fully available to the company you already run.
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What stays human
As working intelligence becomes abundant, the scarce thing is no longer analysis. It is judgement, taste, and the will to mean it.
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Decisions with the model in the loop
AI as a tool you pick up, or an agent that replaces you. Both pictures miss the real change. The shift is to the loop.
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A company your model can read
A company knows far more than it can say. Until that knowledge is made legible, a model cannot do anything useful inside it.
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The end of scarce intelligence
Every company alive today was built around the assumption that working intelligence is scarce. That assumption has quietly stopped being true.