HeyJaredHuman x AI
Exploring how technology and humanity evolve together. Essays and insights on AI, learning, and conscious leadership by Karine Allouche.
- Indexed issues, last 90 days
- 5
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- Sep 28, 2026
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- Jul 29, 2026
Latest issues
Who Is Redesigning the Bargain? (opens the original)
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In April I read that Meta would begin capturing its employees’ mouse movements, keystrokes and button clicks. I read it twice, because I assumed I had misunderstood the purpose.I had filed it as surveillance, the familiar story about employers watching whether people are really working. That is not what it is. Meta said it plainly: “If we’re building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them.” Nobody is being grad
If AI Is an Operating-Model Transformation, Who Owns It? (opens the original)
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Over coffee a few weeks ago, someone asked me a question I have kept turning over since.I had just described a pattern I see often. Boards say they are not getting AI right. CEOs who know their business deeply hand the change to their CTO, or to whoever is most technical, and move on. He listened, agreed, and asked:“What would have to be true to change that?”I have come to believe the AI gap is an operating-model gap. In two engineering teams I worked with recently, AI adoption was almost identi
The AI Gap Is an Operating-Model Gap (opens the original)
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This week a chart from BCG’s new CEO survey came across my feed. Four rows, each showing how many CEOs name a barrier to scaling AI, and how many have actually done something about it.56% say linking AI to the P&L is a key barrier. 14% have defined the P&L impact for all their AI initiatives. 55% name funding people and change. 32% have funded it. 30% have brought HR into AI governance, while 82% have brought in technology.In every row, action trails recognition, in one case by more than 40 poin
Your Team Got Faster. Your Company Didn't. (opens the original)
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When we started redesigning our company around AI, I braced for a fight over the technology. But it never came, people wanted the tools, and complained about not getting them fast enough. As a result, some tasks got faster, but the company did not accelerate evenly.The drag was the organisation, and the supporting operating model. It was roles that had not caught up to what the tools could do. It also was decision rights nobody had redrawn. Or data that was still unavailable, or too immature to
The Hardest Part Starts After Adoption (opens the original)
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Four months ago I made a call that most of my peers would have argued with.After standing up our AI transformation teams, each team came out with a document setting out its strategic goals, the workflows we were targeting with AI, the AI capability infrastructure it would need, and what the organization looks like once AI supports part of the execution. It also named where we would need judgment, what would never be done with AI, what has to be reviewed, and what could be automated.From there, e
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