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- Indexed issues, last 90 days
- 17
- Latest publication
- Oct 1, 2026
- Audience
- Checking…
- Earliest in this view
- Aug 10, 2026
Latest issues
You've Been Building Your AI Skills in the Wrong Order (opens the original)
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TL;DR: AI skills are the differentiator in knowledge work, but they sit on top of existing professional experience rather than replacing it. The World Economic Forum projects 170 million jobs created and 92 million displaced by 2030. Displaced workers do not transition one-to-one into the new roles without upskilling.<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/image/fetch/$s_!FA_H!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazona
The AI Do-Not-Touch List: A Faster Way Into Your AI Vision (opens the original)
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TL;DR: AI vision statements fail because AI is not a business goal, it’s an amplifier for one. The faster starting point is an AI do-not-touch list: the decisions and judgment calls AI will never make in your organization, drawn from the expertise that got you where you are.<div class="image2-in
AI Adoption Fails Because We Never Onboard It (opens the original)
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TL;DR - AI adoption differs from AI access: giving employees AI tools does not change how work gets done. The real unit of AI adoption is the workflow rather than the employee. Five layers (access, ability, trust, workflow, ownership) show where adoption stalls, and a 15-minute audit locates the blockage.<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/image/fetch/$s_!FIwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpubl
How to Decide What to Hand AI Next (and Where to Stop) (opens the original)
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A skill that interviews you about your week, ranks what’s ready to hand over, and draws the line on each one.TL;DR: What you hand AI next matters more than which tool you use. Gallup surveyed 22,573 U.S. workers in Q2 2026 and found that people using AI for one or two kinds of work report a 45% productivity gain, while those using it for seven or more report 90%. Same tools. The difference is how much they let go of.<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/image
The Best AI Model Money Can’t Buy (opens the original)
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TL;DR: Anthropic released Claude Fable 5.1 and Claude Mythos 5.1 on the same day. They are the same model with different safeguards, and only Fable is generally available. The 75% cache-read price cut got the coverage, but Fable 5.1 burns more tokens per job, and restricting the more capable version to vetted organizations is the right call.<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/image/fetch/$s_!cOAf!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubsta
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