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- Indexed issues, last 90 days
- 12
- Latest publication
- Sep 18, 2026
- Audience
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- Earliest in this view
- Aug 7, 2026
Latest issues
Substack's AI Detector Is Automating Away Discernment (opens the original)
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TLDR: Substack added an AI detector built by Pangram, and most of the argument since has been about accuracy. I don’t think that’s the useful question. My collaborator asked her readers what they thought and got more replies than she’s ever had to an email, including one from a writer who had stopped publishing over it. This piece overs what those replies said, what the research shows about who detectors actually penalize, and four habits we both use to keep the judgment call in our own hands. I
What To Do After You Hand A Task To AI (opens the original)
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TLDR: When you hand a task to AI, the first AI output usually comes back close but wrong in ways you can feel and can’t name. This piece is my process for what happens next: roam for options when you don’t know what you want, recognize exactly what’s off, refine it with one clear instruction, and reinforce by saving the correction as a rule. If you want an outside read on how you work with AI right now, book a free 30-minute AI diagnostic.<div class="captioned-image-co
Apply Design Taste on Command (opens the original)
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TLDR: You have probably been told to have taste and to act as the art director when you use AI to design something. That advice is correct, but it’s incomplete. It’s not usable if nobody ever taught you what to look at. This piece explains why that gap exists, then hands over to of UX + AI, a designer, for the questions she uses to decide whether a design is actually working. Her MCP, with over 100 design methods you can pull into whatever AI you already use, is linked at the bottom.<div class="
5 Factors That Monetizes An AI Assessment (opens the original)
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TLDR: An AI powered assessment scores someone on a set of questions and hands back a report about their situation. Two builds stand out: one had fifty takers and made nothing, another had just over sixty and has brought in more than $20,000 so far. There are 5 items that made a $20,000 difference between two identical AI assessments. At the end there is a free tool that designs a powerful assessment from your own method.<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/
The 3 Decisions Behind Every Task You Hand To AI (opens the original)
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TLDR: Most AI output is competent and forgettable, and the cause is one thing: the handoff. You make three decisions every time you delegate to AI: what you hand over, what you hand it with, and what you take back. I asked 23 founders, consultants and creators who use AI daily how they run each one, and their answers turned into a delegation framework of ten small moves you can use on your next task. If you want an outside look at your own process, take the AI Readiness Diagnostic at the end.<a
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