Episode
"But what if someone steals my idea?"
- Published
- May 28, 2026
- Duration seconds
- 3419
- Processing state
not_requested- Canonical source
- https://aggressivelyhuman.substack.com/p/75-getting-ripped-off
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Summary
Getting ripped off online used to feel like the worst-case scenario for putting your ideas out there. Now it’s a near-certainty — your work has already been scraped, ingested, and trained on, whether you wanted it to be or not. But, on the other hand, if you don’t claim your expertise early and often… you can’t be the one cited and known for your work. In this episode, we talk about the tension between wanting to be found and being afraid of being stolen from — and why the answer isn’t to publish less. We get into what AI models actually train on, what it means to claim your semantic territory, and why naming your frameworks matters more than ever in an era of linguistic convergence. We talk about real examples of being ripped off, the myth-busting around AI policies, and why information itself is a leaky moat: what’s worth protecting, what’s worth releasing, and why your discernment — not your information — is what people are actually paying for. * The first time Jessica was beat-for-beat plagiarized — and why she made the stolen idea a cornerstone of her book anyway * Why you can’t copyright a concept (only the specific words) * The myth that AI trains on your private workshops and client conversations * What an AI policy actually does — and doesn’t — protect * Claiming your semantic territory vs. resetting your authority every time you post a Reel * Why naming things (Sacred Sales Hour, Building Blocks, the Beacon Framework) creates findable entities tied back to you * Linguistic convergence: why everyone in your industry sounds similar, and what to do about it * Information is a leaky moat — what people are actually buying when they hire you * Why gatekeeping “the secret” behind an hour-long presentation burns goodwill * The difference between compounding authority…