Working in crypto has taught me something unexpected about the gap between academic research and practical implementation. Academic research operates on different timelines and incentives than industry. In academia, you work privately for months, write comprehensive papers, submit to peer review, wait for acceptance, and then publish complete results. The cycle takes months or years. Crypto moves differently. Ideas get tweeted immediately, iterated publicly, and built collaboratively in real-time. The cycle takes hours or days. This creates constant tension. When traditional academics see researchers posting incomplete ideas on Twitter, they view it as premature self-promotion. "Stream of consciousness" posting violates their norms about rigorous, complete work. But I'm starting to think the crypto approach might be superior for certain types of problems. Cryptography benefits from many eyes examining approaches for potential flaws. Publishing work-in-progress invites immediate scrutiny and improvement. My experience with ChatGPT illustrates this. I spent two days working with it on a BitVM research problem. It made obvious math errors but also identified connections to obscure 25-year-old papers that my professor colleagues missed. The immediate feedback loop, even from an AI, accelerated my thinking. BitVM 3 development exemplifies this new model. No single inventor exists because multiple teams are building simultaneously on publicly shared ideas. The specification emerges organically from community discussion rather than being defined by central authority. The traditional academic model prioritizes completeness and rigor. The crypto model prioritizes speed and collaboration.