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Gonna start posting again soon 😈🥩💪🏾 #bator #stroking #lowhangers #batespread #bde #stonerboner

91,970 Aufrufe • vor 2 Jahren •via X (Twitter)

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New! ✨ Lex 🤝 Kit ✨ We built a new technique to train AI to write in your voice—using your Kit newsletters—that's the closest I've ever gotten AI to sound like me. 👉 > "Damn. This is really solid. Immediately obvious that it is trained on my newsletters." — Nathan Barry > "damn finally just read this and those subject lines and that example newsletter, it feels 90% nailed, super intrigued how we can build this tone of voice into the app more, feels like a total gear shift for any AI suggestions." — fred rivett 🇬🇧📈 (usually a skeptic of the "write a draft for me" approach) The way we did it is cool and (I think?) new! We all know if you go to ChatGPT or Claude and ask it to write for you, it's gonna sound like AI. Maybe you've tried uploading some examples or a style guide and still get disappointing results. Lots of AI writing apps purport to "write in your style," but they typically just generate a short summary of your style using a prompt like "Analyze the style and tone of these writing samples" and then stick it into the prompt. Maaaaybe they'll throw in a few examples. We've tried this and didn't think it was great, so we killed it. But when Nathan Barry pushed us to think about this problem again, we came up with a subtly new technique that had a big impact on the results. (The reason I'm sharing it is because our goal is to build the world's best interface for collaborating on text, and the world's best platform for saving, sharing, and running prompts. Proprietary prompting techniques are not our thing.) Instead of just asking what the "style" is (a very fuzzy question) we ask AI what patterns it can find. Specifically we ask it to look for patterns in structure and tone. Then—and this is crucial—we ask the AI to generate a detailed set of instructions that a new writer could use to consistently reproduce those patterns. We include those instructions and a bunch of examples in a prompt (often quite a large one, it's kinda expensive for us tbh). I think it works so much better than just giving examples or giving a broad overview of "style" because LLMs are trained to pay close attention to instructions and thrive on specificity. Here we ask the LLM to look for very specific patterns and generate equally specific instructions to reproduce those patterns. The other cool thing is unlike a fine-tuned model this is powered by a big-ass prompt that you can inspect and modify to your liking. Does it sound a little too enthusiastic? A bit cheesy? Just edit the prompt. Of course it's not perfect, it's still gonna need careful editing, but to us this feels like an obvious leap. I'd be really curious to hear if it feels the same to you. To start this is only available via our Kit integration but we'll start rolling it out more broadly soon. You can sign up at 👉 Would love your honest feedback!

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