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Nathan Baschez

@nbaschez • 49,287 subscribers

Founder of @lexdotpage. AI scout at @trueventures. Previously: co-founder @Every, first employee @SubstackInc. Always: @SoniaBaschez

Shorts

Took my daylight to the beach Re-read Paul Graham’s “taste for makers” Noticed a line about Durer leaving no room for later engravers to improve on his work Looked up Durer Wow

Took my daylight to the beach Re-read Paul Graham’s “taste for makers” Noticed a line about Durer leaving no room for later engravers to improve on his work Looked up Durer Wow

20,538 次观看

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Introducing Roughdraft! A new open source project designed to make collaboration with agents better. The idea is to bring commenting and suggested changes to markdown (e.g. plan docs) in a nice interface. Free, local, etc. 👉 👈

Introducing Roughdraft! A new open source project designed to make collaboration with agents better. The idea is to bring commenting and suggested changes to markdown (e.g. plan docs) in a nice interface. Free, local, etc. 👉 👈

352,084 次观看 • 15 天前

New in Lex: 👉 Huge overhaul of Ask Lex, our AI chat for writers

New in Lex: 👉 Huge overhaul of Ask Lex, our AI chat for writers

47,967 次观看 • 1 年前

LEX V2 — part 3 of 5 Introducing Personas Get different perspectives on your writing. Also, this solves many of the most common annoyances with LLMs, e.g. sycophancy! Try it 👉 (Thanks to eigenrobot & Nick for the inspiration!)

LEX V2 — part 3 of 5 Introducing Personas Get different perspectives on your writing. Also, this solves many of the most common annoyances with LLMs, e.g. sycophancy! Try it 👉 (Thanks to eigenrobot & Nick for the inspiration!)

26,881 次观看 • 1 年前

LEX V2 — part 2 of 5 Introducing the world's most powerful interface for using AI to edit text

LEX V2 — part 2 of 5 Introducing the world's most powerful interface for using AI to edit text

25,806 次观看 • 1 年前

LEX V2 — part 1 of 5 We redesigned and rebuilt our start page from the ground up

LEX V2 — part 1 of 5 We redesigned and rebuilt our start page from the ground up

25,161 次观看 • 1 年前

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!

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!

16,279 次观看 • 1 年前

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