the stream
People need to be more thoughtful building products on top of LLMs. The fact that they generate text is not the point. LLMs are cheap, infinitely scalable, predictably consistent black boxes to soft human-like reasoning. That's the headline! The text I/O mode is just the API to this reasoning genie. It's a side effect of the training paradigm (self-supervision on Internet scale text data). A vanishingly small slice of knowledge work has the shape of text-in-text-out (copywriting/Jasper). The real alpha is not in generating text, but in using this new capability and wrapping it into jobs that have other shapes. Text generation in the best LLM products will be an implementation detail, as much as backend APIs are for current SaaS. Text, like code, is a liability, not an asset. An organization should strive to own as little text as necessary to express their information and accomplish tasks. If you don't heed this warning, you end up with a Notion that has 10 copies of every piece of info
the stream 2022/11/16 16:52 People need to be more thoughtful building products on top of LLMs. The fact that they generate text is not the point. LLMs are cheap, infinitely scalable, predictably consistent black boxes to soft human-like reasoning. That's the headline! The text I/O mode is just the API to this reasoning genie. It's a side effect of the training paradigm (self-supervision on Internet scale text data). A vanishingly small slice of knowledge work has the shape of text-in-text-out (copywriting/Jasper). The real alpha is not in generating text, but in using this new capability and
related reading
- Guardian Angels: LLM Personalization for Productivity and Security · Gwern.netgwern.net
- What We’ve Learned From A Year of Building with LLMs – Applied LLMsapplied-llms.org
- Writing for LLMs So They Listen · Gwern.netgwern.net
- Outsourcing thinking – Erik Johannes Husomerikjohannes.no
- GenAI Handbookgenai-handbook.github.io
- What We Learned from a Year of Building with LLMs (Part I) – O’Reillyoreilly.com
- How LLMs Work, Explained Without Math - miguelgrinberg.comblog.miguelgrinberg.com
- LLMs Are Not All You Need | Pineconepinecone.io
- Things we learned about LLMs in 2024simonwillison.net
- crawshaw - 2025-01-06crawshaw.io
- Stop Sloppypasta: Don't paste raw LLM output at peoplestopsloppypasta.ai
- Productizing Large Language Modelsblog.replit.com