We support the llms.txt convention for making documentation available to large language models and the applications that make use of them.
The /llms.txt file – llms-txt
A proposal to standardise on using an /llms.txt file to provide information to help LLMs use a website at inference time.
feat: add llms.txt endpoint for LLM-optimized documentation by quantizor · Pull Request #2388 · tailwindlabs/tailwindcss.com
Add /llms.txt endpoint that serves a concatenated, text-only version of all Tailwind CSS documentation pages optimized for Large Language Model consumption. Extract text from MDX files, removing J...
Wikipedia:LLM-assisted translation
This guideline applies to machine translation tools that include a large language model ("LLM"). Assume that it applies to any online translation tool unless you have confirmed there is no LLM element.
Yuchen Jin on Twitter / X
Karpathy’s “LLM Wiki” pattern: stop using LLMs as search engines over your docs. Use them as tireless knowledge engineers who compile, cross-reference, and maintain a living wiki. Humans curate and think.Diagram generated by my Claude agent knowledge worker. https://t.co/5u5i1GeFK8 pic.twitter.com/NIaq3KlAok— Yuchen Jin (@Yuchenj_UW) April 4, 2026
Wikipedia:Writing articles with large language models
Text generated by large language models (LLMs)[a] often violates several of Wikipedia's core content policies. For this reason, the use of LLMs to generate or rewrite article content is prohibited,[b] save for these two exceptions:
Large language models reduce public knowledge sharing on online Q&A platforms
Abstract. Large language models (LLMs) are a potential substitute for human-generated data and knowledge resources. This substitution, however, can present
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory · GitHub
Large language model
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots.[1] Biased or inaccurate training data can make an LLM's output less reliable.[2]
How to Build an LLM Knowledge Base
A hands-on guide to building a simple LLM knowledge base with raw markdown sources, a compiled wiki, reusable prompts, and an agent that keeps improving the knowledge base over time.
Patrick Collison on Twitter / X
I want some kind of LLM workflow tool.• Ability to manage a set of input files (Markdown or similar), plus other general-purpose context.• With real-time collaboration. (And maybe some concept of snapshots or VCS integration.)• And the ability to create/manage a inference…— Patrick Collison (@patrickc) June 6, 2026
Docs as Code: The Best Guide for Technical Writers
Recently, my work has involved writing a lot of documentation and. Doing this has introduced me to...
sosumi.ai - Apple Docs for LLMs
sosumi.ai provides Apple Developer documentation in an AI-readable format by converting JavaScript-rendered pages into Markdown.
The Case Against LLMs as Rerankers
Authors: Apoorva Joshi, Zhenmei Shi, Akshay Goindani, Hong LiuResearch Leads: Zhenmei Shi, Akshay Goindani, Hong Liu Large language models are increasingly being used for a broad range of tasks, in…
We are excited to introduce Doc-to-LoRA and Text-to-LoRA, two related papers exploring how to make LLM customization faster. By training a hypernetwork to generate LoRA adapters on the fly, models instantly internalize new info. Blog: pub.sakana.ai/doc-to-lora/ Doc-to-LoRA: arxiv.org/abs/2602.15902
