Every now and then, the industry invents a new “standard” that's supposed to solve everything. Right now the hype train is parked at llms.txt. People call it the robots.txt for AI. Cute analogy. The problem is: it doesn't actually work that way.
At Redocly, we like to experiment. So we added automatic llms.txt support to our platform. Turn it on, it generates the file. Easy. We even ran a full Phronesis project on it — testing across models, prompts, and scenarios.
The results? Pretty underwhelming.
- Unless you explicitly paste the llms.txt file into the LLM, it doesn't do anything.
- When you do paste it, you'd get better results just pasting the actual Markdown docs.
- No model we tested spontaneously “read” or respected llms.txt on its own.
That's not a governance breakthrough. That's a parlor trick.
We also pulled logs. How often are llms.txt and llms-full.txt even being accessed? Answer: basically never. When they are, it looks like someone experimenting in a single LLM session, not systematic use by the models.
Michael O'Neill at the University of Iowa checked too — same conclusion: don't lose sleep over llms.txt.
The best thing about building llms.txt wasn't llms.txt. It was what came after:
- one-click copy of any page in Markdown,
- links you can drop straight into ChatGPT or Claude,
- smooth handoff from docs → AI assistant.
That's useful today. That's how people actually want to interact with docs in an AI-first world.
Not all experiments flop. Last week, we ran another Phronesis project, this time on two of our new MCP features (not yet public). The difference was night and day.
With Docs MCPs, we saw real value. They made docs instantly more useful inside AI workflows. The debriefs weren’t full of head-scratching like with llms.txt — they were full of smiles.
That’s the difference between smoke and fire. LLMS.txt is smoke. Docs MCPs are fire.
Focus on making good content.
If we want content governance in AI, it won't come from a text file no one reads. It'll come from:
- licensing,
- attribution,
- legal clarity,
- real standards AI companies can't ignore.
Until then, llms.txt is just… there. More checkbox than standard.
We tried it. We measured it. We learned from it. And now we can say it out loud: llms.txt is overhyped.
The sooner we move past the illusion, the sooner we can focus on solutions that actually matter.