Companies Are Missing Out by Not Writing Documents for AI, CTO Says

Your company’s database of screen-recorded webinars could be on its way out.

Laura Tacho, CTO of developer productivity platform DX, says companies should at least consider rewriting their documents to make them more legible for AI.

Corporate documentation is often a messy haze of memos, slide decks, and video trainings. In the age of AI, Tacho told Business Insider that training materials should be in text form, so that they may easily be read by a large language model.

Text-based procedures are even more important for developers, who can immediately feed their documentation to an AI code editor like Cursor.

Tacho said she thinks that documents can benefit both humans and LLMs. Speaking about the topic on the “Pragmatic Engineer” podcast, she said that “AI-first” companies were overhauling their internal documentation for LLM consumption.

“That’s been the biggest way that I’ve seen companies think about or already start trying to change the way that they architect their services,” Tacho told podcast host Gergely Orosz.

In a follow-up interview with BI, Tacho elaborated on her policy for documentation. Well-organized, text-based procedures don’t just help an LLM or a human worker, she said. The “venn diagram is a circle,” she said.

“Documentation is a huge point of friction for nearly every organization,” Tacho told BI. “There’s a lot of efficiency gain to be had when documentation is more fit for purpose. This is an area where what’s good for the human is also good for the LLM.”

Human-first documentation often relies on “visual cues” and screenshots, which the AI can find incomprehensible, Tacho said. She recommended that all photos have text descriptions alongside them.

Social media sites often have alternative texts and captioning to make their services less exclusively visual. Tacho said that corporate document-makers can “take a note from the world of web accessibility.”

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“It is so important for people who are not using their eyes to access the screen,” she said.

She said other tasks, like centralizing documents, help an LLM’s ease of access and also make the human worker’s life easier. Tacho used the developer term, saying that companies should “defrag” their policies.

“Documentation is made piecemeal, a little here, a little there,” she said. “You have to hop between different pages in order to put together the complete instruction of what you’re supposed to do.”

Tacho also listed some technical elements of documentation, like making sure the HTML markup is semantic, which can help ensure LLM readability.

Some companies have already begun the change. In May, Vercel’s former VP of Developer Experience Lee Robinson posted about the company’s documentation on X.

“We’re starting to add cURL commands to Vercel’s documentation wherever we previously said ‘click,'” Robinson wrote. “In the future, maybe computer using agents could log in and perform actions for you, but this feels like a nice incremental step for the LLMs.”

Tacho expects that more companies will join Vercel in making their documents easily legible to AI. She found that engineers were wasting over 30 minutes a week looking for information they couldn’t find in documentation. AI code editors should automate those problems — if the LLM can read the documents properly.

“When you think about how much time is being wasted due to poor documentation, it becomes actually a very critical business problem,” she said.