For the forseeable future, AI tools will continue to generate such incomplete and sometime hallucinated outputs that there will be a continuing need for a "human-in-the-loop" to not only use several LLMs to review each other's output but to fact-check the final output. Using one LLM alone results in mediocre quality. Using two LLMs results in (sometimes very) good quality. Use three LLMs with human verification for great/outstanding results.

"1,131 people across the documentation industry responded to the 2026 State of Docs survey — more than 2.5x the number of respondents last year. But the size of the sample matters less than what it represents: a genuine cross-section of the people who create, manage, evaluate, and depend on documentation.

Documentation’s role in purchase decisions is stable and strong, and the case that docs drive business value is well established. The shift this year is in what documentation is being asked to do, and who — and what — is consuming it.

AI has crossed the mainstream threshold for documentation, both in how docs get written and how they get consumed. Users are arriving through AI-powered search tools, coding assistants, and MCP servers. Documentation is becoming the data layer that feeds AI products, onboarding wizards, and developer tools. The teams investing in this shift are treating documentation as context infrastructure, not just a collection of pages.

But adoption has outrun governance, and the gap matters. Most teams are using AI without guidelines in place, and documentation carries a higher accuracy bar than most content. After all, one wrong instruction can break a user’s implementation and erode trust in the product.
(...)
Writers are spending less time drafting and more time fact-checking, validating, and building the context systems that make AI output worth refining."

https://www.stateofdocs.com/2026/introduction-and-demographics

#TechnicalWriting #TechnicalCommunication #SoftwareDocumentation #DocsAsProduct #AI #GenerativeAI

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Working with LLMs is a skill that is often based on what you enjoyed about your work. There are people who love the outcome and people who love the process.

If you most enjoy the process of writing, coding, etc then you’ll hate working with LLMs but if you most enjoy having a finished product you created then you see them as a tool to get you there faster.