Insights on documentation, content, and writing well.
Practical writing on technical documentation, content strategy, AI search, and how to build documentation that actually works for your users.
Why most enterprise documentation fails its users before they even start reading
The problem with most enterprise documentation is not that it is wrong. It is that it was written for the person who already knows the answer. We break down the structural and stylistic failures that make documentation unusable, and what it takes to fix them.
Read articleHow to write a style guide your team will actually follow
Most style guides fail not because they are wrong but because they are ignored. Here is how to write one that sticks, with practical examples from real documentation projects.
Answer Engine Optimization: how to get your documentation cited by AI
ChatGPT, Perplexity, and Google SGE are changing how people find information. Here is what it takes to get your documentation into AI-generated answers instead of just search results.
The difference between API documentation that developers love and documentation they tolerate
Great API documentation does not just describe endpoints. It anticipates questions, provides working examples, and respects the developer's time. Here is how to tell the difference.
Information architecture for documentation: how to structure content users can actually navigate
Content that is hard to find is content that does not get used. This is a practical guide to designing documentation structure that matches how users think, not how products are built.
Active voice, passive voice, and when the rules do not apply in technical documentation
The rule is simple: use active voice. The reality is more nuanced. Here is how experienced technical writers decide when to break the rule and why it matters for documentation quality.
How to structure documentation for RAG systems so your AI actually retrieves the right content
Retrieval-augmented generation is only as good as the content it retrieves. Here is how to structure, chunk, and tag your documentation so RAG systems surface the right answers.
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