How to Write Content for RAG Systems

To write content for RAG systems, make each section self-contained, start sections with a clear statement of the answer, use descriptive headings, and keep facts specific and consistent. Retrieval-augmented generation (RAG) means an AI first searches for relevant text chunks, then writes an answer using them. Content that still makes sense when a single section is pulled out on its own is far more likely to be used correctly.

How RAG works in simple terms

1. A user asks a question.
2. The system searches an index (the web, or a company’s documents) for passages that match.
3. It splits pages into chunks, often a few paragraphs each, and picks the most relevant ones.
4. The language model reads those chunks and writes an answer, sometimes with citations.

Perplexity, ChatGPT with web search and Copilot all use forms of retrieval. Many companies also build RAG chatbots on their own help centres. The details differ, but the principle is the same: the AI only sees the pieces it retrieved.

Principle 1: Every chunk should stand alone

If a section says “As mentioned above, it costs less”, the chunk loses meaning once separated. Repeat the subject: “The Basic plan costs €15 per month, less than the Team plan.” Avoid pronouns that point to earlier sections. Name the product, the place or the topic in each section.

Principle 2: Headings should describe the content

Retrieval often matches the question against headings and the text beneath them. “Pricing” is weak; “How much does [product] cost for teams of 10?” is strong. Descriptive headings also help the system split the page at sensible points.

Principle 3: Lead with the answer

Put the core fact in the first sentence of each section, then explain. If the chunk is cut short, the important part survives.

Principle 4: Be specific

Vague text matches many queries weakly. Specific text matches the right query strongly. Compare:

• Weak: “We offer fast delivery across the region.”
• Strong: “Orders placed before 14:00 ship the same day and arrive in 1 to 2 working days anywhere in Belgium.”

Principle 5: Keep sections a sensible length

Very long sections may be split mid-thought. Very short ones may lack context. Aim for sections of roughly 100 to 300 words, each covering one idea.

Principle 6: Use simple, clean formatting

Use real HTML headings, paragraphs, lists and tables. Avoid putting key facts inside images, PDFs without text, tabs that load by script, or accordions that hide content from crawlers. Our LLM content formatting guidelines cover this further.

Principle 7: Keep facts consistent across pages

If one page says the warranty is two years and another says three, a RAG system may retrieve either. Audit key facts and fix contradictions. Remove or update outdated pages rather than leaving them live.

Applying this to help centres and docs

If customers use AI to ask about your product, your documentation is a likely retrieval source. Write one article per task, title it as the question, and include the product name in the text. See generative SEO for product documentation and optimizing a knowledge base for AI.

A quick test

Copy one section of your page into a blank document. Read it without the rest. Does it say what it is about, who it applies to and the key fact? If not, rewrite it until it does.

How Keboost helps

Keboost tracks the prompts customers ask across AI assistants and shows which sources they cite, so you can see whether your content is being retrieved. It then creates and distributes focused, well-structured content to improve the chances AI finds and cites your brand. Run a free AI visibility check to get started.