If you want your website to “talk back” — to answer questions in plain language — you need better content design. NLWeb is one of the new tools that helps websites become conversational. In this post, we’ll walk through how to design content so that NLWeb or similar AI endpoints can use it well.
Before diving into design, let’s explain what NLWeb aims to do:
Because AI endpoints depend on content structure, not just raw text, how you write and organize your content matters more than ever.
If your content is messy, scattered, or not well organized, AI might pick confusing or irrelevant bits to answer questions. But if content is clean, broken into small chunks, and well labeled, AI endpoints can do better.
Good content design helps in at least three ways:
Below are guidelines you can follow when writing or reorganizing your site content so NLWeb (or a similar AI endpoint) can use it well.
AI systems like NLWeb rely on structured data — data you label so machines understand. That includes:
By embedding structured data, you tell AI: “This text is a product with name X, price Y, feature Z.” That helps with accuracy.
Don't have just one huge page full of everything. Instead:
If content is atomic (i.e. smallest useful unit), AI can combine bits smartly.
Use consistent names and labels. If you call something “Return Policy” in one place, don’t call it “Refund Rules” somewhere else without linking them or making that clear. Consistency helps AI map concepts.
Also, include keywords and synonyms in your content so AI can match variations of user queries.
Often, a user’s question touches more than one page or section. If your content links related topics, AI can navigate that structure.
Example: On a recipe site, a “Vegan Recipes” page might link to “Protein Sources” or “Ingredient Substitutes.” That helps when a user asks: “What protein can I use instead of eggs?”
Besides structured markup, your site should have:
These help AI pick relevant content and time-order answers.
AI endpoints often cache or index content. If your pages never update, users may get stale info.
Let’s imagine an e-commerce site selling laptops. Here’s what a well-structured product entry might look like:
Then your RSS feed or JSON feed includes this structured data so AI can ingest it easily.
When a user asks, “Show me laptops with 16 GB RAM under $1,000”, the system can filter by structured fields and return relevant models.
Let me outline a simple workflow you or your content team can follow:
Step Action Why It Helps 1 Audit existing content: see what has good structure and what doesn’t You must know where your weak spots are 2 Decide on ontology (topic categories, key fields) Helps you keep consistency 3 Rewrite long pages into smaller topics Easier for AI to serve precise answers 4 Add structured data (Schema, JSON-LD, RSS) Provides machine-readable context 5 Interlink related content Helps breadth of answers 6 Tag, categorize, and include metadata Improves filtering and relevance 7 Test sample queries against AI endpoint See how it answers your content 8 Update and evolve content Keep things fresh and accurate
Once you’ve designed or restructured your content, you need to test.
Here’s how:
By iterating, you’ll improve the match between user queries and the content your AI endpoint serves.
Designing content for NLWeb or similar AI endpoints is not just about writing well — it’s about writing smartly, with structure, context, and clarity in mind. A human reader should understand it easily, but also an AI should be able to pick apart your content and recombine pieces to answer user questions.
As conversational web tools grow, your content’s quality and structure will become even more critical. Start small, test often, and evolve your approach. You’ll be ahead when AI agents become the standard way people explore the web.
If you like, I can help you draft a “checklist for AI-ready content” or a sample guide specific for your site. Do you want me to help with that next