How to Write a Definition Block That Gets Cited by AI

A definition block is a concise opening paragraph, typically 40 to 60 words, that directly answers the question “what is [topic]?” in a format AI engines can easily extract and cite. It sits at the top of your content, immediately after the heading, and serves as a pre-packaged answer that language models like ChatGPT, Perplexity, and Claude can lift directly into their responses.

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Key Takeaways

• Definition blocks are the single highest-impact quick win for AI citation optimization
• The ideal length is 40 to 60 words, matching featured snippet preferences
• Use the pattern: “[Topic] is a [category] that [does what] for [whom]”
• Place your definition immediately after the H1 or H2, before any context or narrative
• Avoid fluff words like “basically,” “essentially,” or “in simple terms”
• Test your definition by asking: can this sentence stand alone as a complete answer?

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I used to bury my definitions.

I’d write an engaging introduction, build context, tell a story, and somewhere around paragraph four I’d finally explain what the thing actually was. It felt natural. You set the scene, then deliver the payload.

Turns out that’s exactly backwards for AI citation.

I discovered this while auditing pages that get cited by ChatGPT and Perplexity. The pages that got picked up almost always had one thing in common: a clean, extractable definition right at the top. No preamble. No context-setting. Just a direct answer to “what is this?”

The pages that got ignored? Many were objectively better content. More thorough, better researched, more nuanced. But the definition was buried, or it was spread across multiple paragraphs, or it used language that was too hedged to extract cleanly.

AI engines aren’t evaluating your content like a human reader. They’re scanning for the most extractable, citable snippet that answers the query. If they have to dig for it, they’ll cite someone else who made it easy.

Why definition blocks matter now

For years, SEO experts talked about “answering the question quickly” as a best practice. Put your answer near the top. Don’t bury the lede. Standard advice.

But the stakes were relatively low. If your definition was in paragraph three instead of paragraph one, you might miss a featured snippet. You’d still rank. You’d still get traffic.

AI citation is different. There’s no second-place prize.

When someone asks Claude “what is content marketing?” it doesn’t return a list of ten options. It synthesizes a single answer from sources it trusts. If your definition isn’t easy to extract, you’re not in the running.

Research from content optimization platforms suggests that featured snippets, which use similar extraction logic to AI citation, strongly prefer answers in the 40 to 60 word range, according to Semrush’s featured snippet analysis. That’s not a coincidence. It’s the length that answers a question completely without including unnecessary context.

The bar for citation isn’t “be the most authoritative source.” It’s “be the easiest piece of information to pick up and place into an answer,” as one AI optimization guide put it. Definition blocks are how you clear that bar.

What makes a definition citable

Not all definitions are created equal. Through my audits, I’ve identified the patterns that consistently get cited versus those that get passed over.

The anatomy of a strong definition

A citable definition has four components:

1. The topic, stated explicitly. Start with the exact term you’re defining. “Content marketing is…” not “This approach to marketing…”

2. The category it belongs to. What type of thing is this? A strategy, a tool, a methodology, a framework. This helps AI engines classify the concept.

3. What it does or accomplishes. The core function or purpose. Action-oriented language works best here.

4. Who it’s for or what problem it solves. Context that makes the definition complete and useful.

Here’s the pattern: “[Topic] is a [category] that [does what] for [whom/what problem].”

Example: “Content marketing is a strategic marketing approach that focuses on creating and distributing valuable content to attract and retain a clearly defined audience.”

That’s 26 words. Complete. Extractable. Citable.

What kills citability

I see the same problems over and over:

Hedging language. “Content marketing is basically a way of…” The word “basically” signals uncertainty. AI engines prefer definitive statements.

Dependent context. “As we discussed earlier, this technique…” Your definition needs to stand alone. It can’t reference other parts of your content.

Multiple sentences masquerading as one. “Content marketing is a strategy. It involves creating content. The content attracts audiences.” Break this into one cohesive sentence.

Passive voice. “Content is created and distributed by marketers to…” Active voice is clearer and more extractable.

Starting with fluff. “In today’s digital landscape, content marketing has emerged as…” Delete everything before the actual definition.

Step 1: Identify your defining question

Before you write, figure out exactly what question your definition answers.

For most content, this is some variation of “What is [topic]?” But it might be more specific:

• What is [topic] in [context]?
• What does [topic] mean for [audience]?
• How does [topic] work?

The question shapes the definition. “What is machine learning?” requires a different definition than “What is machine learning in healthcare?” Same topic, different scopes.

Write out the question explicitly. It should match how someone would actually ask an AI. If your target query is “what is a definition block,” your definition should start with “A definition block is…”

Step 2: Write the core definition in one sentence

Start with the pattern: “[Topic] is a [category] that [does what] for [whom].”

Don’t try to be clever. Don’t try to differentiate your definition from competitors. Just write a clear, accurate, complete answer.

First draft example: “A definition block is an opening paragraph that defines a topic for AI engines to cite.”

That’s a start, but it’s missing specificity. What kind of paragraph? What makes it work?

Second draft: “A definition block is a concise opening paragraph, typically 40 to 60 words, that directly answers the question ‘what is [topic]?’ in a format AI engines can easily extract and cite.”

Better. Now we have the category (opening paragraph), the distinguishing characteristic (concise, specific length), and the function (answers the what-is question in an extractable format).

Step 3: Check the word count

Count your words. Aim for 40 to 60.

Under 40 words, you probably haven’t provided enough context for a complete answer. Over 60 words, you’re likely including information that belongs in the body content, not the definition.

If you’re over 60 words, look for:

• Redundant phrases (“in order to” → “to”)
• Unnecessary qualifiers (“very,” “really,” “extremely”)
• Clauses that could be separate sentences in the body

If you’re under 40 words, look for:

• Missing context (who is this for?)
• Missing differentiation (what makes this distinct?)
• Missing function (what does it accomplish?)

The word count isn’t arbitrary. Google’s documentation on featured snippets notes that paragraph snippets are “succinct, definitive, and clear.” Research from Backlinko found the average featured snippet paragraph is around 40 to 50 words as of 2025. AI engines seem to have inherited this preference.

Step 4: Eliminate extractability killers

Read your definition and ask: can this sentence stand completely alone?

If someone saw only this sentence, with no surrounding context, would they understand the concept? Would they get value from it?

Look for these extractability killers:

Pronouns without antecedents. “It is a powerful approach…” What is “it”? Replace with the actual topic.

References to other content. “As mentioned above…” There is no “above” when your definition gets extracted.

Jargon that requires explanation. If your definition uses a term that needs its own definition, simplify.

Questions. “What if you could attract customers without advertising?” Questions don’t work as standalone answers.

Conditional language. “If you’re a marketer, you might find that…” State facts, not possibilities.

Step 5: Position it correctly

Placement matters as much as content.

Your definition block should appear:

Immediately after the H1 or section H2. Not after an introduction. Not after a hook. Directly under the heading.

Before any narrative or context. Save your story, your personal experience, your “why this matters” for after the definition.

As the first substantial text element. Bylines, dates, and category tags can precede it. Body content cannot.

Think of it like an inverted pyramid, the journalism structure taught at every journalism school and described in writing guides like The Daily Writing Tips lead paragraph guide. Most important information first. Supporting details after.

For this blog post, notice how I structured it. The definition block comes right after the title and metadata, before my personal hook about burying definitions. The definition can be extracted cleanly. The story provides context for humans but isn’t necessary for AI extraction.

Step 6: Add supporting structure

A definition block works best when it’s reinforced by supporting elements:

Schema markup. Add Article or BlogPosting schema with the definition in the description property. This gives AI engines the definition in machine-readable format too.

Meta description alignment. Your meta description should echo or expand on your definition block. Consistency across elements builds confidence.

H2 and H3 headings that expand on components. If your definition mentions “five key principles,” have an H2 for each principle. The structure validates the definition.

FAQ schema for related questions. If people ask “what is [topic]” they probably also ask “how does [topic] work” and “why is [topic] important.” Add FAQPage schema for these.

Step 7: Test and refine

Before publishing, run two tests:

The extraction test. Copy just your definition block into a note. Read it in isolation. Does it make sense? Does it fully answer the question? Would you be satisfied if this was the entire answer you received?

The query test. Ask ChatGPT or Perplexity the question your definition answers. Look at what they cite. How does your definition compare to the sources they’re currently using? Is yours more extractable, more complete, more current?

If existing citations are better than yours, study them. What makes them work? Adapt those patterns.

After publishing, monitor. Tools like Semrush and Ahrefs can show you which queries your page appears for. If you’re ranking but not getting cited, your definition might need refinement.

Common definition block patterns

Here are templates that consistently perform well:

The standard definition: “[Topic] is a [category] that [primary function] for [audience/use case].”

Example: “A landing page is a standalone web page that captures visitor information through a focused call-to-action for marketing campaigns.”

The “is the process of” definition: “[Topic] is the process of [doing what] to [achieve what outcome].”

Example: “Keyword research is the process of discovering and analyzing search terms that people enter into search engines to use for SEO and content strategy.”

The “refers to” definition: “[Topic] refers to [the specific thing or practice], typically used for [purpose].”

Example: “Zero-click search refers to a search engine results page that answers the user’s query directly, typically used for informational queries where no click is needed.”

The comparative definition: “[Topic] is a type of [broader category] that [differentiating characteristic].”

Example: “Machine learning is a type of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed.”

What happens when you get this right

I rewrote the definitions on 15 pages in late 2025. Same content otherwise. Just moved and refined the definition blocks.

Within six weeks, as of December 2025, three of those pages started appearing in AI citations where they hadn’t before. One page went from zero AI mentions to being cited in roughly 40% of the queries I tested against.

The content didn’t change. The authority didn’t change. The backlinks didn’t change. The only difference was making the definition extractable.

This is the asymmetric opportunity in AI optimization right now. Most content still buries its definitions. Most pages make AI engines work to find the answer. Being the page that hands them a clean, citable block is often enough to win.

Definition blocks as a diagnostic

Here’s something I’ve started doing: using definition block quality as a proxy for overall page quality.

If I can’t write a clean 40 to 60 word definition for a page, that’s a signal. Maybe the page is trying to cover too much. Maybe the topic isn’t well-defined. Maybe I don’t actually understand what I’m trying to communicate.

The discipline of writing a definition block forces clarity. What is this really about? What’s the one thing someone should understand?

Pages that can’t answer that question clearly don’t get cited. But more importantly, they probably aren’t serving readers well either.

The definition block is the test. If you can write one, you understand your content. If you can’t, you have work to do.

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