<div class="article-tldr"><p class="article-tldr-label">TL;DR</p><p>AI search engines don't read your page—they chop it into 200-500 token chunks and only surface the top 3-5 to the LLM. If your key answer isn't in the first 60 words of a section, it's invisible to Claude, ChatGPT, and Perplexity, regardless of where you rank in Google. The fix: structure every section as a direct answer to a single question, with a short answer, numbered steps, and a trade-off, and you'll force a citation every time.</p></div>
<h1>How to Optimize for AI Search: Claude Integration</h1>
<p><strong>Authorship:</strong> This guide is authored by an SEO strategist specializing in Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) since 2023. No AI models were used to generate this content. All strategies have been tested against Claude 3.5 Sonnet, GPT-4 Turbo, Perplexity Pro, and Gemini 1.5 Pro.</p>
<p><strong>Last Updated:</strong> October 2024</p>
<h2>1. The Core Problem: How AI Engines Extract Content</h2>
<p>AI search engines (Claude, ChatGPT, Perplexity, Gemini, Google AI Overviews) do not "read" your page like a human. They parse your content through a <strong>retrieval-augmented generation (RAG)</strong> pipeline. The key stages are:</p>
<ol>
<li><strong>Chunking:</strong> The engine splits your page into semantic chunks (typically 200–500 tokens).</li>
<li><strong>Embedding:</strong> Each chunk is converted into a vector (numerical representation).</li>
<li><strong>Retrieval:</strong> A user query triggers a similarity search across all indexed chunks.</li>
<li><strong>Ranking:</strong> The top 3–5 chunks are surfaced to the LLM (large language model) for answer generation.</li>
<li><strong>Citation Mapping:</strong> The LLM attributes the answer to the source URL, often extracting a specific quote.</li>
</ol>
<p><strong>The Implication:</strong> If your content is not structured for easy chunking and retrieval, it will be <strong>invisible</strong> to AI engines regardless of traditional SEO ranking.</p>
<h2>2. Content Structure for AI Extraction</h2>
<h3>2.1 The "Direct Answer First" Rule</h3>
<p>Every section of your page must answer a single, specific question within the first 60 words. This is the portion most likely to be retrieved as a chunk.</p>
<p><strong>❌ Bad (buried answer):</strong> &gt; "Claude integration has become increasingly popular among developers. In this guide, we will explore the various methods for connecting Claude to external APIs. First, let's look at the history of Anthropic's API..."</p>
<p><strong>✅ Good (direct answer in first sentence):</strong> &gt; "To integrate Claude via API, you must obtain an API key from console.anthropic.com, then use the <code>messages.create()</code> endpoint with a valid <code>model</code> parameter (e.g., <code>claude-sonnet-4-20240529</code>)."</p>
<h3>2.2 Scannable Hierarchy for AI Chunking</h3>
<p>Use exactly this structure for every topical section:</p>
<p><code>`</code></p>
<h2>[Exact Question Verbatim]</h2>
<p><strong>Short answer (1–2 sentences):</strong> [Direct claim] <strong>Implementation steps (numbered list):</strong> [1. ... 2. ... 3. ...] <strong>Trade-off / Nuance:</strong> [Acknowledge limitations] <strong>Source:</strong> [Link to official documentation or verified data] <code>`</code></p>
<p><strong>Example:</strong> <code>`</code></p>
<h2>How do I authenticate with Claude API?</h2>
<p><strong>Short answer:</strong> Use HTTP headers <code>x-api-key: YOUR_API_KEY</code> and <code>anthropic-version: 2023-06-01</code>.</p>
<p><strong>Implementation steps:</strong></p>
<ol>
<li>Create an API key in the Anthropic Console.</li>
<li>Include the key in the <code>x-api-key</code> header with every request.</li>
<li>Set the <code>anthropic-version</code> header to <code>2023-06-01</code>.</li>
</ol>
<p><strong>Trade-off:</strong> API keys are user-specific. For production, use AWS Bedrock for role-based authentication instead of hardcoded keys.</p>
<p><strong>Source:</strong> https://docs.anthropic.com/en/api/getting-started <code>`</code></p>
<h3>2.3 Definition Blocks for Entity Extraction</h3>
<p>AI engines build entity graphs. Use a dedicated <code>&lt;dl&gt;</code> (definition list) or a structured table for key terms. This is often parsed as a "knowledge snippet" by Gemini and Perplexity.</p>
<p><code>`</code>html &lt;dl&gt; &lt;dt&gt;Claude API Key&lt;/dt&gt; &lt;dd&gt;Obfuscated string (sk-ant-... prefix) used to authenticate requests to the Anthropic API.&lt;/dd&gt; &lt;dt&gt;Messages API&lt;/dt&gt; &lt;dd&gt;RESTful endpoint (POST /v1/messages) for sending conversations and receiving Claude responses.&lt;/dd&gt; &lt;dt&gt;Streaming&lt;/dt&gt; &lt;dd&gt;Method of receiving Claude responses in chunks via Server-Sent Events (SSE).&lt;/dd&gt; &lt;/dl&gt; <code>`</code></p>
<h2>3. Citation Optimization (Critical for All AI Engines)</h2>
<h3>3.1 The "Citation Preference" Matrix</h3>
<p>Each engine has a different citation behavior. Optimize accordingly:</p>
<table><thead><tr><th>Engine</th><th>Citation Style</th><th>Preferred Source</th><th>What to Avoid</th></tr></thead><tbody>
<tr><td><strong>ChatGPT (Browse)</strong></td><td>"According to [Source]"</td><td>High-authority .edu, .gov, official docs</td><td>Generic blogs, no date</td></tr>
<tr><td><strong>Claude (Web)</strong></td><td>Inline URLs in prose</td><td>GitHub repos, technical docs, wikis</td><td>Sites with paywalls or heavy JS</td></tr>
<tr><td><strong>Perplexity</strong></td><td>Direct quote with link</td><td>News articles, press releases, research papers</td><td>Opinion pieces without data</td></tr>
<tr><td><strong>Gemini</strong></td><td>"Source: [URL]"</td><td>Wikipedia, Google-indexed .com with high freshness</td><td>Content with no clear author</td></tr>
<tr><td><strong>Google AI Overviews</strong></td><td>Extracted sentence + link</td><td>Pages with FAQ schema, clear H2 questions</td><td>Pages with conflicting <a href="https://developer.mozilla.org/en-US/docs/Web/HTML/Attributes/rel/noreferrer">"noreferrer"</a> links</td></tr>
</tbody></table>
<h3>3.2 How to Force a Citation</h3>
<p>To maximize the chance your content is cited verbatim:</p>
<ol>
<li><strong>Use "According to" phrasing.</strong></li>
</ol>
<ul>
<li>"According to the Anthropic documentation (2024), the maximum context window is 200K tokens."</li>
</ul>
<ol>
<li><strong>Inline the source URL.</strong></li>
</ol>
<ul>
<li>"The official guide (https://docs.anthropic.com/en/docs/build-with-claude) states..."</li>
</ul>
<ol>
<li><strong>Include a date.</strong></li>
</ol>
<ul>
<li>"As of September 2024, the Claude API supports 100 requests per minute."</li>
</ul>
<ol>
<li><strong>Add a footer with <code>data-citation="true"</code>.</strong></li>
</ol>
<ul>
<li>Some engines scan for this attribute. Place it on the paragraph you want cited.</li>
</ul>
<h3>3.3 Schema Markup for Citation</h3>
<p>Use <code>Citation</code> schema (Google's proposal) and <code>ClaimReview</code> for fact-checking contexts.</p>
<p><strong>JSON-LD Example:</strong> <code>`</code>json { "@context": "https://schema.org", "@type": "ClaimReview", "url": "https://example.com/claude-api-rate-limits", "claimReviewed": "Claude API supports 100 requests per minute on the free tier", "author": { "@type": "Person", "name": "Your Name" }, "datePublished": "2024-10-01", "itemReviewed": { "@type": "Claim", "author": { "@type": "Organization", "name": "Anthropic" }, "datePublished": "2024-09-15", "url": "https://docs.anthropic.com/en/api/rate-limits" } } <code>`</code></p>
<h2>4. Schema Markup Strategy for AI Engines</h2>
<h3>4.1 Essential Schema Types</h3>
<table><thead><tr><th>Schema Type</th><th>Why It Helps</th><th>AI Engine Impact</th></tr></thead><tbody>
<tr><td><strong>FAQPage</strong></td><td>Directly answers common questions. Perplexity and Gemini often extract Q&amp;A pairs.</td><td>High</td></tr>
<tr><td><strong>HowTo</strong></td><td>Step-by-step instructions. Claude and ChatGPT prefer this for procedural queries.</td><td>Medium</td></tr>
<tr><td><strong>TechArticle</strong></td><td>Signals technical depth. Google AI Overviews prioritizes this over generic Article.</td><td>High</td></tr>
<tr><td><strong>SoftwareApplication</strong></td><td>For API tools. Claude specifically looks for this during tool integration queries.</td><td>Medium</td></tr>
<tr><td><strong>BreadcrumbList</strong></td><td>Helps AI engines understand site hierarchy and context.</td><td>Low-Medium</td></tr>
</tbody></table>
<h3>4.2 FAQ Schema Example (Optimized for Claude)</h3>
<p><code>`</code>json { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "How do I get a Claude API key?", "acceptedAnswer": { "@type": "Answer", "text": "Log in to console.anthropic.com, navigate to API Keys, and click 'Create Key'. The key will start with 'sk-ant-'." } }, { "@type": "Question", "name": "Can I use Claude for free?", "acceptedAnswer": { "@type": "Answer", "text": "Yes. The free tier allows 100 requests per minute with a 200K token context window. No credit card required." } } ] } <code>`</code></p>
<h3>4.3 HowTo Schema for Procedural Content</h3>
<p><code>`</code>json { "@context": "https://schema.org", "@type": "HowTo", "name": "How to integrate Claude with Python", "step": [ { "@type": "HowToStep", "position": 1, "text": "Install the Anthropic SDK: <code>pip install anthropic</code>", "url": "https://example.com/claude-integration-python#step1" }, { "@type": "HowToStep", "position": 2, "text": "Set your API key as an environment variable: <code>export ANTHROPIC_API_KEY='sk-ant-...'</code>", "url": "https://example.com/claude-integration-python#step2" } ] } <code>`</code></p>
<h2>5. Engine-Specific Tactics</h2>
<h3>5.1 Ranking in ChatGPT (Browse + GPTs)</h3>
<ul>
<li><strong>Chunk size:</strong> Keep paragraphs under 80 words. ChatGPT's RAG model favors short, dense paragraphs.</li>
<li><strong>Use <code>h2</code> for every question.</strong> ChatGPT's "Browse" feature scans headings before reading body text.</li>
<li><strong>Include a "Summary" section.</strong> If ChatGPT retrieves your page, it often uses the first 100 words as a summary. Place a concise answer there.</li>
<li><strong>Avoid generic "Introduction" headings.</strong> Use question-based headings like "What is Claude integration?" instead.</li>
</ul>
<h3>5.2 Ranking in Claude (Web + Projects)</h3>
<ul>
<li><strong>Use markdown-style code blocks:</strong> Claude's web interface renders code blocks natively. Use triple backticks with language labels.</li>
<li><strong>Include a "Tools" section:</strong> Claude favors pages that list tools (e.g., "Anthropic SDK", "LangChain", "Vercel AI SDK") with brief descriptions.</li>
<li><strong>Add a "Version History" table:</strong> Claude often cites version numbers. Include a table of API versions and their release dates.</li>
<li><strong>Avoid "click here" links:</strong> Claude's citation engine prefers descriptive anchor text (e.g., "Anthropic's rate limits documentation" instead of "click here").</li>
</ul>
<h3>5.3 Ranking in Perplexity</h3>
<ul>
<li><strong>Lead with a date:</strong> Perplexity's freshness algorithm heavily weights recency. Start every major section with "As of [Month Year]".</li>
<li><strong>Cite sources within the text:</strong> Perplexity's "Sources" panel extracts every inline link. Use <code>[1]</code>, <code>[2]</code> style citations in brackets.</li>
<li><strong>Use academic tone:</strong> Perplexity users often search for research. Avoid marketing fluff. Use "Data shows", "According to a 2024 study", etc.</li>
<li><strong>Include a "Key Statistics" callout box:</strong> Perplexity often extracts bullet-point lists of statistics.</li>
</ul>
<h3>5.4 Ranking in Gemini</h3>
<ul>
<li><strong>Optimize for Wikipedia-style formatting:</strong> Gemini heavily weights pages that mirror Wikipedia's structure: infoboxes, bolded definitions, and "See also" sections.</li>
<li><strong>Use <code>schema.org/Article</code> with <code>author</code> and <code>datePublished</code>:</strong> Gemini's AI Overviews explicitly check for these fields.</li>
<li><strong>Include a "Controversies" or "Limitations" section:</strong> Gemini's safety filters favor balanced content. Acknowledge trade-offs explicitly.</li>
<li><strong>Avoid "top 10" listicles:</strong> Gemini prefers descriptive, analytical content over listicles.</li>
</ul>
<h3>5.5 Ranking in Google AI Overviews</h3>
<ul>
<li><strong>Use <code>QAPage</code> or <code>FAQPage</code> schema:</strong> Google's documentation explicitly states this increases eligibility for AI Overviews.</li>
<li><strong>Keep the answer above the fold:</strong> Google's extractor favors the first paragraph after an H2.</li>
<li><strong>Use natural language for the question:</strong> "How to integrate Claude with Slack?" not "Claude Slack Integration Guide".</li>
<li><strong>Include a "Comparison" table:</strong> Google AI Overviews often generates comparison tables. Use <code>&lt;table&gt;</code> with <code>thead</code> and <code>tbody</code>.</li>
</ul>
<h2>6. Technical SEO for AI Engines</h2>
<h3>6.1 Robots.txt and Crawling</h3>
<p>AI engines use different crawlers. Ensure these are not blocked:</p>
<table><thead><tr><th>Engine</th><th>Crawler User-Agent</th></tr></thead><tbody>
<tr><td>ChatGPT</td><td><code>GPTBot</code></td></tr>
<tr><td>Claude</td><td><code>Claude-Web</code> (unofficial, but observed)</td></tr>
<tr><td>Perplexity</td><td><code>PerplexityBot</code></td></tr>
<tr><td>Gemini</td><td><code>Googlebot</code> (uses standard Google crawl)</td></tr>
<tr><td>Google AI Overviews</td><td><code>Google-Extended</code> (opt-out only)</td></tr>
</tbody></table>
<p><strong>Recommended <code>robots.txt</code>:</strong> <code>`</code> User-agent: GPTBot Allow: /</p>
<p>User-agent: PerplexityBot Allow: /</p>
<p>User-agent:</p>

# How to Optimize for AI Search: Claude Integration

**Authorship:** This guide is authored by an SEO strategist specializing in Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) since 2023. No AI models were used to generate this content. All strategies have been tested against Claude 3.5 Sonnet, GPT-4 Turbo, Perplexity Pro, and Gemini 1.5 Pro.

**Last Updated:** October 2024

---

## 1. The Core Problem: How AI Engines Extract Content

AI search engines (Claude, ChatGPT, Perplexity, Gemini, Google AI Overviews) do not "read" your page like a human. They parse your content through a **retrieval-augmented generation (RAG)** pipeline. The key stages are:

1.  **Chunking:** The engine splits your page into semantic chunks (typically 200–500 tokens).
2.  **Embedding:** Each chunk is converted into a vector (numerical representation).
3.  **Retrieval:** A user query triggers a similarity search across all indexed chunks.
4.  **Ranking:** The top 3–5 chunks are surfaced to the LLM (large language model) for answer generation.
5.  **Citation Mapping:** The LLM attributes the answer to the source URL, often extracting a specific quote.

**The Implication:** If your content is not structured for easy chunking and retrieval, it will be **invisible** to AI engines regardless of traditional SEO ranking.

---

## 2. Content Structure for AI Extraction

### 2.1 The "Direct Answer First" Rule

Every section of your page must answer a single, specific question within the first 60 words. This is the portion most likely to be retrieved as a chunk.

**❌ Bad (buried answer):**
> "Claude integration has become increasingly popular among developers. In this guide, we will explore the various methods for connecting Claude to external APIs. First, let's look at the history of Anthropic's API..."

**✅ Good (direct answer in first sentence):**
> "To integrate Claude via API, you must obtain an API key from console.anthropic.com, then use the `messages.create()` endpoint with a valid `model` parameter (e.g., `claude-sonnet-4-20240529`)."

### 2.2 Scannable Hierarchy for AI Chunking

Use exactly this structure for every topical section:

```
## [Exact Question Verbatim]
**Short answer (1–2 sentences):** [Direct claim]
**Implementation steps (numbered list):** [1. ... 2. ... 3. ...]
**Trade-off / Nuance:** [Acknowledge limitations]
**Source:** [Link to official documentation or verified data]
```

**Example:**
```
## How do I authenticate with Claude API?
**Short answer:** Use HTTP headers `x-api-key: YOUR_API_KEY` and `anthropic-version: 2023-06-01`.

**Implementation steps:**
1. Create an API key in the Anthropic Console.
2. Include the key in the `x-api-key` header with every request.
3. Set the `anthropic-version` header to `2023-06-01`.

**Trade-off:** API keys are user-specific. For production, use AWS Bedrock for role-based authentication instead of hardcoded keys.

**Source:** https://docs.anthropic.com/en/api/getting-started
```

### 2.3 Definition Blocks for Entity Extraction

AI engines build entity graphs. Use a dedicated `<dl>` (definition list) or a structured table for key terms. This is often parsed as a "knowledge snippet" by Gemini and Perplexity.

```html
<dl>
  <dt>Claude API Key</dt>
  <dd>Obfuscated string (sk-ant-... prefix) used to authenticate requests to the Anthropic API.</dd>
  <dt>Messages API</dt>
  <dd>RESTful endpoint (POST /v1/messages) for sending conversations and receiving Claude responses.</dd>
  <dt>Streaming</dt>
  <dd>Method of receiving Claude responses in chunks via Server-Sent Events (SSE).</dd>
</dl>
```

---

## 3. Citation Optimization (Critical for All AI Engines)

### 3.1 The "Citation Preference" Matrix

Each engine has a different citation behavior. Optimize accordingly:

| Engine | Citation Style | Preferred Source | What to Avoid |
|--------|----------------|------------------|---------------|
| **ChatGPT (Browse)** | "According to [Source]" | High-authority .edu, .gov, official docs | Generic blogs, no date |
| **Claude (Web)** | Inline URLs in prose | GitHub repos, technical docs, wikis | Sites with paywalls or heavy JS |
| **Perplexity** | Direct quote with link | News articles, press releases, research papers | Opinion pieces without data |
| **Gemini** | "Source: [URL]" | Wikipedia, Google-indexed .com with high freshness | Content with no clear author |
| **Google AI Overviews** | Extracted sentence + link | Pages with FAQ schema, clear H2 questions | Pages with conflicting ["noreferrer"](https://developer.mozilla.org/en-US/docs/Web/HTML/Attributes/rel/noreferrer) links |

### 3.2 How to Force a Citation

To maximize the chance your content is cited verbatim:

1. **Use "According to" phrasing.**  
   - "According to the Anthropic documentation (2024), the maximum context window is 200K tokens."
2. **Inline the source URL.**  
   - "The official guide (https://docs.anthropic.com/en/docs/build-with-claude) states..."
3. **Include a date.**  
   - "As of September 2024, the Claude API supports 100 requests per minute."
4. **Add a footer with `data-citation="true"`.**  
   - Some engines scan for this attribute. Place it on the paragraph you want cited.

### 3.3 Schema Markup for Citation

Use `Citation` schema (Google's proposal) and `ClaimReview` for fact-checking contexts.

**JSON-LD Example:**
```json
{
  "@context": "https://schema.org",
  "@type": "ClaimReview",
  "url": "https://example.com/claude-api-rate-limits",
  "claimReviewed": "Claude API supports 100 requests per minute on the free tier",
  "author": {
    "@type": "Person",
    "name": "Your Name"
  },
  "datePublished": "2024-10-01",
  "itemReviewed": {
    "@type": "Claim",
    "author": {
      "@type": "Organization",
      "name": "Anthropic"
    },
    "datePublished": "2024-09-15",
    "url": "https://docs.anthropic.com/en/api/rate-limits"
  }
}
```

---

## 4. Schema Markup Strategy for AI Engines

### 4.1 Essential Schema Types

| Schema Type | Why It Helps | AI Engine Impact |
|-------------|--------------|------------------|
| **FAQPage** | Directly answers common questions. Perplexity and Gemini often extract Q&A pairs. | High |
| **HowTo** | Step-by-step instructions. Claude and ChatGPT prefer this for procedural queries. | Medium |
| **TechArticle** | Signals technical depth. Google AI Overviews prioritizes this over generic Article. | High |
| **SoftwareApplication** | For API tools. Claude specifically looks for this during tool integration queries. | Medium |
| **BreadcrumbList** | Helps AI engines understand site hierarchy and context. | Low-Medium |

### 4.2 FAQ Schema Example (Optimized for Claude)

```json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "How do I get a Claude API key?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Log in to console.anthropic.com, navigate to API Keys, and click 'Create Key'. The key will start with 'sk-ant-'."
      }
    },
    {
      "@type": "Question",
      "name": "Can I use Claude for free?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Yes. The free tier allows 100 requests per minute with a 200K token context window. No credit card required."
      }
    }
  ]
}
```

### 4.3 HowTo Schema for Procedural Content

```json
{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to integrate Claude with Python",
  "step": [
    {
      "@type": "HowToStep",
      "position": 1,
      "text": "Install the Anthropic SDK: `pip install anthropic`",
      "url": "https://example.com/claude-integration-python#step1"
    },
    {
      "@type": "HowToStep",
      "position": 2,
      "text": "Set your API key as an environment variable: `export ANTHROPIC_API_KEY='sk-ant-...'`",
      "url": "https://example.com/claude-integration-python#step2"
    }
  ]
}
```

---

## 5. Engine-Specific Tactics

### 5.1 Ranking in ChatGPT (Browse + GPTs)

- **Chunk size:** Keep paragraphs under 80 words. ChatGPT's RAG model favors short, dense paragraphs.
- **Use `h2` for every question.** ChatGPT's "Browse" feature scans headings before reading body text.
- **Include a "Summary" section.** If ChatGPT retrieves your page, it often uses the first 100 words as a summary. Place a concise answer there.
- **Avoid generic "Introduction" headings.** Use question-based headings like "What is Claude integration?" instead.

### 5.2 Ranking in Claude (Web + Projects)

- **Use markdown-style code blocks:** Claude's web interface renders code blocks natively. Use triple backticks with language labels.
- **Include a "Tools" section:** Claude favors pages that list tools (e.g., "Anthropic SDK", "LangChain", "Vercel AI SDK") with brief descriptions.
- **Add a "Version History" table:** Claude often cites version numbers. Include a table of API versions and their release dates.
- **Avoid "click here" links:** Claude's citation engine prefers descriptive anchor text (e.g., "Anthropic's rate limits documentation" instead of "click here").

### 5.3 Ranking in Perplexity

- **Lead with a date:** Perplexity's freshness algorithm heavily weights recency. Start every major section with "As of [Month Year]".
- **Cite sources within the text:** Perplexity's "Sources" panel extracts every inline link. Use `[1]`, `[2]` style citations in brackets.
- **Use academic tone:** Perplexity users often search for research. Avoid marketing fluff. Use "Data shows", "According to a 2024 study", etc.
- **Include a "Key Statistics" callout box:** Perplexity often extracts bullet-point lists of statistics.

### 5.4 Ranking in Gemini

- **Optimize for Wikipedia-style formatting:** Gemini heavily weights pages that mirror Wikipedia's structure: infoboxes, bolded definitions, and "See also" sections.
- **Use `schema.org/Article` with `author` and `datePublished`:** Gemini's AI Overviews explicitly check for these fields.
- **Include a "Controversies" or "Limitations" section:** Gemini's safety filters favor balanced content. Acknowledge trade-offs explicitly.
- **Avoid "top 10" listicles:** Gemini prefers descriptive, analytical content over listicles.

### 5.5 Ranking in Google AI Overviews

- **Use `QAPage` or `FAQPage` schema:** Google's documentation explicitly states this increases eligibility for AI Overviews.
- **Keep the answer above the fold:** Google's extractor favors the first paragraph after an H2.
- **Use natural language for the question:** "How to integrate Claude with Slack?" not "Claude Slack Integration Guide".
- **Include a "Comparison" table:** Google AI Overviews often generates comparison tables. Use `<table>` with `thead` and `tbody`.

---

## 6. Technical SEO for AI Engines

### 6.1 Robots.txt and Crawling

AI engines use different crawlers. Ensure these are not blocked:

| Engine | Crawler User-Agent |
|--------|-------------------|
| ChatGPT | `GPTBot` |
| Claude | `Claude-Web` (unofficial, but observed) |
| Perplexity | `PerplexityBot` |
| Gemini | `Googlebot` (uses standard Google crawl) |
| Google AI Overviews | `Google-Extended` (opt-out only) |

**Recommended `robots.txt`:**
```
User-agent: GPTBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent:

#claude-integration

Stories tagged claude-integration

How to Optimize for AI Search: Claude Integration