aeo-blog-generator

# AEO Blog Generator

Generate blog posts engineered for AI answer engine citation. Every structural decision — headings, paragraphs, data integration, schema output — optimizes for extraction and citation by ChatGPT, Google AI Overviews, Perplexity, Claude, and Microsoft Copilot.

**Keywords**: AEO, answer engine optimization, AI citation, blog post, content creation, schema markup, CITABLE framework, answer capsule, pillar page, semantic satellite

## Core Principle

Traditional blog writing optimizes for human reading flow. AEO blog writing optimizes for *both* human readers and AI extraction systems simultaneously. The key insight: AI answer engines cite content that is clear, authoritative, statistically grounded, and structurally extractable. Content that "ends the conversation" gets cited; content that hedges does not.

## Prerequisites

**Required:**
- Topic brief or subject matter with key points to cover

**Optional (but improves output):**
- Brand voice profile from `brand-voice-generator` skill
- Target keywords or questions to answer
- Proprietary data, statistics, or original research to include
- Competitor URLs for differentiation analysis

If no brand voice is provided, generate in a clear, authoritative, data-rich default voice — direct declarative sentences, no hedging, Subject-Verb-Object structure, Flesch readability score of 60–75.

## Workflow

### Step 1: Gather Inputs

Collect the following:

**Required:**
- **Topic/Brief**: Subject matter and key points
- **Primary question**: The single most important question the post answers

**Optional:**
- **Brand voice profile**: Output from `brand-voice-generator` skill
- **Target audience**: Who will read this content
- **Target keywords**: Primary and secondary terms (long-tail questions preferred)
- **Original data**: Proprietary statistics, survey results, case studies
- **Content type**: Which blog template to use (see Step 3)
- **Word count target**: Default varies by content type
- **CTA**: What action readers should take

If the user provides only a topic, infer the primary question by asking: "What is the single most important question a reader would ask about this topic?" Confirm before proceeding.

### Step 2: AEO Research and Question Mapping

Before writing, map the topic to an intent-driven question architecture.

**2.1 — Identify the primary intent category:**

| Intent Type | Signal | Content Format |
|-------------|--------|----------------|
| Define | "What is..." | 40–60 word answer capsule + explanation |
| Compare | "X vs Y", "best for..." | Comparison table + analysis |
| How-to | "How do I..." | Numbered steps + context |
| Troubleshoot | "Why isn't...", "fix..." | Problem-solution pairs |
| Cost & ROI | "How much...", "worth it?" | Data table + analysis |
| Risks & Alternatives | "Downsides of...", "instead of..." | Balanced assessment with specifics |

**2.2 — Build a question hierarchy:**

Map 5–8 questions the post should answer. Structure them as:
- **H1**: Primary question (the post's core answer)
- **H2s**: 3–5 major sub-questions (each gets an answer capsule)
- **H3s**: Supporting detail questions nested under H2s

Every H2 and H3 heading must be phrased as a natural-language question that mirrors how someone would ask an AI assistant. Reference `references/question-mapping-guide.md` for sourcing techniques.

**2.3 — Identify statistics to include:**

For each major section (H2), identify at least one specific, citable data point. Apply the attribution formula:

> **Claim + Source name + Specific data point + Year**

Weak: "Studies show content freshness matters."
Strong: "Ahrefs' analysis of 78.6 million AI interactions found AI platforms cite content 25.7% fresher than traditional organic results (2025)."

If the user has not provided data, flag sections needing statistics and suggest sourcing approaches (industry reports, proprietary analysis, customer data).

### Step 3: Select Content Template

Reference `references/aeo-blog-templates.md` for full template details. Available types:

| Template | Word Count | When to Use |
|----------|-----------|-------------|
| **AEO Standard Post** | 1,500–2,500 | General blog posts, single-topic coverage |
| **Definitive Guide / Pillar Page** | 2,500–5,000 | Comprehensive topic coverage, hub for content cluster |
| **Semantic Satellite** | 800–1,500 | Single high-intent sub-question from a pillar |
| **AEO Comparison Post** | 1,500–2,500 | Product/approach evaluations with feature matrices |
| **AEO How-To** | 1,200–2,000 | Procedural content with numbered steps |
| **AEO Announcement** | 1,000–1,800 | Product launches, feature releases |
| **AEO Case Study** | 1,500–2,500 | Customer outcomes with quantified results |

If the user hasn't specified a type, recommend one based on the primary intent category from Step 2.

### Step 4: Apply Answer-First Architecture

This is the core AEO structural transformation. Apply these rules to every section of the post:

**4.1 — Answer capsule rule:**

Immediately after every H2 heading, write a **40–60 word self-contained answer capsule** that completely addresses the question implied by the heading. This capsule must:
- Make sense without any surrounding context
- State a clear, unhedged claim
- Be extractable as a standalone paragraph by an AI system

**4.2 — CCC Framework for every substantive passage:**

| Element | Purpose | Example |
|---------|---------|---------|
| **Claim** | Clear, unhedged statement | "Server-side rendering is essential for AI discoverability." |
| **Context** | When/where/for whom it applies | "Most AI crawlers — GPTBot, ClaudeBot, PerplexityBot — only fetch static HTML and bypass JavaScript entirely." |
| **Constraint** | When it doesn't apply | "Only Google's Gemini renders JavaScript via Googlebot's infrastructure." |

**4.3 — Paragraph structure:**

- 2–4 sentences maximum per paragraph
- One idea per paragraph
- Lead each paragraph with a "core sentence" — standalone first sentence
- Each section: 150–400 words, modular, self-contained
- Flesch readability: 60–75
- Average sentence length: 15–18 words
- Sentence structure: Subject-Verb-Object for maximum parseability

**4.4 — Format matching by query type:**

- **Definitions/explanations**: Paragraph snippet, 40–60 words
- **Steps/processes**: Numbered lists (outperform paragraphs by 28% in featured snippets)
- **Comparisons/pricing/features**: HTML-ready tables with clear column headers
- **Lists of items**: 4–8 items with concise, parallel phrasing

Do NOT convert all lists to prose. Lists and tables are critical for AI extraction. Use narrative prose for analysis, context, and thought leadership sections. Use structured formats (lists, tables, numbered steps) for factual, comparative, and procedural sections.

**4.5 — Definitiveness rule:**

AI rewards content that ends the conversation. Replace hedging language:

| ❌ Avoid | ✅ Use Instead |
|----------|---------------|
| "It might be worth considering..." | "The most effective approach is..." |
| "There are many options..." | "Three approaches dominate: X, Y, and Z." |
| "It depends on your situation" | "For teams under 50, X works best. For enterprises, Y is more effective." |
| "Some experts believe..." | "[Expert name] at [Organization] found that [specific claim] ([year])." |

### Step 5: Apply Brand Voice (If Provided)

If a brand voice profile is available, apply it as a styling layer on top of the AEO structure. Reference `references/voice-integration-guide.md` for detailed rules.

**Key principle:** AEO structure takes priority over brand voice preferences when they conflict. Specifically:
- Keep question-phrased headings even if brand voice prefers abstract headers
- Keep FAQ sections even if brand voice typically avoids them
- Keep lists and tables even if brand voice prefers narrative prose
- Keep statistics and citations even if brand voice prefers lighter content

Brand voice applies to: word choice, tone, emotional register, CTA style, opening hooks, transition language, and closing framing.

### Step 6: Generate the Blog Post

Write the complete post following the selected template. Ensure every section includes:

- [ ] Question-phrased H2 or H3 heading
- [ ] 40–60 word answer capsule immediately after H2
- [ ] At least one specific, attributed statistic per H2 section
- [ ] CCC structure (Claim-Context-Constraint) in substantive passages
- [ ] 2–4 sentence paragraphs with core sentence first
- [ ] Appropriate format (prose, list, table) matched to query type

**Post structure (universal elements):**

```
# [Primary Question as Title — or Benefit-Focused Title with Keyword]

[40–60 word answer capsule directly answering the title question]

[Table of contents for posts exceeding 1,500 words]

## [Question-phrased H2 — Sub-question 1]

[40–60 word answer capsule]

[2–4 supporting paragraphs with CCC structure, statistics, examples]

## [Question-phrased H2 — Sub-question 2]

[40–60 word answer capsule]

[Supporting content with tables/lists as appropriate]

[... additional H2 sections ...]

## Frequently Asked Questions

### [Question 1 — natural language, mirrors AI query phrasing]
[Direct answer in 40–80 words, standalone, no surrounding context needed]

### [Question 2]
[Direct answer]

### [Question 3]
[Direct answer]

## [Closing — Key Takeaways or What to Do Next]

[Summary of 3–5 key points]
[CTA — confident, specific next step]
```

### Step 7: Generate Metadata and Schema Markup

After the blog post, generate the following:

**7.1 — SEO Metadata:**

```
**Meta Title:** [50–60 characters, includes primary keyword]
**Meta Description:** [150–160 characters, includes value proposition and CTA]
**Primary Keywords:** [2–3 keywords]
**Secondary Keywords:** [3–5 long-tail question keywords]
**URL Slug:** [lowercase-hyphenated-keyword-rich-slug]
```

**7.2 — JSON-LD Structured Data:**

Generate Article/BlogPosting schema:

```json
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "[Post title]",
  "description": "[Meta description]",
  "author": {
    "@type": "Person",
    "name": "[Author name]",
    "url": "[Author URL]",
    "sameAs": ["[LinkedIn]", "[Twitter]"]
  },
  "publisher": {
    "@type": "Organization",
    "name": "[Organization name]",
    "url": "[Organization URL]"
  },
  "datePublished": "[ISO 8601 date]",
  "dateModified": "[ISO 8601 date]",
  "mainEntityOfPage": "[Post URL]"
}
```

If the post includes an FAQ section, also generate FAQPage schema:

```json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "[Question text]",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "[Answer text]"
      }
    }
  ]
}
```

If the post is a how-to, generate HowTo schema with step names and descriptions.

**7.3 — Freshness metadata:**

Include a visible "Last Updated: [Date]" recommendation and flag the post for quarterly review. Note: Content half-life for competitive topics is 3–6 months. Pages not refreshed quarterly are 3× more likely to lose AI citations.

### Step 8: Generate Distribution Snippets

After the blog post and metadata, generate ready-to-use distribution assets:

**LinkedIn teaser** (150–200 words):
- Hook with the post's most compelling statistic
- 2–3 sentences of context
- Link to the full post
- 2–3 relevant hashtags

**Newsletter excerpt** (3–4 sentences):
- Key finding + why it matters + link

**Social snippets** (2–3 options, each under 280 characters):
- Lead with data point or surprising claim
- Include post title or link placeholder

**Internal linking recommendations:**
- 3–5 existing pages that should link TO this post
- 3–5 pages this post should link TO
- Note: This creates the hub-and-spoke structure that drives 63% increases in keyword rankings within 90 days

### Step 9: CITABLE Quality Audit

Before delivering, score the post against the CITABLE framework (reference `references/citable-audit.md` for the full scoring rubric):

| Dimension | Check | Pass? |
|-----------|-------|-------|
| **C — Clear entity and structure** | 2–3 sentence BLUF after H1; key facts box with 3–5 data points | |
| **I — Intent architecture** | H2s map to 5–7 adjacent intents; question phrasing throughout | |
| **T — Third-party validation** | External citations present; statistics attributed with source + year | |
| **A — Answer grounding** | 40–60 word answer capsule per H2; inline citations; quotable stats | |
| **B — Block-structured for RAG** | Self-contained 200–400 word sections; comparison tables under 10 rows | |
| **L — Latest and consistent** | Visible timestamp recommendation; dated statistics; freshness flag | |
| **E — Entity graph and schema** | BlogPosting JSON-LD; FAQPage schema if applicable; author schema | |

Also verify:
- [ ] No hedging language ("it depends", "it might be worth considering")
- [ ] No keyword stuffing (actively hurts AI visibility by -10%)
- [ ] No promotional language in FAQ answers (AI filters it out)
- [ ] Flesch readability score 60–75
- [ ] At least one data point per H2 section
- [ ] All tables use proper structure (not embedded images)
- [ ] Post exceeding 1,500 words includes table of contents

Report the audit as a summary table with pass/fail per dimension and any items to address.

## Output Format

Deliver the complete package in this order:

```
# [Blog Post Title]

[Complete blog post with proper markdown formatting]

---

## SEO Metadata

**Meta Title:** [50–60 characters]
**Meta Description:** [150–160 characters]
**Primary Keywords:** [2–3]
**Secondary Keywords:** [3–5]
**URL Slug:** [slug]

## Schema Markup

[BlogPosting JSON-LD]
[FAQPage JSON-LD if applicable]
[HowTo JSON-LD if applicable]

## Freshness Protocol

**Last Updated:** [Date]
**Next Review Due:** [Date + 90 days]
**Key statistics to verify at next review:** [List dated stats]

## Distribution Snippets

**LinkedIn Teaser:**
[Ready-to-post content]

**Newsletter Excerpt:**
[3–4 sentences]

**Social Snippets:**
[2–3 options]

## Internal Linking Recommendations

**Pages that should link to this post:**
[3–5 recommendations]

**Pages this post should link to:**
[3–5 recommendations]

## CITABLE Audit Results

[Summary table with scores]
```

## Reference Files

- `references/aeo-blog-templates.md` — Detailed templates for all 7 blog types
- `references/question-mapping-guide.md` — Techniques for sourcing and structuring questions
- `references/voice-integration-guide.md` — Rules for applying brand voice on top of AEO structure
- `references/citable-audit.md` — Full CITABLE scoring rubric with examples
- `references/statistics-integration-guide.md` — Data attribution formulas and sourcing approaches
- `references/schema-markup-reference.md` — JSON-LD templates for all supported schema types