Quick Start Guide

Fresh

Time to complete: 15 minutes

This guide will help you understand the core concepts and take your first steps toward optimizing for AI-driven discovery.

The Big Picture

┌─────────────────────────────────────────────────────────────────────┐
│                    THE NEW OPTIMIZATION STACK                        │
├─────────────────────────────────────────────────────────────────────┤
│                                                                      │
│   Layer 5: Reinforcement ──► Feedback loops train the stack         │
│        ▲                                                            │
│   Layer 4: Response ──► Where visibility becomes attribution        │
│        ▲                                                            │
│   Layer 3: Reasoning ──► Models assess coherence, validity, trust   │
│        ▲                                                            │
│   Layer 2: Vector & Retrieval ──► Semantic similarity matching      │
│        ▲                                                            │
│   Layer 1: Crawl & Index ──► Foundation (still matters!)            │
│                                                                      │
└─────────────────────────────────────────────────────────────────────┘

Step 1: Understand the Shift

Traditional SEO optimized for pages. GenAI systems optimize for chunks.

Traditional SEO	GenAI Optimization
Crawled, Indexed, Ranked	Chunked, Retrieved, Synthesized
Keyword matching	Semantic similarity
Page-level ranking	Chunk-level retrieval
Link equity	Machine trust signals
Click-through rate	Attribution rate

Step 2: Quick Wins (Do These Today)

1. Structure Content for Chunking

Break your content into logical blocks of 100-300 tokens (roughly 75-225 words).

## Clear Heading That Echoes a Query

One focused idea per section. Use semantic HTML tags.
Lead with the answer. Support with context.

2. Enable AI Crawler Access

Check your robots.txt - ensure these bots are NOT blocked:

# Allow AI crawlers
User-agent: GPTBot
Allow: /

User-agent: Google-Extended
Allow: /

User-agent: CCBot
Allow: /

User-agent: anthropic-ai
Allow: /

3. Add Basic Schema Markup

At minimum, add Organization and Author schema:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://yoursite.com",
  "sameAs": [
    "https://linkedin.com/company/yourcompany",
    "https://twitter.com/yourcompany"
  ]
}
</script>

4. Use Declarative Language

Don't Do This

"We believe this solution might help improve onboarding outcomes."

Do This Instead

"This tool increased onboarding completion by 29% over six months."

Step 3: Choose Your Path

Based on your current situation, pick a path:

Path A: Content Optimization

If you have existing content that needs updating:

1. Read SOP 001 - Content Chunking
2. Read SOP 006 - Embedding-Friendly Content
3. Follow Workflow 001 - GenAI Content Optimization

Path B: Technical Foundation

If you need to fix technical issues first:

1. Read SOP 004 - AI-Crawlable Sites
2. Read SOP 008 - AI Bot Access Setup
3. Read SOP 003 - Schema Markup

Path C: Authority Building

If you need to establish trust signals:

1. Read SOP 002 - E-E-A-T Implementation
2. Read SOP 007 - Author Identity Signals
3. Follow Workflow 002 - Machine Trust Building

Key Concepts to Know

Concept	Definition
Chunk	A modular content block (100-300 tokens) that LLMs retrieve and score
Embedding	Vector representation of content meaning for similarity matching
Retrieval	Process of selecting relevant chunks based on query similarity
E-E-A-T	Experience, Expertise, Authoritativeness, Trustworthiness
Machine Trust	Signals that help AI systems verify and cite your content

Next Steps

1. Audit your site: Use the AI Visibility Audit Workflow
2. Track new metrics: Learn the 12 GenAI KPIs
3. Explore tools: Check the Tool Stack

Need Help?

Use the chat widget in the bottom-right corner to ask questions about any topic in this documentation.