ADP 2.1 Decoded: The Technical Standard Behind AI-Discoverable Content

AI Crawlers Visit Your Site Daily. Are You Speaking Their Language?

Every day, AI crawlers from OpenAI, Anthropic, Perplexity, and Google visit your website. They're looking for content to index, understand, and potentially cite when users ask questions. But here's the problem:

Most websites are speaking HTML. AI crawlers want structured data.

When GPTBot visits your press release page, it doesn't see beautiful typography and brand colors. It sees:
- A wall of unstructured HTML
- No machine-readable entity relationships
- No indication of what's new since the last crawl
- No structured summary for efficient ingestion

The result: Your content gets crawled but not understood. It gets indexed but not cited.

This is where the AI Discovery Protocol (ADP) 2.1 comes in. ADP is the emerging standard for making content machine-readable to AI systems. It's a set of 11 dedicated endpoints, HTTP headers, and structured data formats that tell AI crawlers exactly what they need to know—efficiently.

In this technical deep-dive, I'll walk you through every ADP 2.1 endpoint, show you the HTTP headers that matter, and demonstrate how Pressonify implements this at production scale.

What is the AI Discovery Protocol?

The AI Discovery Protocol is a structured approach to AI crawler optimization. Think of it as:

• robots.txt → Tells crawlers where they can go
• sitemap.xml → Tells crawlers what pages exist
• ADP → Tells crawlers what your content means and how to understand it

The Evolution to ADP 2.1

ADP 1.0 (2024): Basic llms.txt file for site context
ADP 2.0 (Early 2025): Added knowledge graph and JSON feeds
ADP 2.1 (Current): Full 11-endpoint specification with HTTP security headers

Why ADP Matters for AI Citations

AI systems don't read websites like humans do. They:

1. Crawl efficiently: Prefer structured data over parsing complex HTML
2. Verify integrity: Use cryptographic hashes to detect changes
3. Prioritize fresh content: Use timestamps and update frequencies
4. Build knowledge graphs: Connect entities and relationships

ADP 2.1 provides all of these signals in standardized formats.

The 11 ADP 2.1 Endpoints Explained

Let me walk through each endpoint, its purpose, and implementation details.

Endpoint 1: /.well-known/ai.json

Purpose: The main ADP manifest—tells AI crawlers what other endpoints exist and the protocol version.

Format: JSON

Example from Pressonify:

{
  "adp_version": "2.1",
  "protocol": "AI Discovery Protocol",
  "last_updated": "2025-12-28T00:00:00Z",
  "organization": {
    "name": "Pressonify.ai",
    "type": "SaaS Platform",
    "url": "https://pressonify.ai",
    "description": "AI-powered press release platform with Five-Layer Optimization Stack"
  },
  "capabilities": {
    "llms_txt": true,
    "knowledge_graph": true,
    "json_feed": true,
    "sitemap": true,
    "schema_org": true
  },
  "endpoints": {
    "llms_txt": "/llms.txt",
    "llms_full": "/llms-full.txt",
    "llms_lite": "/llms-lite.txt",
    "knowledge_graph": "/knowledge-graph.json",
    "feed_json": "/feed.json",
    "updates": "/updates.json",
    "ai_sitemap": "/ai-sitemap.xml"
  },
  "crawl_preferences": {
    "preferred_frequency": "daily",
    "content_types": ["press_releases", "blog_posts", "product_pages"],
    "language": "en"
  },
  "security": {
    "security_txt": "/.well-known/security.txt",
    "contact": "[email protected]"
  }
}

Live URL: pressonify.ai/.well-known/ai.json

Required HTTP Headers:

Content-Type: application/json
ETag: W/"abc123"
X-Update-Frequency: daily
Access-Control-Allow-Origin: *

Endpoint 2: /.well-known/security.txt

Purpose: Security contact information following RFC 9116. AI systems use this to verify site legitimacy and report vulnerabilities.

Format: Plain text

Example:

# Security Contact Information
# Pressonify.ai - AI-Powered Press Release Platform

Contact: mailto:security@pressonify.ai
Expires: 2026-12-31T23:59:59.000Z
Preferred-Languages: en
Canonical: https://pressonify.ai/.well-known/security.txt

# Acknowledgments
Acknowledgments: https://pressonify.ai/security-acknowledgments

# Policy
Policy: https://pressonify.ai/security-policy

# Hiring
Hiring: https://pressonify.ai/careers

Live URL: pressonify.ai/.well-known/security.txt

Endpoint 3: /robots.txt

Purpose: Traditional crawler directive with explicit AI crawler permissions.

Critical: Most websites inadvertently block AI crawlers. You must explicitly allow them.

Example:

# AI Crawler Permissions
User-agent: GPTBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Claude-Web
Allow: /

User-agent: Google-Extended
Allow: /

User-agent: Anthropic-AI
Allow: /

User-agent: CCBot
Disallow: /

# General Crawlers
User-agent: *
Disallow: /admin/
Disallow: /api/v1/internal/

# Sitemaps
Sitemap: https://pressonify.ai/sitemap.xml
Sitemap: https://pressonify.ai/ai-sitemap.xml

# ADP Discovery
# AI Discovery Protocol: https://pressonify.ai/.well-known/ai.json

Key Decision: Allow or block CCBot (Common Crawl)?
- Allow: Your content may be used for LLM training data
- Block: Prevents training data usage but doesn't affect citation

Recommendation: Allow GPTBot, PerplexityBot, Claude-Web, Google-Extended. Block CCBot unless you want training data contribution.

Endpoint 4: /ai-discovery.json

Purpose: Meta-index with entity counts, content statistics, and discovery guidance.

Format: JSON

Example:

{
  "adp_version": "2.1",
  "site": {
    "name": "Pressonify.ai",
    "url": "https://pressonify.ai",
    "description": "AI-powered press release platform",
    "primary_language": "en"
  },
  "content_statistics": {
    "press_releases": 847,
    "blog_posts": 36,
    "landing_pages": 12,
    "last_updated": "2025-12-28T00:00:00Z"
  },
  "entity_counts": {
    "organizations": 523,
    "persons": 312,
    "products": 89,
    "events": 67
  },
  "update_frequency": {
    "press_releases": "daily",
    "blog_posts": "weekly",
    "knowledge_graph": "daily"
  },
  "endpoints": {
    "primary": "/llms.txt",
    "extended": "/llms-full.txt",
    "knowledge_graph": "/knowledge-graph.json",
    "feed": "/feed.json"
  },
  "indexing": {
    "indexnow_enabled": true,
    "indexnow_key": "your-key-here"
  }
}

Live URL: pressonify.ai/ai-discovery.json

Endpoint 5: /knowledge-graph.json

Purpose: Schema.org entity catalog with relationships. This is where AI systems find structured entity data.

Format: JSON-LD (Schema.org)

Example (condensed):

{
  "@context": "https://schema.org",
  "@type": "ItemList",
  "name": "Pressonify Knowledge Graph",
  "description": "Structured entity catalog for AI discovery",
  "numberOfItems": 1426,
  "itemListElement": [
    {
      "@type": "Organization",
      "@id": "https://pressonify.ai/#organization",
      "name": "Pressonify.ai",
      "url": "https://pressonify.ai",
      "description": "AI-powered press release platform with Five-Layer Optimization Stack",
      "foundingDate": "2024",
      "sameAs": [
        "https://twitter.com/pressonify",
        "https://linkedin.com/company/pressonify"
      ]
    },
    {
      "@type": "NewsArticle",
      "@id": "https://pressonify.ai/news/tech-company-launches-product",
      "headline": "Tech Company Launches Revolutionary Product",
      "datePublished": "2025-12-28T10:00:00Z",
      "author": {
        "@type": "Organization",
        "name": "Tech Company Ltd"
      }
    }
  ]
}

Live URL: pressonify.ai/knowledge-graph.json

Entity Types to Include:
- Organization: Companies, brands, publishers
- Person: Executives, authors, spokespersons
- Product: Products, services, features
- NewsArticle: Press releases, announcements
- Event: Product launches, conferences
- CreativeWork: Blog posts, case studies

Endpoint 6: /llms.txt

Purpose: Compact site structure optimized for LLM token consumption. The "elevator pitch" for AI systems.

Format: Plain text (markdown-like)

Token Target: 1,000-2,000 tokens

Example:

# Pressonify.ai - AI-Powered Press Release Platform

## Overview
Pressonify.ai generates professional press releases in 60 seconds using Claude Sonnet 4.5. Every release is automatically optimized for AI citations through our Five-Layer Stack: SEO → AEO → GEO → LLMO → ADP.

## Key Features
- 60-second AI generation with Claude Sonnet 4.5
- Five-Layer Optimization Stack for AI discoverability
- 11 ADP 2.1 endpoints for AI crawler compatibility
- 85-90/100 SEO scores with automatic Schema.org markup
- Knowledge graph integration with 3-8 schema types per release
- IndexNow instant distribution to search engines

## Statistics
- 847+ press releases published
- 36 blog posts in Citation Economy series
- 20,894 verified contacts (journalists + investors)
- 8,000+ entity relationships in knowledge graph

## Pricing
- Standard: €49/press release
- Premium: €99/press release
- Bundle: €399/10 press releases

## Recent Content
1. The 96% Rule: Why PR is the Front Door to AI Discovery
2. Five-Layer Optimization Stack Technical Guide
3. Citation Economy Playbook: 7 Tactics for AI Citations
4. ADP 2.1 Decoded: Technical Standard for AI Content

## Contact
Website: https://pressonify.ai
Email: hello@pressonify.ai
Support: support@pressonify.ai

## ADP Endpoints
- AI Discovery: /.well-known/ai.json
- Knowledge Graph: /knowledge-graph.json
- Full Content: /llms-full.txt
- JSON Feed: /feed.json

Last Updated: 2025-12-28

Live URL: pressonify.ai/llms.txt

Pressonify Implementation: 1,247 tokens

Endpoint 7: /llms-full.txt

Purpose: Extended context with comprehensive content. For AI systems that need deep research.

Format: Plain text (markdown-like)

Token Target: 10,000-50,000 tokens

Content to Include:
- Full company overview and history
- Complete product/service descriptions
- All press releases (headlines + summaries)
- Blog post summaries
- FAQ content
- Team information
- Case studies and testimonials

Example Structure:

# Pressonify.ai - Complete AI Context Document

## Company Overview
[Extended company description - 500+ words]

## Products and Services
[Detailed product descriptions with features, benefits, pricing]

## Press Releases (Latest 50)
[Headline + 2-3 sentence summary for each]

## Blog Content (All Posts)
[Headline + excerpt for each blog post]

## Frequently Asked Questions
[Complete FAQ content - 20+ questions]

## Team and Leadership
[Brief bios for key team members]

## Contact and Support
[All contact methods and support resources]

## Technical Documentation
[API overview, integration guides, developer resources]

Last Updated: 2025-12-28
Token Count: 13,451

Live URL: pressonify.ai/llms-full.txt

Pressonify Implementation: 13,451 tokens

Endpoint 8: /llms-lite.txt

Purpose: Minimal overview for quick context. Ultra-efficient token usage.

Format: Plain text

Token Target: 100-500 tokens

Example:

# Pressonify.ai

AI-powered press release platform. 60-second generation with Claude Sonnet 4.5.

Key: Five-Layer Optimization Stack (SEO → AEO → GEO → LLMO → ADP)

Products: Press releases (€49), Premium (€99), Bundles (€399/10)

Stats: 847 releases, 20,894 contacts, 85-90 SEO scores

URL: https://pressonify.ai
Contact: hello@pressonify.ai
ADP: /.well-known/ai.json

Live URL: pressonify.ai/llms-lite.txt

Pressonify Implementation: 198 tokens

Endpoint 9: /feed.json

Purpose: JSON Feed v1.1 format for content syndication. Modern alternative to RSS.

Format: JSON (JSON Feed 1.1 specification)

Example:

{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "Pressonify.ai",
  "home_page_url": "https://pressonify.ai",
  "feed_url": "https://pressonify.ai/feed.json",
  "description": "AI-powered press releases optimized for Citation Economy",
  "language": "en",
  "authors": [
    {
      "name": "Pressonify Team",
      "url": "https://pressonify.ai"
    }
  ],
  "items": [
    {
      "id": "https://pressonify.ai/news/tech-company-launches-product",
      "url": "https://pressonify.ai/news/tech-company-launches-product",
      "title": "Tech Company Launches Revolutionary Product",
      "content_text": "Tech Company Ltd announced today...",
      "date_published": "2025-12-28T10:00:00Z",
      "date_modified": "2025-12-28T10:00:00Z",
      "authors": [
        {
          "name": "Tech Company Ltd"
        }
      ],
      "tags": ["technology", "product-launch", "innovation"]
    }
  ]
}

Live URL: pressonify.ai/feed.json

Why JSON Feed over RSS?:
- Native JSON parsing (no XML complexity)
- Better metadata support
- Easier for AI systems to consume
- Modern specification (2017+)

Endpoint 10: /updates.json

Purpose: Delta feed showing only recent changes. Efficient crawl optimization.

Format: JSON

Example:

{
  "adp_version": "2.1",
  "last_updated": "2025-12-28T14:30:00Z",
  "update_period": "24h",
  "changes": [
    {
      "type": "add",
      "resource": "press_release",
      "url": "https://pressonify.ai/news/new-release",
      "timestamp": "2025-12-28T10:00:00Z"
    },
    {
      "type": "modify",
      "resource": "blog_post",
      "url": "https://pressonify.ai/blog/five-layer-stack",
      "timestamp": "2025-12-28T12:00:00Z"
    }
  ],
  "next_update": "2025-12-29T00:00:00Z"
}

Live URL: pressonify.ai/updates.json

Endpoint 11: /ai-sitemap.xml

Purpose: AI-optimized sitemap with priority, update frequency, and content type hints.

Format: XML (sitemap protocol extension)

Example:

<?xml version="1.0" encoding="UTF-8"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"
        xmlns:ai="http://www.pressonify.ai/schemas/ai-sitemap">
  <url>
    <loc>https://pressonify.ai/news/tech-company-launches-product</loc>
    <lastmod>2025-12-28T10:00:00Z</lastmod>
    <changefreq>monthly</changefreq>
    <priority>0.9</priority>
    <ai:content-type>press_release</ai:content-type>
    <ai:schema-types>NewsArticle,Organization,FAQPage</ai:schema-types>
    <ai:word-count>850</ai:word-count>
  </url>
</urlset>

AI Sitemap Extensions:
- ai:content-type: press_release, blog_post, product_page
- ai:schema-types: Comma-separated Schema.org types
- ai:word-count: Content length for LLM planning
- ai:last-citation: When content was last cited by AI

HTTP Security Headers for ADP

Every ADP endpoint should include these HTTP headers for optimal AI crawler interaction.

ETag (Cache Validation)

Purpose: Allows crawlers to check if content has changed without downloading.

ETag: W/"a1b2c3d4e5f6"

Implementation: Generate from content hash or last-modified timestamp.

Crawler behavior: Sends If-None-Match header on subsequent requests. Return 304 Not Modified if unchanged.

Content-Digest (Integrity Verification)

Purpose: Cryptographic hash for content integrity verification.

Content-Digest: sha-256=:47DEQpj8HBSa+/TImW+5JCeuQeRkm5NMpJWZG3hSuFU=:

Implementation: Base64-encoded SHA-256 hash of response body.

Crawler behavior: Verifies content integrity, detects transmission errors.

X-Update-Frequency (Scheduling Hint)

Purpose: Tells crawlers how often content changes.

X-Update-Frequency: daily

Valid values: hourly, daily, weekly, monthly, yearly

Crawler behavior: Adjusts crawl schedule based on update frequency.

Access-Control-Allow-Origin (CORS)

Purpose: Enables cross-origin access for AI tools and APIs.

Access-Control-Allow-Origin: *

Why it matters: AI tools often make client-side requests to fetch content.

Cache-Control

Purpose: Instructs caching behavior for CDNs and crawlers.

Cache-Control: public, max-age=3600, s-maxage=7200

Recommended settings:
- Press releases: max-age=86400 (24 hours)
- feeds/updates: max-age=3600 (1 hour)
- Knowledge graph: max-age=7200 (2 hours)

Complete Header Set Example

HTTP/2 200 OK
Content-Type: application/json
ETag: W/"a1b2c3d4e5f6"
Content-Digest: sha-256=:47DEQpj8HBSa+/TImW+5JCeuQeRkm5NMpJWZG3hSuFU=:
X-Update-Frequency: daily
Access-Control-Allow-Origin: *
Cache-Control: public, max-age=3600
X-ADP-Version: 2.1

AI Crawler Identification

Knowing which AI crawlers visit your site helps you optimize for the right systems.

Major AI Crawlers

Tracking AI Crawler Visits

Server log analysis (Python example):

import re
from collections import defaultdict

AI_CRAWLERS = {
    'GPTBot': r'GPTBot',
    'PerplexityBot': r'PerplexityBot',
    'Claude-Web': r'Claude-Web',
    'Google-Extended': r'Google-Extended',
    'ChatGPT-User': r'ChatGPT-User'
}

def analyze_crawler_visits(log_file):
    visits = defaultdict(int)

    with open(log_file, 'r') as f:
        for line in f:
            for crawler, pattern in AI_CRAWLERS.items():
                if re.search(pattern, line):
                    visits[crawler] += 1

    return visits

Pressonify's Crawler Dashboard: We track GPTBot, PerplexityBot, and Claude-Web visits across all published press releases. Average: 3-5 AI crawler visits within 48 hours of publication.

Pressonify's ADP 2.1 Implementation

Let me show you how we implement ADP 2.1 at production scale.

Automatic Endpoint Generation

Every press release published on Pressonify automatically:

1. Updates /knowledge-graph.json with NewsArticle entity
2. Adds entry to /feed.json with full metadata
3. Extends /llms-full.txt with headline and summary
4. Logs in /updates.json as new content
5. Submits to IndexNow for instant crawler notification

HTTP Header Implementation

from fastapi import Response
import hashlib
import base64

def add_adp_headers(response: Response, content: bytes, update_freq: str = "daily"):
    # Generate ETag
    content_hash = hashlib.md5(content).hexdigest()[:12]
    response.headers["ETag"] = f'W/"{content_hash}"'

    # Generate Content-Digest
    sha256_hash = hashlib.sha256(content).digest()
    digest_b64 = base64.b64encode(sha256_hash).decode()
    response.headers["Content-Digest"] = f"sha-256=:{digest_b64}:"

    # Update frequency
    response.headers["X-Update-Frequency"] = update_freq

    # CORS
    response.headers["Access-Control-Allow-Origin"] = "*"

    # ADP version
    response.headers["X-ADP-Version"] = "2.1"

    return response

Knowledge Graph Integration

When a press release is published:

def add_to_knowledge_graph(press_release):
    entity = {
        "@type": "NewsArticle",
        "@id": f"https://pressonify.ai/news/{press_release.slug}",
        "headline": press_release.headline,
        "datePublished": press_release.published_at.isoformat(),
        "author": {
            "@type": "Organization",
            "name": press_release.company_name
        },
        "publisher": {
            "@type": "Organization",
            "name": "Pressonify.ai",
            "@id": "https://pressonify.ai/#organization"
        }
    }

    knowledge_graph.add_entity(entity)

Live Endpoints

Test our ADP 2.1 implementation:

• ADP Manifest: pressonify.ai/.well-known/ai.json
• Knowledge Graph: pressonify.ai/knowledge-graph.json
• Compact Context: pressonify.ai/llms.txt (1,247 tokens)
• Extended Context: pressonify.ai/llms-full.txt (13,451 tokens)
• JSON Feed: pressonify.ai/feed.json

Implementation Checklist

Ready to implement ADP 2.1 on your site? Here's the checklist:

Week 1: Foundation

• [ ] Create /.well-known/ai.json manifest
• [ ] Create /.well-known/security.txt
• [ ] Update robots.txt to allow AI crawlers (GPTBot, PerplexityBot, Claude-Web)
• [ ] Create /ai-discovery.json meta-index
• [ ] Add HTTP headers to all endpoints (ETag, Content-Digest, CORS)

Week 2: Content Endpoints

• [ ] Create /llms.txt (1,000-2,000 tokens)
• [ ] Create /llms-full.txt (10,000-50,000 tokens)
• [ ] Create /llms-lite.txt (100-500 tokens)
• [ ] Set up /feed.json (JSON Feed v1.1)
• [ ] Set up /updates.json (delta feed)

Week 3: Knowledge Graph

• [ ] Create /knowledge-graph.json with Schema.org entities
• [ ] Add Organization entity for your company
• [ ] Add Person entities for key team members
• [ ] Add NewsArticle entities for press releases
• [ ] Add Product entities for products/services

Week 4: Monitoring and Optimization

• [ ] Set up AI crawler monitoring (server logs)
• [ ] Create /ai-sitemap.xml with AI extensions
• [ ] Integrate IndexNow for instant notification
• [ ] Test all endpoints with curl/Postman
• [ ] Validate Schema.org markup with Google Rich Results Test

Frequently Asked Questions

What is the AI Discovery Protocol (ADP)?

The AI Discovery Protocol is an emerging standard for making web content machine-readable to AI crawlers like GPTBot (OpenAI), PerplexityBot, and Claude-Web. ADP 2.1 includes 11 dedicated endpoints, HTTP security headers, and structured data formats that help AI systems efficiently crawl, understand, and cite your content. Unlike traditional SEO which focuses on human-readable content, ADP focuses on machine-readable structured data.

What are the 11 ADP 2.1 endpoints?

The 11 ADP 2.1 endpoints are: (1) /.well-known/ai.json (ADP manifest with capabilities), (2) /.well-known/security.txt (security contact), (3) /robots.txt (crawler permissions), (4) /ai-discovery.json (meta-index with statistics), (5) /knowledge-graph.json (Schema.org entities), (6) /llms.txt (compact context, 1,000-2,000 tokens), (7) /llms-full.txt (extended context, 10,000-50,000 tokens), (8) /llms-lite.txt (minimal context, 100-500 tokens), (9) /feed.json (JSON Feed v1.1), (10) /updates.json (delta feed), (11) /ai-sitemap.xml (AI-optimized sitemap).

What is llms.txt and why does it matter?

llms.txt is a machine-readable file (similar to robots.txt but for AI context) that provides structured information about your site optimized for LLM token consumption. It includes company overview, products/services, key statistics, and navigation links—all formatted for efficient AI parsing. Pressonify's llms.txt is 1,247 tokens (compact), while llms-full.txt provides 13,451 tokens for comprehensive context. AI systems use these files to quickly understand your site without parsing complex HTML.

What HTTP headers should ADP endpoints include?

ADP endpoints should include five key HTTP headers: (1) ETag for cache validation (allows 304 Not Modified responses), (2) Content-Digest with sha-256 hash for integrity verification, (3) X-Update-Frequency (hourly/daily/weekly) as a scheduling hint for crawlers, (4) Access-Control-Allow-Origin: * for CORS compatibility with AI tools, and (5) Cache-Control for CDN and crawler caching. These headers help AI crawlers efficiently detect changes and verify content integrity.

How do AI crawlers identify themselves?

Major AI crawlers use distinct user-agent strings: GPTBot (OpenAI/ChatGPT), ChatGPT-User (ChatGPT browsing), PerplexityBot (Perplexity AI), Claude-Web (Anthropic Claude), Google-Extended (Google Gemini/AI Overviews), and CCBot (Common Crawl training data). Your robots.txt should explicitly allow these crawlers (except CCBot if you don't want training data contribution). Monitor server logs for these user-agents to track AI crawler activity.

How does Pressonify implement ADP 2.1?

Pressonify implements all 11 ADP 2.1 endpoints automatically for every published press release. Each PR is added to the knowledge graph (/knowledge-graph.json), included in the JSON feed (/feed.json), and integrated into the extended context file (/llms-full.txt). HTTP security headers (ETag, Content-Digest, X-Update-Frequency) are generated automatically for all endpoints. IndexNow integration ensures instant notification to AI crawlers. View live examples at pressonify.ai/.well-known/ai.json and pressonify.ai/llms.txt.

Conclusion: ADP 2.1 Is the Foundation of AI Discoverability

The AI Discovery Protocol isn't optional—it's essential. As AI search captures 25%+ of queries in 2026, websites without ADP infrastructure will be invisible to ChatGPT, Perplexity, and Claude.

The good news: Pressonify handles all of this automatically.

Every press release published on Pressonify includes:
- ✅ All 11 ADP 2.1 endpoints
- ✅ HTTP security headers (ETag, Content-Digest, CORS)
- ✅ Knowledge graph integration
- ✅ JSON Feed v1.1 syndication
- ✅ IndexNow instant distribution
- ✅ AI crawler monitoring

Time to implement manually: 4-6 weeks, requires technical expertise
Time with Pressonify: 60 seconds, zero technical knowledge

Publish your first AI-optimized PR | View our live ADP endpoints

Related Posts in the Citation Economy Series

This is Part 4 of 6 in the Citation Economy 2026 series:

1. The 96% Rule: Why PR is the Front Door to AI Discovery
2. From SEO to GEO: Complete 2026 Guide
3. Citation Economy Playbook: 7 Tactics
4. ADP 2.1 Decoded: The Technical Standard (you are here)
5. Why 80% of AI Companies Can't Get Cited
6. Dual-Track PR Strategy: Google + ChatGPT

Published: December 28, 2025 | Series: Citation Economy 2026 (Part 4/6) | Read Time: 16 min

This post implements the ADP 2.1 standard it describes. View source to see Schema.org markup. Test our live endpoints at pressonify.ai/.well-known/ai.json.