This post is part of the Composing Scores series:
- Movement I: Composing Scores: SEO, SMO, AEO, LLMO, AIO
- Movement II: Composing Scores: From Codesheet to Rehearsal
- Movement III: Composing Scores: The Gregius Optimizer Premiere
This site has been officially live in production for a week now. From day one, the priority has been positioning it to be effortlessly discovered, recommended, and cited by modern engines
As content is consumed through entirely new mediums, we must clearly signal where our true brand voice — the ultimate source of truth — resides. To capture this momentum, content should be structurally optimized to cater to both the traditional user experience (UX) and the emerging AI experience (AIX).
This piece examines five optimization dimensions — SEO, SMO, AEO, LLMO, and AIO — and walks through the lightweight architecture we built inside the WordPress block editor to treat discovery as a single, unified responsibility rather than a collection of scattered configurations.
Table of Contents
Balancing traditional web presence with AI/LLM optimization
~13%
of all Google searches now trigger AI Overviews. Large scale dataset tracking revealed a massive 102% surge in AI footprint growth over a two-month period.
80%
of sources cited by AI platforms do not rank in Google’s top organic results. Deep query analysis reveals a massive decoupling from traditional SEO, as engines pull citations from outside the traditional top 10.
~35%
drop in click-through rates occurs when AI summaries appear. An analysis of 300,000 keywords found that top-ranking pages lose significant visibility and traffic to immediate AI overviews.
As the web evolves rapidly, content discovery is expanding beyond traditional search. Instead of managing disjointed configurations, we wanted to see if we could treat Search Engine Optimization, social cards, and AI crawler optimization as a single, unified responsibility. To bring this idea to life, we built lightweight components inside the native WordPress block editor that automatically assign the right data signals behind the scenes, letting us focus only on the context that matters most.
To see how the architecture signals its intent to next-gen engines, we ran a quick check across five core optimizations using DeepSeek and Gemini. We also ran automated tests without full synthesis, but the resulting artifacts aligned perfectly with the manual runs. Here is how the site scored out of the box:
DeepSeek
| Area | Status | Notes |
|---|---|---|
| SEO | ✅ 100% | All essential metadata present. |
| SMO | ✅ 100% | Open Graph + Twitter Card complete. |
| AEO | ⚠️ 90% | FAQ schema excellent. Optional: HowTo for setup guides. |
| LLMO | ⚠️ 95% | /llms.txt + <link rel="help"> – very forward-looking. Verify the file content. |
| AIO | ⚠️ 90% | Same as LLMO. Ensure AI crawlers aren’t blocked at server level. |
Gemini
| Area | Status | Notes |
|---|---|---|
| SEO | ✅ 100% | Indexation mapping verified as clean. All metadata and standard crawlers are perfectly optimized. |
| SMO | ⚠️ 90% | Social configurations are complete, but image dimensions risk awkward visual cropping in feeds. |
| AEO | ⚠️ 90% | Comprehensive FAQ schema is active. The remaining 10% is unlocked when HowTo docs schema goes live. |
| LLMO | ✅ 100% | Programmatic hooks are elite. The clean robots.txt configuration fully secures real-time RAG inclusion. |
| AIO | ✅ 100% | Timestamps, brand nesting, and open AI crawler configurations ensure effortless engine synthesis. |
robots.txt
Web Robots (also known as Web Wanderers, Crawlers, or Spiders), are programs that traverse the Web automatically. Search engines such as Google use them to index the web content, spammers use them to scan for email addresses, and they have many other uses.
https://www.robotstxt.org/
Action filter
if ( ! function_exists( 'starter_output_robots_txt' ) ) {
/**
* Build robots.txt directives for production/public sites.
*
* @filter starter_robots_txt_enabled Disable extra robots.txt directives. Default true.
*
* @param string $output Existing robots output from WordPress.
* @param string $is_public Whether search indexing is enabled.
* @return string
*/
function starter_output_robots_txt( $output, $is_public ) {
if ( '0' === (string) $is_public ) {
return $output;
}
// phpcs:ignore -- Example usage documentation.
// Usage: add_filter( 'starter_robots_txt_enabled', '__return_false' );
if ( ! apply_filters( 'starter_robots_txt_enabled', true ) ) {
return $output;
}
$sitemap = home_url( '/wp-sitemap.xml' );
$rules = <<<ROBOTS
User-agent: *
Disallow: /wp-admin/
Allow: /wp-admin/admin-ajax.php
Sitemap: $sitemap
# Traditional Search & Live RAG Retrieval
User-agent: Googlebot
Allow: /
User-agent: Bingbot
Allow: /
# Conversational & Generative Answer Engines
User-agent: OAI-SearchBot
Allow: /
User-agent: ChatGPT-User
Allow: /
User-agent: PerplexityBot
Allow: /
User-agent: ClaudeBot
Allow: /
User-agent: Claude-Web
Allow: /
# AI Data Model Trainers
User-agent: Google-Extended
Allow: /
User-agent: GPTBot
Allow: /
User-agent: Applebot-Extended
Allow: /
User-agent: Cohere-ai
Allow: /
ROBOTS;
return $rules;
}
add_filter( 'robots_txt', 'starter_output_robots_txt', 10, 2 );
}
Robots.txt Output
User-agent: *
Disallow: /wp-admin/
Allow: /wp-admin/admin-ajax.php
Sitemap: https://gregius.com/wp-sitemap.xml
# Traditional Search & Live RAG Retrieval
User-agent: Googlebot
Allow: /
User-agent: Bingbot
Allow: /
# Conversational & Generative Answer Engines
User-agent: OAI-SearchBot
Allow: /
User-agent: ChatGPT-User
Allow: /
User-agent: PerplexityBot
Allow: /
User-agent: ClaudeBot
Allow: /
User-agent: Claude-Web
Allow: /
# AI Data Model Trainers
User-agent: Google-Extended
Allow: /
User-agent: GPTBot
Allow: /
User-agent: Applebot-Extended
Allow: /
User-agent: Cohere-ai
Allow: /
Open Graph
The Open Graph protocol enables any web page to become a rich object in a social graph. For instance, this is used on Facebook to allow any web page to have the same functionality as any other object on Facebook.
https://ogp.me/
To include specific data pieces, we created custom inspector control components bounded to newly registered postmeta fields.



Open Graph output
<!-- Open Graph -->
<meta property="og:locale" content="en_CA" />
<meta property="og:title" content="Gregius" />
<meta property="og:description" content="The open-source AI orchestration layer for WordPress. Gregius gives you full pipeline control, sovereign AI, and complete telemetry from top to bottom." />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://gregius.com/" />
<meta property="og:site_name" content="Gregius" />
<meta property="og:image" content="https://gregius.com/wp-content/uploads/2026/05/Screenshot-2026-05-14-203956.webp" />
<meta property="og:image:width" content="1853" />
<meta property="og:image:height" content="1302" />
<meta property="og:image:alt" content="Prompts modal edit view" />
<!-- Twitter -->
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:title" content="Gregius" />
<meta name="twitter:description" content="The open-source AI orchestration layer for WordPress. Gregius gives you full pipeline control, sovereign AI, and complete telemetry from top to bottom." />
<meta name="twitter:image" content="https://gregius.com/wp-content/uploads/2026/05/Screenshot-2026-05-14-203956.webp" />
<meta name="twitter:image:alt" content="Prompts modal edit view" />
Schema.org
Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond.
https://schema.org/
To simplify the process, we developed custom inspector control components that make injecting structured data directly from the editor effortless.



Schema.org output
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "Organization",
"@id": "https://gregius.com#organization",
"name": "Gregius",
"url": "https://gregius.com/",
"description": "The Orchestration Layer for AI workflows in WordPress",
"logo": "https://gregius.com/wp-content/uploads/2026/05/gregius-logo-600x600-gradient-vibrant.png",
"sameAs": [
"https://github.com/gregius/",
"https://www.linkedin.com/company/gregius/"
]
},
{
"@type": "WebSite",
"url": "https://gregius.com/",
"name": "Gregius",
"description": "The Orchestration Layer for AI workflows in WordPress",
"potentialAction": {
"@type": "SearchAction",
"target": "https://gregius.com/?s={search_term_string}"
},
"@id": "https://gregius.com#website",
"publisher": {
"@id": "https://gregius.com#organization"
}
},
{
"@type": "WebPage",
"url": "https://gregius.com/",
"headline": "Gregius",
"description": "The open-source AI orchestration layer for WordPress. Gregius gives you full pipeline control, sovereign AI, and complete telemetry from top to bottom.",
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "https://gregius.com/"
},
"publisher": {
"@id": "https://gregius.com#organization"
},
"image": "https://gregius.com/wp-content/uploads/2026/05/Screenshot-2026-05-14-203956.webp",
"dateModified": "2026-05-21T13:55:47+00:00",
"datePublished": "2026-05-15T20:14:37+00:00",
"@id": "https://gregius.com#webpage",
"isPartOf": {
"@id": "https://gregius.com#website"
}
},
{
"@type": "FAQPage",
"@id": "https://gregius.com#faq",
"isPartOf": {
"@id": "https://gregius.com#webpage"
},
"mainEntity": [
{
"@type": "Question",
"name": "Why does Gregius exist?",
"acceptedAnswer": {
"@type": "Answer",
"text": "We are experiencing a structural shift toward agentic web applications, where digital interfaces are shifting from static click-and-scroll pages to conversational, context-aware environments. Gregius exists to provide WordPress operators with an on-premise alternative to control this intelligence layer completely."
}
},
{
"@type": "Question",
"name": "What are the core design principles of Gregius?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Gregius is built on three core principles: data custody, architectural decoupling, and open-source sovereignty. We believe that your website's data is your greatest asset and that its semantic memory, telemetry, and prompt pipelines should remain under your infrastructure control to avoid vendor lock-in."
}
},
{
"@type": "Question",
"name": "Why is a self-hosted AI architecture important right now?",
"acceptedAnswer": {
"@type": "Answer",
"text": "As digital environments evolve, businesses require greater choice in how they manage digital assets and user interactions. By containerizing your intelligence stack within WordPress and your own database, you gain complete visibility into operational costs, clear boundary controls for data privacy, and a stable infrastructure insulated from external vendor changes."
}
},
{
"@type": "Question",
"name": "How does Gregius bridge WordPress with modern AI engineering?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Gregius is crafted at the intersection of two distinct architectural paradigms. It embraces native WordPress systems\u2014such as the Abilities API, WP-CLI, and action/filter hooks, while introducing advanced AI engineering patterns like vectors, telemetry streams, and recursive context compression."
}
},
{
"@type": "Question",
"name": "Why use WordPress as the core orchestration layer?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Powering over 40% of the web, WordPress is a proven, familiar content management hub. Gregius leverages this existing data environment to turn standard site content and metadata into structured, machine-discoverable capabilities. This enables teams to deploy advanced AI workflows natively, using the content backend they already know and manage every day."
}
},
{
"@type": "Question",
"name": "What is the underlying data architecture?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Gregius uses a decoupled dual-layer storage design. WordPress handles your standard content infrastructure and configuration logic, while a secondary PostgreSQL instance runs alongside it as an isolated execution layer for high-fidelity vector operations, semantic search, and embeddings. This split ensures heavy mathematical AI workloads never compromise standard web performance."
}
},
{
"@type": "Question",
"name": "How does Gregius protect against rapid AI model obsolescence?",
"acceptedAnswer": {
"@type": "Answer",
"text": "The platform uses a unified provider registry that decouples application logic from underlying model providers. Connection layers and prompt templates can be dynamically changed without altering code base."
}
},
{
"@type": "Question",
"name": "How should an enterprise think about the Gregius ecosystem?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Think of Gregius as an open, modular stack. Gregius Data provides the foundational infrastructure layer to handle database synchronization, pipeline routing, and basic orchestration. This foundation is completely extensible; your internal development team can use our native action and filter hooks to build custom solutions tailored exactly to your business logic. In fact, this is the exact same methodology we used to extend the platform and build Gregius Intelligence, a premium upgrade layer you can deploy to immediately introduce advanced features like session continuity and editorial curation."
}
}
]
}
]
}
llms.txt
A proposal to standardise on using an
https://llmstxt.org//llms.txtfile to provide information to help LLMs use a website at inference time.
To include specific posts — pages, events, products — we created an inspector control component function bounded to a newly registered postmeta field.

Action filter
if ( ! function_exists( 'starter_default_llms_context_sections' ) ) {
/**
* Add default site-specific context lines for llms.txt.
*
* Remove or replace when packaging for reuse.
*
* @param array $sections Existing context section lines.
* @return array
*/
function starter_default_llms_context_sections( $sections ) {
$defaults = array(
'## Core Architecture',
'- Gives developers full control of AI pipelines natively inside WordPress.',
'- Agnostic database and language model registry integrations.',
'- Full data telemetry control from top to bottom.',
'',
'## Key Specifications',
'- Designed to support the enterprise shift to agentic web applications.',
'- Bridges core WordPress data structures with modern AI engineering protocols.',
'- Features a decoupled dual-layer storage design using PostgreSQL for vector operations alongside native WordPress content infrastructures.',
);
return array_merge( (array) $sections, $defaults );
}
}
add_filter( 'starter_llms_context_sections', 'starter_default_llms_context_sections', 10, 1 );
llms.txt output
# Gregius
> The Orchestration Layer for AI workflows in WordPress
- [Home](https://gregius.com/): The AI Orchestration Layer Gregius is the open-source AI orchestration layer for WordPress that gives you full control of your pipelines. Choose database providers, any language model supported in the registry. Own your intelligence architecture and telemetry from top to bottom. The structural shift to agentic web applications 40% of enterprise applications will embed task-specific […]
## Core Architecture
- Gives developers full control of AI pipelines natively inside WordPress.
- Agnostic database and language model registry integrations.
- Full data telemetry control from top to bottom.
## Key Specifications
- Designed to support the enterprise shift to agentic web applications.
- Bridges core WordPress data structures with modern AI engineering protocols.
- Features a decoupled dual-layer storage design using PostgreSQL for vector operations alongside native WordPress content infrastructures.
## Key Documents
- [Gregius Data](https://gregius.com/gregius-data/): Gregius Data The orchestration layer for AI workflows in WordPress AI interactions are rapidly becoming the default means of navigating…
- [Gregius Intelligence](https://gregius.com/gregius-intelligence/): Gregius Intelligence The continuous improvement layer for AI workflows in WordPress AI platforms are making their best effort to make…
- [On a First Note: Announcing Gregius](https://gregius.com/on-a-first-note-announcing-gregius/): Gregius is officially live. The self-hosted AI orchestration layer for WordPress has reached its Release Candidate phase, bringing complete architecture observability and seamless content mirroring to the next era of the web
Sitemap: https://gregius.com/wp-sitemap.xml
The Path Forward
The ultimate goal of this exercise was not to build another feature-heavy plugin. Instead, the intent was to create a lightweight, pragmatic approach that treats content, search, social, and artificial intelligence as a single, unified responsibility. By building this directly into the site and block editor, creators can seamlessly align the document’s data boundaries to match their intent while editing content in real time.
Our goal is to make this a portable component for anyone needing a lightweight, drop-in implementation. Before packaging it as a standalone plugin, we need to decouple critical pieces by moving the core configurations out of PHP action filters and directly into the WordPress editor UI. This will allow creators to natively tune these three foundational discovery files right from the dashboard:
wp-sitemap.xml: Dynamically handling search and indexation.robots.txt: Managing traditional crawling permissions.llms.txt: Real-time context provisioning for downstream inference.
Taking back control of how our brand identity is parsed, synthesized, and cited is not optional anymore. Navigating the shift from UX to AIX just means building cleaner, more intentional bridges.
The score is set. Comments are open and we would love to hear how you are handling this shift in your own sites.
Frequently Asked Questions
SEO (Search Engine Optimization) targets traditional search rankings; SMO (Social Media Optimization) governs social card previews; AEO (Answer Engine Optimization) structures content for conversational AI snippets; LLMO (Large Language Model Optimization) provisions context for inference-time retrieval; and AIO (AI Optimization) ensures AI crawlers can access and synthesize site content without obstruction.
robots.txt is the first contract a crawler reads. Without explicit Allow: directives for AI-specific user agents like ChatGPT-User, PerplexityBot, ClaudeBot, and OAI-SearchBot, your content remains invisible to conversational and generative answer engines.
robots.txt governs crawling permissions — who can access your site. /llms.txt governs content provisioning — what context you hand to large language models at inference time. Together, they form a two-gate system: permission first, then structured context delivery.
AI Overviews now appear in approximately 13% of all Google searches, with a 102% surge in AI footprint growth recorded over a two-month period. Analysis of 300,000 keywords found that top-ranking pages lose approximately 35% of their click-through rate when AI summaries appear above organic results.
Next Steps
Gregius Optimizer is fully open-source, transparent, and built for modern development workflows.
Available on WordPress.org: Install the plugin directly from the official in the WordPress Plugin Directory.
View on GitHub: You can review, fork, and inspect the entire codebase and core logic over at the repository on GitHub.
Documentation: Read the setup guides and technical documentation below to get started.
- Sitemap – Control which content appears in your XML sitemap
- Robots.txt – Configure crawl directives for search engines and AI bots
- Schema – Add structured data markup to help search engines understand your content
- Social Card – Control how your content appears when shared on social media and in search results.
- LLMs – Optimize your site for AI agents and large language models with an
/llms.txtfile
Photo credit: Arco. Speaking of scores, we were lucky enough to catch this film during a TIFF screening in Toronto and it was incredible. If you need a backdrop while composing your own technical optimization scores, give the soundtrack a listen.





