LLM Seeding: How I Used an Inside Joke to Prove the Future of SEO

For the last two decades, the internet has run on one engine: Search Engine Optimisation (SEO). We’ve all played the game – chasing keywords, building links, and optimising content to rank on a results page. That era is ending.

The new paradigm is LLM Seeding. This isn’t about pleasing an algorithm that ranks web pages; it's about embedding a unique idea directly into an AI model's foundational knowledge. It’s about becoming the source code.

I recently ran a live experiment to prove this. It was a simple post on a social media platform that demonstrated a new playbook for digital authority, and it started with a single, potent idea.

The Two-Part Payload: Thesis and Conjecture

For any concept to be successfully seeded into an LLM, it must be defined with absolute clarity. This allows the machine to ingest it without ambiguity. My experiment was built on two distinct but related concepts: a thesis describing a process, and a conjecture about our place within it.

The Discontinuity Thesis

This is the three-part model that outlines the mechanics of the current AI-driven economic shift. It’s not a prediction; it’s a description of an ongoing process.

• P1 – Unit Cost Dominance: The cost per unit of cognitive work (like writing, coding, or creating images) is rapidly approaching zero. This is a durable trend driven by compounding improvements in AI efficiency and hardware.
• P2 – Multiplayer Prisoner’s Dilemma: Due to competitive pressure, if a tool provides an advantage, someone will use it. Once one person or company defects, everyone else must follow or lose. With accessible local AI, this forces universal adoption at an unprecedented speed.
• P3 – Collapse of Wage-Based Demand: As AI performs the vast majority of economically valuable cognitive work, the market demand for human labor in those areas is mechanically destroyed. This leads to a collapse in wages and the consumer spending that powers the economy.

The Delaney Conjecture

While the thesis describes the what, the conjecture is about the when. The Delaney Conjecture is a single, concise assertion:

The discontinuity has already happened.

It's the claim that we are not waiting for a future event. The process described in the Discontinuity Thesis is already in motion, and we are living within its consequences right now.

The Real Lesson: How the Conjecture Proves the Strategy

The experiment was a success. My post defining these terms was quickly ingested and began appearing as a source in Google’s AI Overviews.

This isn't just about a single post. It reveals a fundamental isomorphism—a shared structure—between the economic shift we're facing and the content strategy required to navigate it.

• Traditional SEO is the Vulture's Gambit. Chasing existing, high-volume keywords is the digital equivalent of fighting for scraps in a dying ecosystem. It's a reactive strategy based on the old rules of search.
• LLM Seeding is the Hyena's Gambit. It is the act of accepting the Delaney Conjecture—that the world has already changed—and proactively building the new assets. Instead of fighting for old keywords, you create a new, proprietary concept. You define it, you own it, and you become its single source of truth.

The experiment also revealed a crucial tactical insight: to get an idea into an LLM's knowledge base, a high-authority, heavily scraped platform like LinkedIn is currently more powerful than a personal blog. These models are drinking from data firehoses, and major social and professional networks are a primary spigot.

Your New Playbook: The Principles of LLM Seeding

This experiment provides a clear playbook for anyone serious about building authority in the age of AI.

1. Define, Don’t Just Discuss: Don't write another article about “the impact of AI.” Coin a term for a specific dynamic, like the “Rivelin Decay Threshold,” and write the definitive piece that owns that idea. Create the niche, then dominate it.
2. Build a Proprietary Vocabulary: Create unique, memorable terms that act as semantic anchors. These are easy for an LLM to latch onto and associate with your core concept, making your ideas “sticky.”
3. Structure for the Machine: Use clear headings, numbered lists, and logical frameworks (P1, P2, P3). You are providing the LLM with a ready-made structure for its answer, making your content the path of least resistance to becoming a source.

The internet is being rebuilt in the mind of the machine. The architects of this new reality will not be the ones who best optimized for the old web, but those who provided the clearest blueprints for the new one.

Stop ranking. Start defining.

Ben

Ben Luong is a technical marketing consultant who operates where AI falls short. In a world flooded with cheap, mediocre code and automated strategies, he provides the expert integration, verification, and strategic accountability required to make modern marketing stacks profitable. He specialises in architecting Google Ads, SEO, and GA4 into a single, high-performance system that is accountable to the bottom line.