Understanding LLM Optimisation and Generative AI Search

As generative AI transforms content discovery, understanding how to optimize content for LLMs (Large Language Models) has become crucial for digital visibility. This comprehensive guide explores how LLM SEO, or LLMO (“Large Language Model Optimisation” to coin a phrase) differs from traditional search engine optimisation (SEO) and provides actionable strategies for getting your content into generative AI results. To build this guide I asked the leading LLMs – ChatGPT, DeepSeek, Claude and Google Generative AI a simple prompt “How to optimise written content for LLMs?”. I have de-duplicated their responses aggregated them to form a bullet proof guide. But before we get into that let’s start from the beginning:

What is LLM Optimisation (LLMO)?

LLM optimization (LLMO) represents the next evolution in content strategy, focusing on making content more accessible and understandable for AI language models. Unlike traditional SEO, which prioritizes search engine rankings, LLM optimization ensures your content appears in AI-generated responses from platforms like ChatGPT, DeepSeek, Claude, and Google’s Generative AI.
Key Differences: Traditional SEO vs. LLM Optimisation

Before we get into the nuts and bolts of this, I feel its fair to do a quick refresher on SEO:
Traditional SEO Focus Areas:

Building trustworthy intent focused content
Keyword usage, frequency and placement
Content popularity through back-links
Meta tags optimization
Technical website structure
Search engine crawl-ability

To obtain results in large language models (LLM), search engine optimization (SEO) remains important. If an LLM cannot access and read information, it cannot reference it. Therefore, ensuring our page is crawlable and indexable with basic elements such as meta tags, structured markup (e.g., H1, H2), and schema is crucial for LLMs to access and understand the content.

The lines between SEO and LLMs begin to blur with the principle of E.E.A.T. (Experience, Expertise, Authority, and Trust). E.E.A.T. ensures the content is trustworthy by verifying it is written by an expert with the necessary experience and authority. Unlike traditional SEO, LLMs take this concept further by evaluating the inherent quality and validity of the content and the language used to convey the message, considering factors such as simplicity, comprehensiveness, clarity, accuracy, and relevance. All the AIs share similar priorities:
LLM Optimisation Priorities:

Natural language processing
Contextual relevance
Clear content structure
Comprehensive information
Conversational format