LLM SEO or now LLMO: How to Write and Optimise Content for Generative AI Results in 2025

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

But the AIs also have their nuances.

How to Write Content for Generative AI

So, I asked the leading AI models to provide their different perspectives on content optimization they had the same priorities, but to my surprise also their own nuances which i have summarised below:

ChatGPT’s Approach to Content Structure

• Keep paragraphs concise
• Use clear headings and subheadings
• Avoid internal references
• Provide complete context

Google’s Generative AI Recommendations

• Focus on conversational tone
• Implement semantic keywords
• Monitor performance metrics
• Consider user intent

Claude’s Content Organization Strategy

• Maintain consistent terminology
• Create clear hierarchies
• Implement proper documentation
• Verify technical accuracy

DeepSeek’s Optimization Guidelines

• Provide explicit context
• Use neutral language
• Consider ethical implications
• Implement feedback loops

As you can see they all differ to some degree, but I feel you can still create and write an article to play into all 4 systems. So here is the best practice guide for writing content for LLMs:

Getting Into Generative AI Results: Best Practices

1. Content Structure Optimization

• Use clear, descriptive headers
• Implement logical content hierarchy
• Break information into digestible sections
• Maintain consistent formatting

2. Language and Keyword Implementation

• Use natural language patterns
• Include relevant semantic keywords
• Maintain consistent terminology
• Provide clear definitions

3. Context and Comprehensiveness

• Offer complete background information
• Include relevant examples
• Define technical terms
• Provide practical applications

Advanced LLM SEO Strategies

1. Contextual Relevance

• Align content with user intent
• Provide comprehensive coverage
• Include related concepts
• Maintain topical authority

2. Content Quality Signals

• Ensure factual accuracy
• Provide unique insights
• Include credible sources
• Maintain consistent quality

3. Structural Optimization

• Implement clear hierarchies
• Use appropriate formatting
• Create logical flow
• Maintain consistency

Measuring LLM Optimization Success

To measure success what should we look for?

Key Performance Indicators

• AI response inclusion rate
• Content accuracy in responses
• Context retention
• User engagement metrics

Proofing the pudding, does LLMO work?

This is all well and good, the AIs have spoken, but does LLMO actually work? To test this I wrote an SEO article (Emojis, Emoticons and SEO: 🎯 Do They Work?) taking into account the guideline outlined by the leading AIs. The results within 2 weeks were pleasantly surprising:

Future of LLM SEO and Content Optimization

As generative AI continues to evolve, successful content strategy will require balancing traditional SEO with LLM optimization. The key is creating content that serves both human readers and AI systems effectively while maintaining natural readability and comprehensive coverage.

Conclusion: Implementing LLM SEO Strategy

To optimize your content for generative AI results:

1. Keep SEO, make sure the content indexes and is read-able
2. Focus on clear, well-structured content
3. Provide comprehensive context
4. Use natural language with strategic keywords
5. Implement consistent formatting
6. Monitor and adjust based on performance

By following these LLM optimization guidelines while maintaining SEO best practices, you can create content that performs well in both traditional search results and generative AI responses.

I hope you enjoyed my guide if you have any further suggestion I would love to hear them in the comments!

FAQs About LLM SEO and Content Optimization

What is LLM optimization?

LLM optimization involves structuring content to be effectively processed and recalled by large language models in generative AI responses.

How does LLM SEO differ from traditional SEO?

While traditional SEO focuses on search engine rankings, LLM SEO prioritizes content clarity, context, and comprehensive coverage for AI understanding.

Can I optimize content for both traditional SEO and LLMs?

Yes, by focusing on high-quality, well-structured content that serves both human readers and AI systems while maintaining natural keyword usage.

How do I know if my content is optimized for LLMs?

Monitor your content’s appearance in AI-generated responses and assess the accuracy and context retention of these responses.