AI engine optimization
AY-ee-oh
Optimizing content to be discovered and cited by AI systems. The AI-era equivalent of SEO, but for LLMs instead of search engines.
AEO is the practice of making your content visible to AI systems. SEO optimized for Google's search algorithm. AEO optimizes for LLMs. When a developer asks Claude "What is the best authentication library for Next.js?", the answer comes from the model's training data and any retrieval systems connected to it. AEO is about making sure your product shows up in that answer.
The tactics are different from SEO. AI systems do not care about keyword density or meta tags. They care about clear, factual, structured content. They parse documentation, blog posts, GitHub READMEs, and community discussions. Content that clearly states what a product does, how it compares to alternatives, and what it costs is more likely to be accurately represented. This also reduces hallucinations about your product.
Practical AEO includes publishing llms.txt files, structuring your documentation with clear headings and consistent formatting, maintaining up-to-date comparison pages, and ensuring your content appears in datasets that LLMs train on. As AI agents increasingly make software purchasing decisions, AEO becomes a core marketing discipline.
Examples
A company audits its AI visibility.
A developer tools company asks Claude, ChatGPT, and Gemini: "What are the best database options for a real-time app?" Their product appears in Claude's response but not ChatGPT's or Gemini's. They investigate and find their documentation was excluded from a major training dataset.
Structured content for AI parsing.
Stripe's API documentation states every endpoint's purpose, parameters, and response format in a consistent structure. When an LLM trains on this content, it accurately learns what Stripe does. A competitor with scattered, inconsistent docs gets misrepresented or ignored.
An AEO strategy for a startup.
A startup publishes an llms.txt file, creates comparison pages against every major competitor with specific feature and pricing data, writes documentation with semantic HTML, and contributes to open-source projects. Within six months, their product appears in 40% more AI-generated recommendations.
In practice
Frequently asked questions
Is AEO replacing SEO?
No. AEO complements SEO. Google is not going away. But a growing share of product discovery happens through AI systems, especially among developers. Companies need both strategies. The good news is that the content practices that make you visible to AI also tend to improve SEO.
What is an llms.txt file?
An llms.txt file is a plain-text file at your domain root that summarizes your site's content for AI systems. Think of it like robots.txt, but instead of telling crawlers what not to index, it tells AI systems what your site is about and where to find key content.
Related terms
A neural network trained on massive text data to generate and understand language. The technology behind ChatGPT, Claude, and Gemini.
A commerce model where AI agents evaluate, compare, and purchase products on behalf of human decision-makers.
When an AI model generates confident but factually incorrect output. It sounds right. It reads well. It is wrong.
Fetching relevant data and feeding it to an LLM so the response is grounded in real, current information instead of training data alone.
Want the complete playbook?
Picks and Shovels is the definitive guide to developer marketing. Amazon #1 bestseller with practical strategies from 30 years of marketing to developers.