LLM SEO: How to Create Content for AI Search Engines

Over the past few months, LinkedIn and marketing publications have been flooded with headlines like “SEO is dead” or “AI search is the only future that matters.” Statements like these are designed to grab attention — but the reality is still far more grounded.

We don’t believe LLM-powered search is going to replace traditional SEO anytime soon. That said, this way of searching is growing fast, and it’s smart to start accounting for it in your content strategy today.

In addition to optimizing for classic search engines, you now need to structure and write content so that AI can easily understand it, trust it, and use it as a cited source in its answers.

LLM SEO is still a very new field, which means there isn’t a single universal playbook that works every time. Models keep changing, platforms are experimenting, and the world of search is constantly evolving.

Even so, we’re already seeing early patterns and signals that are worth paying attention to.

In this article, we’ll break down what we currently know about LLM SEO — and answer a few of the most common questions marketers ask:

• What is LLM SEO, and how is it different from traditional SEO?

• How do you write content for AI search engines so AI can understand it clearly?

• What increases the chances that AI will use your content as a source?

• What types and formats of content show up most often in AI-generated answers?

What You Need to Know About LLM SEO (The Essentials)

LLM SEO vs. GEO vs. AEO: What’s the Difference?

LLM SEO is an umbrella term for practices that increase the chances your content shows up in AI-generated answers — whether that’s in ChatGPT, Perplexity, or AI-powered search features directly in Google and other engines. You’ll also see the same concept referred to as GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization).

Traditional SEO focuses on ranking higher in search results and earning clicks to your website. LLM SEO shifts the focus: the goal is for your content to become a source AI uses when generating an answer. In other words, AI needs to understand it and consider it trustworthy enough to reference.

This doesn’t replace SEO. A strong technical foundation and high-quality content still matter — but now there’s more emphasis on clarity, structure, and credibility.

What LLM Search Prioritizes: Clarity, Structure, and Trust

If you want your content to show up in AI-generated answers, it helps to think about how LLMs “read” and reuse information. It’s not just about whether a page contains the right keywords anymore. What matters more is whether the information is easy to understand, easy to extract, and credible enough to build an answer around.

In practice, the content that performs best in LLM search consistently follows three principles: clarity, structure, and trust.

Clarity: say things directly

Your writing should be as direct as possible — and free of unnecessary fluff. Ideally, both readers and AI should understand the main point within the first few sentences. The explanation should be specific and easy to apply.

Structure: make your content easy to scan and cite

Well-structured content is not only easier for people to read — it’s also easier for AI tools to extract and combine into an answer. Clear headings, bullet points, short paragraphs, summaries, and FAQ sections all help. The more “modular” your content is, the easier it is for AI to reuse it.

Trust: become a source AI can rely on

LLMs tend to favor information that feels reliable, verifiable, and written by someone who knows what they’re talking about. Brand authority matters here, but so do clear expertise signals — like concrete data, real examples, and transparent sourcing. If your content is vague, generic, or lacks context, the model is more likely to treat it as less trustworthy.

Original Content Has the Upper Hand in AEO

Today, the internet is full of thousands of articles covering the exact same topics — often using the same wording, examples, and conclusions. If your content doesn’t bring anything new to the table, AI tools have no reason to pick your page as a source.

That’s where brands with genuinely original, useful content gain a real advantage. In many cases, you don’t even need a completely new topic — it’s enough to take a familiar one and cover it in a way that’s clearer, more specific, and more actionable than what’s already out there.

One of the most effective ways to stand out is to add your own perspective. Real-life experience, an internal process, a mini case study, or even a small experiment can give your content something competitors usually don’t have.

This can be as simple as a quick test (“we tried two different approaches,” “we compared three solutions”), a framework you use internally, or an honest breakdown of what didn’t work in practice — and why. Even a small experiment, if described clearly and transparently, often provides more value than yet another generic summary that already exists in dozens of versions online.

In practice, the takeaway is simple: you won’t beat competitors by writing the same thing — just longer. Much better results come from clearly defining the problem and explaining it in a way that readers can understand instantly and apply right away.

If you manage to create content that helps people grasp a topic faster than your competitors, you’re not only increasing its value for readers — you’re also increasing the likelihood that AI tools will use it as a trusted source.

Build Visibility Beyond Your Website

Visibility in AI-driven search isn’t built on your website alone. Language models learn from information that appears repeatedly across the web — in different formats, contexts, and sources. That’s why it matters how often (and how) your brand or topic is discussed outside of your own pages.

This is exactly why it makes sense to build a presence where people naturally go to find real experiences and practical answers. That can include platforms like Reddit, YouTube, LinkedIn, Quora, as well as local forums, industry communities, or “best tools for…” comparison articles.

The goal isn’t to publish everywhere. The goal is to show up where your target audience actually spends time — and where conversations around your topic are already happening.

Another advantage is that each channel supports a different type of content. LinkedIn often works best for short, clear observations from real practice. YouTube allows you to go deeper and show things visually with concrete examples. Community discussions reward straightforward, helpful answers without marketing language. And comparison lists or recommendation-style articles help both users and algorithms understand where you fit in the market.

When your brand and your topic appear consistently over time across multiple credible sources, you build something that’s essential for LLM search: context. That broader context makes it easier for AI to understand what you do, who you’re relevant for, and in which situations it makes sense to recommend or cite you.

Reddit in particular has been showing up in search results more and more — even for queries with strong product or practical intent. That’s why it’s worth paying attention to it, whether through meaningful participation in relevant communities or even testing paid options like Reddit Ads.

UGC: When Others Talk About You, AI Listens

In LLM search, what matters often isn’t what you say about yourself on your website — it’s what others say about you elsewhere. Reviews, comments, discussions, and user comparisons give AI tools something brand copy rarely does: real experience.

Users typically describe the situation they were in, why they chose a product or service, what results they got, and where they ran into limitations. That kind of detail makes it much clearer who a solution is best for — and how it compares to alternatives. And that context can be the difference between your brand showing up in the right types of queries, or being ignored entirely.

UGC also reflects the language people actually use when they talk and search. It’s not polished by marketing — but it’s often more accurate and more relatable. That can increase the chances that AI tools will lean on your brand when generating answers, simply because they have access to a clear description of real-world use.

Google AI Overviews: A New Measurement Blind Spot

AI Overviews are showing up in Google more and more often — but Search Console still can’t track them separately. Their impressions get mixed into standard organic data, which is why you might see impressions going up without clicks following, and CTR dropping without a clear explanation.

If you want real visibility in LLM and AI-driven search under control, it’s worth starting to track AI Overviews — either manually for your most important queries, or through automated tracking via external tools or APIs — and monitoring AI Overview presence + source citations.

How Is Your Website Performing in AI Search?

If you want a quick sense of whether AI search engines are showing your brand — or your competitors instead — the best place to start is with a short diagnostic. It can reveal which topics and queries you’re being mentioned for, where you’re missing entirely, and what’s causing the gaps.

That’s why we offer a free introductory AEO website analysis — so you can get clear data and specific recommendations for what to focus on next.

Conclusion: Create Content AI Actually Wants to Cite

AEO will keep evolving, and it’s very likely that some details and best practices will change over the next few months. But the overall direction is already clear: the content that wins is content that’s easy to understand, well-structured, trustworthy, and genuinely useful — not just for search engines, but for people.

At the same time, LLM SEO isn’t a replacement for traditional SEO. A strong technical foundation and high-quality content remain essential. But alongside optimizing for rankings, it’s becoming increasingly important whether your content can earn a place as a source AI tools rely on when generating answers.

If you’re not sure where to start, or you want to review your current content and search visibility, we offer a free consultation. We’ll assess your starting point and recommend next steps based on your goals and available resources.

Frequently Asked Questions

1) What is LLM SEO, and how is it different from traditional SEO?

LLM SEO is the practice of optimizing content for AI-generated search and answers. While traditional SEO focuses mainly on rankings, LLM SEO focuses on whether your content becomes a source AI tools use when generating responses.

2) What do AEO and GEO mean?

AEO (Answer Engine Optimization) focuses on optimizing for “answer-first” search engines that provide direct responses. GEO (Generative Engine Optimization) is used for optimizing content for generative search systems that assemble answers from multiple sources. In practice, these terms often overlap.

3) Does AI search replace traditional SEO?

Not at the moment. Traditional SEO remains important because it supports technical website quality, indexation, and content accessibility. AI search adds another layer — increasingly, your visibility depends on whether your content appears directly inside AI-generated answers.

4) How can I improve my chances of showing up in AI answers?

Clear writing, strong structure, concrete answers, and credibility make the biggest difference. Pages that include definitions, step-by-step guides, FAQs, and verifiable information tend to perform especially well.

5) How can I tell if my website appears in AI search engines?

The simplest way is to test key queries directly in tools like ChatGPT or Perplexity and see whether your website appears as a cited source. For a more accurate picture, an AEO analysis can evaluate visibility across multiple systems and compare your performance with competitors.