How to revise your old content for AI search optimization

If your brand’s content arm has been active for a few years, I’m guessing you have plenty of material that can be revised to help you show up more prominently in AI search answers — we’ll call this AEO throughout the article.

I’m getting bombarded with brand marketers’ questions about how to get AEO traction these days. “Revise your old content” is a favorite answer that often produces an “aha” moment for the other party, possibly because the nature of AEO is so forward-looking.

That answer sparks a few important follow-up questions I’ll tackle below.

How do you reformat content for better AEO performance?

I like to lean on three principles when I tackle content reformatting. Optimizing for:

• Topical breadth and depth.
• Chunk-level retrieval.
• Answer synthesis.

Here’s what that means in practice.

Optimize for topical breadth and depth

Structure your site using a hub-and-spoke model. For each primary category or keyword theme, build a comprehensive hub page that introduces the broader topic and links out to supporting spoke pages that dive deeper into specific facets.

Each spoke page should focus on one clear angle and develop it thoroughly enough to establish distinct purpose and query intent. Because user questions branch in different directions, covering multiple angles helps expand your overall topical reach.

Link related spoke pages to one another where it makes sense, and consistently back to the hub as the central reference point. This reinforces how your content connects and gives AI systems clearer signals about the relationships between topics.

Optimize for chunk-level retrieval

Don’t rely on using the whole page for context. Each chunk should be independently understandable.

Keep passages semantically tight and self-contained. Use one idea per section and keep each passage tightly focused on a single concept — as Our Family Wizard did here:

Optimize for answer synthesis

Summarize complex ideas clearly, then expand with a clearly structured “Summary” or “Key takeaways”. Start answers with a direct, concise sentence. Favor a plain, factual, non-promotional tone.

This formatting, from Baseten, puts an easily digested TL;DR right at the top of a post explaining AI inference:

Dig deeper: How to keep your content fresh in the age of AI

How will humans react to that formatting?

Start with the premise that AI readability is about clarity, not gimmicks, and this approach has tons of appeal to humans looking to quickly understand the content they’re consuming.

AI systems favor content where:

• Answers are named, not inferred.
• Sections have clear intent.
• Key points are easy to lift without rewriting.

That often means being more explicit than traditional SEO ever required — defining terms directly, summarizing sections, and stating conclusions early. It’s kind of the opposite of keyword-stuffed content that’s overwritten to hit assumed “preferences” the Google algorithm might have for content length.

The only real hesitation I have is that content generated by AI may oversimplify nuance. Not every page should be optimized for a single atomic answer, and strategic or opinionated content still benefits from narrative flow.

I try to strike a balance by:

• Explaining first, then elaborating.
• Labeling insights, then proving them.
• Making the answer obvious before adding sophistication.

When done well, this has appeal for both AI and humans.

Now, all of that said, LLM-produced content — just check out your LinkedIn feed if you need examples — very quickly became recognizable as exactly what it is: AI-produced content that’s easily consumed by AI models.

The effect can be very off-putting depending on the reader, even if your content, as it should always strive to do, includes original POVs, research, and or data that the LLMs couldn’t possibly find from existing content.

Keep a close eye out for AI tells, the dreaded em dash, squished vertical line spacing, a bullet-point list featuring emojis, sentence structures like “It’s not just [X]. It’s also [Y].” or “It’s more than [A]. It’s [B].” and removing them wherever you see them. 

Dig deeper: Refreshing content: How to update old content to drive new traffic

How do you prioritize which content to revise?

For AEO, prioritization is less about traffic, which is where a lot of SEO marketers stop KPI-wise, and more about answer value.

I start by identifying content that:

• Contains clear expertise or proprietary insight, which LLMs love.
• Answers questions people ask repeatedly but doesn’t state the answer cleanly.
• Is already referenced internally by sales, support, or customers as “explainer” material.

Also worth noting: Is the content focusing on one of our core products or services, even indirectly? That’s fundamental. Visibility for visibility’s sake isn’t worth much, so make sure it’s got a natural tie-in to pipeline or revenue growth.

As far as types of content to prioritize, reports, tools, and evergreen guides tend to rise to the top because they already contain structured thinking, if not structured answers. AI systems don’t reward originality embedded in prose. They reward explicit conclusions, definitions, and frameworks.

Here’s my simple AEO prioritization test:

• Can an AI model confidently quote or summarize this page as is?
• Would it know what question this page answers within the first few seconds?
• Are the key takeaways labeled or implied?

If the answers are “no,” and the theme of the content is important to your business growth, that content is a strong reformatting candidate.

Dig deeper: How to use AI to refresh old blog content

How do you approach metadata when revising content for AEO?

Before I dive into the how, I’ll mention that these elements have a different function for AEO than they do for SEO. In SEO, they function as ranking levers. In AEO, they serve more as context anchors.

Let’s break down each key element of metadata and show how that difference should play out.

Title tags

Title tags serve as the topic of the page for traditional SEO. For AEO, make them more descriptive about the page’s primary answer or function.

So a title tag that reads “Session replay software” for SEO purposes could be rewritten for AEO to say “Session replay: what it is, when to use it, and when not to use it.” Title tags with more context give AI systems clearer signals about how and when to cite the content.

Headings (H1-H3)

In traditional SEO, header tags have been used to identify categories, for example, “compliance monitoring.”

In AEO, I use them to map to specific questions or claims. Possible updated versions of the above would be:

• What is compliance monitoring?
• Why does compliance monitoring matter for companies in {x} vertical?
• Common issues caused by a lack of compliance monitoring
• When should a CTO invest in compliance monitoring?

To stress-test your header tags, try answering them. If it takes you more than a few sentences to answer your question or prove your assertion clearly and persuasively, it’s probably the wrong question and not one a user is going to type into ChatGPT.

Meta descriptions

Meta descriptions are those chunks of expanded text that might or might not be pulled into the SERP in traditional SEO, but do serve to explain more about the content. In AEO, they act as a compressed intent signal. AI systems, like the SERPs, may choose not to quote the meta description, but good ones help reinforce:

• Who the content is for.
• What problem it resolves.
• How it should be framed.

Through the AEO lens, I look at meta descriptions as a one-sentence briefing note for both users and LLMs.

Dig deeper: Meta tags for SEO: What you need to know

What changes — and what doesn’t — in the shift to AEO

You may have noticed a theme here — while, in general, what’s good for SEO is what’s good for AEO, there are material differences in the two disciplines. Knowing what they are and how to adapt accordingly can pay off in AI search visibility.

I’m not arguing that your content strategy or themes should pivot. But knowing that AI models read and ingest content differently than more traditional SEO algorithms is important and should be factored into the way you’re repurposing your evergreen work from months and years past.