Webinar Recap: 7 High-Level AI Search & AEO Tactics with Steve Toth

In a recent AirOps webinar, Josh Spilker sat down with Steve Toth to break down seven practical tactics for Answer Engine Optimization (AEO), from reasoning journeys and passage retrieval to brand truth and content repurposing.

The main theme stayed clear throughout? Teams need to help Large Language Models (LLMs) understand, retrieve, and accurately recommend their brand.

Top Takeaways

1. Optimize for the reasoning journey, not just keywords.
   Map content to ideal customer profile (ICP)-specific comparisons, integrations, and deal breakers LLMs use to recommend brands.
2. Structure pages for passage retrieval.
   Short, declarative, self-contained paragraphs are easier for LLMs to extract, cite, and reuse.
3. Use fan-out and customer questions to find hidden demand.
   Prompt themes often come from sales calls, support tickets, and community conversations, not keyword tools.
4. Treat brand accuracy as an AEO priority.
   An indexed source-of-truth page helps LLMs reflect your latest features, fit, and differentiators.
5. Expand AEO beyond blog posts.
   Case studies, docs, testimonials, pricing pages, and video can all influence AI citations and recommendations.

Best Practices and Key Learnings

AI tools need clear evidence, not just keyword coverage. Steve's tactics show how SEO teams can shape that evidence across content, product messaging, and proof assets.

Map Content to the Reasoning Journey

LLMs build answers through comparisons, integrations, pricing checks, compliance filters, and ICP-specific needs—not single keyword matches.

When a buyer asks an AI tool for recommendations, the LLM generates sub-queries to validate fit. Your content needs to answer those sub-queries directly. That means creating pages that address comparisons, integrations, compliance requirements, and specific use cases for your ICP.

Key actions to take:

• Audit your core pages around buyer deal breakers like integrations, pricing, compliance, and company fit.
• Add comparison, alternatives, and "who it's for" content that helps an LLM justify why your brand fits a specific buyer.
• Refresh product messaging fast when features change so old forum threads or review posts don't define your brand.

[Insert image asset: buyer prompt → fan-out subqueries → passages → citations → recommendation]

Write Pages for Passage Retrieval

Page length matters less than passage quality. Short, self-contained paragraphs give LLMs cleaner text chunks to extract, understand, and cite.

Think of each paragraph as a standalone answer. LLMs extract passages, not full pages, so every paragraph should make sense on its own. Front-load your clearest answer, then support it with evidence or specifics.

• Keep each paragraph focused on one idea, then support it with evidence, examples, or product specifics.
• Put the clearest answer near the top of the page so retrieval systems find it faster.
• Audit page chunking on high-value URLs to see which details retrieval systems skip.

Find Hidden Demand With Fan-Out and Customer Questions

Keyword tools only show part of the story. The prompts buyers actually ask AI tools come from sales calls, support tickets, help docs, Reddit threads, and community conversations. You can now do Prompt Mining right inside AirOps.

Steve emphasized that traditional keyword research misses the conversational, multi-part queries buyers use with AI search. To find these hidden opportunities, you need to listen to what customers are already asking your team.

• Pull recurring objections, comparison questions, and integration requests from sales and support data every month.
• Group those questions into themes like pricing, compliance, alternatives, and use-case fit.
• Use fan-out patterns to spot where your brand drops out of the reasoning chain.

"Keyword research for LLMs is more like… understanding what's in the customer's mind" — Steve Toth

Build a Source-of-Truth Page for Brand Accuracy

If AI tools misunderstand your product, they can block qualified demand before a buyer reaches your site. A dedicated indexed page gives models one reliable place to find your latest capabilities, differentiators, and fit.

This isn't about gaming the system. It's about making sure LLMs have accurate, current information about what you do, who you serve, and what makes you different. Without this, AI tools may cite outdated information or miss key differentiators.

• Publish a source-of-truth page that explains what you do, who you serve, and what makes you different.
• Update that page whenever you launch a feature, add an integration, change packaging, or expand into a new market.
• Use the page to correct stale narratives that still live in search results, forums, and review sites.

Expand AEO Beyond Blog Posts

AI tools pull proof from more than your blog. Case studies, docs, testimonials, pricing pages, and video often influence recommendations when buyers ask product-specific questions.

Steve pointed out that many high-citation pages aren't traditional SEO assets. Documentation, customer stories, pricing pages, and video content all shape how LLMs understand and recommend your brand. SEO teams need to think beyond the blog.

• Audit non-blog assets that shape decisions, especially customer stories, docs, industry pages, and pricing content.
• Flag missing proof assets for other teams, like a case study for a target vertical or a doc page for a key integration.
• Turn declining informational posts into video briefs, scripts, and clips that answer the same buyer questions in a stronger format.

How Modern SEO Teams Can Put These Tactics Into Practice

AI search rewards brands that explain their fit clearly, publish proof in multiple formats, and keep facts current. That shift pushes SEO teams beyond keyword maps and into deeper work around retrieval, accuracy, and cross-functional content planning.

Start with one focused workflow:

• Pick a small set of high-intent prompts your ICP actually asks
• Map the likely fan-out themes and sub-queries LLMs generate
• Tighten the top passages on your most important pages
• Build the missing proof assets buyers and LLMs both need to see

This isn't about overhauling your entire content library overnight. Start small, test what works, and build repeatable processes that scale.

AEO isn't just SEO with a new label. Teams win when they map content to buyer reasoning, write for retrieval, keep brand facts current, and optimize more than the blog.

How AirOps Helps Modern SEO Teams Act on AEO Insights

AirOps helps teams turn AI search insights into action. You can track prompt visibility, spot citation gaps, refresh key pages, and build repeatable workflows that support both SEO and AEO.

• Monitor prompt visibility, citation trends, and share of voice so you can see where your brand loses ground.
• Build workflows that refresh content, improve internal links, and create new assets from real customer questions.
• Ground every output in brand truth so your content stays accurate as your product, positioning, and proof evolve.

Book a call to see how AirOps helps your team move from insight to execution.