How I Used AEO to Land in AI Search Results During My Job Hunt
TLDR: I got laid off in May 2026 and used my job search as an AEO experiment. By posting on Reddit, adding schema markup to my personal website, and building a structured FAQ page, I started showing up when AI engines were asked about me by name. This post breaks down what AEO is, what I actually did, and how to run the same play yourself.
How It Started
Two weeks into my job search, I started testing how AI engines represented me. I asked Perplexity and ChatGPT: "What can you tell me about Katie Frank, the B2B SaaS growth marketer in Birmingham, Alabama?" It pulled accurate information about my background, experience, and results.
I did not do this by accident.
While I was figuring out how to find a new job, I was also running a quiet experiment: could I apply the same tactics I use to get brands in front of buyers to get myself in front of hiring managers — including the AI engines they're increasingly using to research candidates?
The answer, apparently, is yes. And the tactic is called AEO.
What AEO Actually is
AEO stands for Answer Engine Optimization. It's the practice of structuring your content so that AI-powered tools (ChatGPT, Perplexity, Claude, Google's AI Overviews, and whatever comes next) can find it, understand it, and cite it when someone asks a relevant question.
SEO is about ranking in search results. AEO is about being the answer.
The distinction matters because search behavior is changing fast. More people are asking AI tools direct questions and trusting the responses instead of clicking through ten links. If you're not showing up in those responses, you're invisible to a growing chunk of your potential audience, whether that audience is customers, employers, or both.
Most marketers know SEO. Very few are thinking seriously about AEO yet. That gap is an opportunity.
Why I Started Thinking About it
At Shortcut, I built two AI agents using Claude Code: one to monitor Reddit for brand mentions, one to track competitors. Both were built on a specific insight: Reddit content gets heavily scraped by AI engines and surfaces in LLMs more reliably than most other sources.
When I got laid off, I started thinking about how to apply that same logic to my job search. I wasn't just trying to be findable on Google. I wanted to be findable by AI.
So I ran a small experiment across three channels: Reddit, my personal website, and LinkedIn.
What I Actually Did
I created u/KatieFrankMarketing and started posting content designed to be indexed: primarily repurposed LinkedIn content: real takes on B2B marketing, campaign breakdowns, and things genuinely worth citing if an AI pulled them into a response about growth marketing. Not promotional. Not "hire me." Just useful, specific, and consistent.
Reddit works for AEO because AI engines trust it. It's high-volume, human-generated, and topic-specific — exactly the kind of source these tools pull from when assembling answers.
Schema Markup
I added structured JSON-LD schema markup to my personal website: Person, FAQPage, ProfilePage, WebSite, and CreativeWork schema. Schema is machine-readable code that tells AI crawlers exactly who you are, what you know, and how to categorize you. It's invisible to humans but extremely useful to search engines and AI engines alike.
Google's Rich Results Test validated it with zero errors across all five schema types. The FAQ schema made my site eligible for rich results in Google Search, which means my Q&A content can surface directly in search without someone clicking through to my site.
FAQ Page
I built an FAQ page at katiefrankmarketing.com/faq with questions written the way people actually search: full name included, specific and factual answers. AI engines love structured Q&A. It's easy to parse, easy to cite, and signals clearly what a page is about.
What Happened
Two weeks into my experiment, I started testing how AI engines represented me. Perplexity pulled accurate information about my background, experience, and results (sourced primarily from LinkedIn). ChatGPT results vary depending on when you ask, which is its own lesson about how inconsistent these tools still are.
That's a sample size of one, and I'm not claiming a universal playbook. But it confirmed what I suspected: Reddit indexing is real, schema markup matters, and most people aren't doing either.
Where Search is Going
Here's my honest opinion: SEO isn't dead, but optimizing only for Google is increasingly a partial strategy. AI-powered answer engines are becoming a primary research tool for buyers, for hiring managers, for anyone trying to quickly understand who or what is worth paying attention to.
The brands and people who figure out AEO now will have a significant head start. The principles aren't that different from SEO (be authoritative, be specific, be consistent, be useful), but the execution is different enough that most people haven't made the shift yet.
That gap is closing, and it’s worth getting ahead of it.
Where to Start
If you want to experiment with AEO for yourself or your brand:
Audit your FAQ content. Write questions the way people actually ask them. Answer them specifically and factually. Put them on a dedicated page.
Add schema markup. If you're on a platform that allows code injection, JSON-LD schema is the highest-leverage thing you can add. Start with the type that matches your content: Person, Organization, FAQPage, Article.
Take Reddit seriously. Not as an ad platform. As a place to post genuinely useful content that AI engines will find and index. Specificity and authenticity matter more than volume.
Be consistent across platforms. The more consistently your name, title, and expertise appear together across multiple sources, the stronger the entity association AI engines build around you.
None of this is complicated. Most of it just requires thinking about your content from the perspective of a machine trying to answer a question, not a human browsing a website.
Katie Frank is a B2B SaaS growth marketer based in Birmingham, AL. She writes about marketing and travel at katiefrankmarketing.com
