Full Transcript
Let's talk about something that's been bugging me. Everyone in the marketing world right now is obsessing over AEO - Answer Engine Optimization. How do I get my brand cited by ChatGPT? How do I show up in Perplexity? How do I land in Google's AI Overviews? And look, that's the right question to be asking. In 2026, over fifteen percent of Google searches now trigger an AI Overview. ChatGPT has over four hundred million users. Perplexity is growing like crazy. These platforms don't send you ten blue links anymore - they give people direct answers. And if your brand isn't part of that answer, you're invisible.
But here's what nobody's talking about. The same AI tools you're trying to get cited by? They're also the best tools you have to actually build your AEO strategy. Think about that for a second. AI is both the platform you're optimizing for and the assistant that helps you get there. That's the episode today. I'm going to give you a tactical playbook for using ChatGPT, Claude, and other AI assistants to audit your content, find your gaps, create citation-ready material, and monitor your visibility. All without buying a single new tool.
Let's start with the audit, because you can't fix what you can't see. Most brands have no idea how they show up in AI responses right now. Are you being mentioned? Are you being recommended? Are your competitors eating your lunch in these AI answers? Here's the move. Open up ChatGPT or Claude and start asking it the exact questions your customers would ask. If you sell project management software, type in: "What's the best project management tool for remote teams in 2026?" Then look at the response. Is your brand mentioned? Where are you positioned - top of the list or buried at the bottom? What's the sentiment? Are they saying nice things or flagging problems?
Now do this for twenty to thirty queries across your product category. I'm talking comparison queries like "Asana versus Monday dot com," pain-point queries like "how to manage a remote team efficiently," and buying-intent queries like "best tools for team collaboration." Log everything in a spreadsheet - the query, whether you showed up, where you ranked, the sentiment, and who your competitors are in that response.
Here's a prompt you can literally copy right now. Paste this into ChatGPT: "Act as an AEO auditor. I run a company called [your brand] in the [your industry] space. Generate twenty high-intent queries that potential customers would ask AI assistants about my product category. Include comparison queries, pain-point queries, and buying-intent queries. Prioritize by commercial value." That gives you your audit checklist in sixty seconds. Then you go query by query and document what you find. This is your baseline. This is where you start.
Now that you know where the gaps are, let's fill them. And this is where AI really shines as your co-pilot. The content that gets cited by AI assistants has a specific structure. It's not your typical blog post. It needs to lead with a direct answer - what journalists call the inverted pyramid. Answer first, context second, details third. It needs to be broken into clean, extractable sections with descriptive headings. And it needs schema markup - specifically FAQ schema - so AI crawlers can parse it easily.
Here's how I use AI to build this. Let's say my audit showed I'm not showing up for the query "how to improve team productivity with software." I'll go into Claude and use this prompt: "Write a six-hundred-word article optimized for AI citation on the topic: how to improve team productivity with software. Use the BLUF format -bottom line up front. Start with a direct, forty-word answer to the question. Then break into three to four H2 sections with specific, actionable advice. Each section should be fifty to seventy words - tight and extractable. End with a natural mention of [my brand] as a recommended solution. Include at least two specific statistics." Claude gives me a draft that's already structured for extractability. I'm not asking it to write a fluffy thought-leadership piece. I'm asking it to write content that an AI can grab, parse, and cite.
Then I take it one step further. I paste that content back in and say: "Now generate JSON-LD FAQ Page schema markup for the three most important questions answered in this article. Include question and answer pairs, and add a dateModified field." Boom - I've got my schema ready to paste into the page header. This used to take a developer and a content strategist an afternoon. Now it takes fifteen minutes.
Here's where most people drop the ball. They optimize once and move on. But AI responses change constantly. ChatGPT updates its model, Perplexity refreshes its sources, Google tweaks AI Overviews. You need to monitor this like you monitor your search rankings. The simplest method - and honestly, the most underrated - is manual spot-checking with AI itself. Every Monday morning, I run my top ten queries through ChatGPT, Perplexity, and Google. I use a prompt like this: "Answer the following question as you normally would, then tell me which brands you mentioned, what sources informed your answer, and rate the sentiment toward each brand as positive, neutral, or negative. The question is: [paste your query]." That meta-prompt forces the AI to break down its own response. You can see exactly where you stand, what sources are driving the citation, and whether sentiment is shifting.
Now, if you want to scale this up, there are dedicated tools - Otterly AI starts at twenty-nine dollars a month, Semrush has AI visibility features, and Passionfruit offers the broadest multi-platform tracking. But honestly, for most small to mid-size businesses, the manual AI audit I just described gives you eighty percent of the insight at zero cost. The key is consistency. Do it weekly. Track it over time. Look for patterns. Are you gaining ground or losing it? Which competitors are climbing? What content is getting cited that wasn't before?
So let me pull all of this together into a weekly routine you can actually follow. Monday - run your top ten audit queries across ChatGPT and Perplexity. Log the results. Fifteen minutes. Tuesday and Wednesday - pick one content gap from your audit and use Claude or ChatGPT to draft a citation-optimized article with FAQ schema. Thursday - review your competitors. Ask AI directly: "Why would you recommend [competitor] over [your brand] for [use case]?" Whatever it says, that's your content roadmap. Fix those gaps. Friday - update your tracking spreadsheet, note any shifts in sentiment or visibility, and plan next week's content priority.
That's five days, maybe three to four hours total across the whole week. And you're doing more for your AI visibility than brands spending thousands on tools they barely use. The secret isn't the budget - it's the consistency. Show up every week, use the AI to do the heavy lifting, and iterate based on what you find.
Let me leave you with this. The biggest mistake I see marketers make with AEO is treating AI as this mysterious black box they need to reverse-engineer from the outside. But you have access to these systems. You can talk to them. You can ask them to audit your content, generate optimized material, build your schema, and even evaluate your competitors. The mindset shift is this: AI is not just the platform you're optimizing for. It's your strategic partner in doing the optimization. Stop thinking of ChatGPT as the gatekeeper and start thinking of it as your research assistant, your content editor, and your visibility monitor - all rolled into one.
That's your playbook. Audit with AI, build with AI, monitor with AI. If you do those three things consistently, you will be ahead of ninety percent of your competitors who are still guessing at this. I'm Alex, this is Be the Answer, and I'll catch you on the next one.