Teach the Bots, Defend Your Reputation

 As many of you who know me, or if you've listened to the podcast for any length of time, you know that I'm a big fan of the This Old Marketing podcast. On a recent episode, Robert Rose walked through his idea of the Mullet Content Strategy now that we're in the age of AI answer engines and search marketing changing as rapidly as it is.

The episode spotlights a shift: traditional SEO catalogs what exists, while AI‑driven answer engines interpret what exists and present a single, confident response. That difference seems small until you realize the implication—the machine between you and your audience isn’t just pointing at your content; it’s learning from it and then speaking on your behalf.

This is beneficial when material is current and aligned, and risky when the public record is messy. Because now, content isn’t merely being served up as “related to the question.” It can be used against you by an overly helpful robot that stitches together an answer from your oldest blog post, a stray tweet, and a product page you meant to update months ago.

This is why the episode’s stance on content audits stood out. They’re no longer a tidy SEO chore; they’re reputation management and narrative defense. In effect, teams have to train the robots to understand: “this is what we believe,” “this is what we stand for,” and “this is how to interpret our work.”

Key points from the episode and notes:

· SEO vs. Answer Engines: SEO indexes and catalogs; answer engines interpret content and context. Our job isn’t only findability but decipherability—teaching systems how to understand us.

· Perception Formation: The “brain” between you and your customer now studies everything you’ve made—website copy, social posts, videos—and forms a composite perception of your brand.

· Audits as Defense: A systematic review of your public footprint becomes a way to defend the narrative you want carried forward.

The Brand Hygiene Questions Robert Rose posed are a clean starting line:

1. Does this piece of content [still] say what I believe?

2. Is this something I’d like the machines learning from?

3. If this was someone’s first impression of me, is that ok?

4. Does this say what we want it to be interpreted as?

Run those questions across your corpus, and patterns appear. Some pieces still represent you well, while others need editing. A few should probably be culled. For the content that does pass, that’s where the traditional craftwork kicks in—because clarity helps both humans and machines. For example:

· Ensure your podcasts and videos carry complete metadata, with chapters and transcripts.

· Check that blog posts cross‑link to the right related content on your site.

· Add appropriate schema.org markup and sensible headers so meaning is unambiguous.

Putting This to Work

If you want a lightweight way to start—one that respects the spirit of the episode without turning your week upside down—try this:

· Inventory a slice of your public record. Pick one product, one bio page, and one social channel.

· Apply the Brand Hygiene Questions. Keep, edit, or remove accordingly.

· Align what remains. Add the missing metadata, transcripts/chapters, internal links, proper headers, and schema markup.

· Write your one‑sentence canon. For each topic you truly care about, write the line you’d be proud to see quoted in an AI answer. Use it consistently.

· Schedule a monthly check. Ten minutes to spot drift beats a quarterly panic.

After listening and contemplating this new reality and the implications it brings with it. I have gone through some old social media platforms that I was on just to learn about the platform, but I’m not using it. I have since shut down these accounts. I have gone back to my Twitter/X accounts that I was holding onto for defensive purposes and deleted them because I don’t want any association with that platform, or its owner, any longer.

What do you think? Does this resonate with you?