Aug 26, 2025 · 29m · we-live-to-build
Earned Media Is Still King, But Not for the Reason You Think
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Host Sean Weisbrot interviews PR principal Curtis Spahr to explore how Generative Engine Optimization (GEO) is reshaping digital marketing, emphasizing why authentic human voice and high-credibility earned media remain essential for AI discoverability.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Sean holds 35.6% of the talking time here. How this is scored →
Sean as informed peer 4.6 Guest teaching 4.0 Guest disagreement 1.1 Sean pushing back 1.7
speaking balance: gold is Sean, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 20:34 Curtis dismissing flatter-heavy outreach
Curtis mocks formulaic 'Me Too' pitches that feign flattery, bluntly criticizing outreach that lacks an understanding of journalistic priorities.
Hardest push from Sean ▶ 3:05 Sean questioning pay-to-play algorithm manipulationSean directly challenges the guest's thesis by citing $95 contributor marketplaces for Forbes and Business Insider and asking if paying for placement manipulates AI.
Biggest teaching moment ▶ 2:29 Curtis defining GEO mechanisms and earned media priorityCurtis breaks down what generative engine optimization actually means in plain terms, explaining how AI algorithms prioritize earned journalistic coverage over paid commercials.
Sean holds their own ▶ 16:17 Sean detailing context windows and token degradationSean demonstrates deep technical familiarity by explaining token limits, multi-chat architecture, and context window refreshes across specific LLM platforms.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Sean as informed peer | Guest teaching | Guest disagreement | Sean pushing back | Why |
|---|---|---|---|---|---|---|
| Defining GEO and the Limits of Pay-to-Play PR | 4 | 5 | 1 | 3 | Sean challenges the premise of organic generative engine optimization by asking whether companies can simply purchase algorithmic influence through cheap contributor placements. Curtis explains why modern AI models discount pay-to-play schemes in favor of earned authoritative media. | |
| Measuring Generative Engine Optimization Performance and Tracking Competitors | 4 | 5 | 1 | 3 | Sean pushes on the technical limitations of LLMs digesting video content, asking why models don't directly prioritize video indexation. Curtis admits he is not an LLM engineer while explaining that text and PDFs remain far easier for current systems to ingest. | |
| The Resurgence of Press Releases and Transcripts in AI | 4 | 6 | 1 | 2 | Curtis educates Sean on how press releases and transcripts have experienced a resurgence because LLMs treat them as authoritative structured sources. Sean follows up by asking how an AI-friendly FAQ differs mechanically from a standard website FAQ. | |
| Authenticity and Human Voice in Modern Corporate Comms | 3 | 4 | 2 | 2 | Curtis explains tells like em-dashes that signal AI generation and notes that corporate comms will need human quirkiness to cut through noise. Sean probes whether AI itself can ever make corporate comms sound more human, which Curtis rejects. | |
| Prompt Engineering and LLM Memory Limitations | 6 | 2 | 1 | 1 | Sean demonstrates practical prompt engineering expertise, sharing specific constraint phrases he uses to force LLMs to deliver concise, truthful outputs. Curtis validates this by sharing his own strict parameter prompts. | |
| Multi-Chat Context Windows and Personal Model Preferences | 7 | 3 | 1 | 1 | Sean demonstrates technical knowledge about context windows, token limits, and degradation in long chats, comparing Gemini Pro, ChatGPT, and Grok. Curtis agrees and elaborates on using Claude for translation and draft assembly. | |
| Deconstructing Bad Outreach and the Formula for Great Pitches | 6 | 4 | 2 | 2 | Sean breaks down how he detects lazy AI-generated guest pitches in his inbox and details the exact short-form data he prefers. Curtis relates this to journalistic 'Me Too' pitches and outlines how concise 10-word pitches win. | |
| Why Earned Media Remains King in Generative Engine Optimization | 3 | 6 | 1 | 1 | Curtis lays out the hierarchy of GEO where earned high-domain media is paramount, followed by owned structured content. Sean admits he does not fully grasp all algorithmic mechanics but connects the insight to third-party advice he received. | |
| Platform Specialization and the Brand AI Ecosystem | 7 | 2 | 1 | 2 | Curtis discusses specialized model usage like DeepSeek for developers. Sean counters with his geopolitical skepticism of DeepSeek from living in China, asserting strong model preferences and software architecture knowledge exceeding most peers, which Curtis concedes. | |
| Concluding Thoughts on Humility and Continuous Learning | 2 | 3 | 0 | 0 | Sean wraps up the episode with a broad philosophical closing question. Curtis shares a reflective lesson on remaining humble, continually learning, and not falling for one's own PR. |
Statements from this episode (17)
Spahr: AI search engines prioritize earned media over paid placements
“AI prioritizes the content that is earned by journalists and media outlets that are respected. It also prioritizes media outlets that are very niche and very in the weeds, if you will, but it doesn't really get excited about media outlets that are obviously pa…”
Spahr: Refused thousands of dollars to write paid Forbes contributor articles
“I've been a contributor for Forbes and for others, and I've been asked to do a story for a couple thousand dollars on X, Y, or Z. Now I refused”
Spahr: AI search engines actively penalize pay-to-play PR contributor articles
“AI is hip to that kind of trick, and so that's why those sort of obvious sort of pay to play shenanigans aren't really doing as well.”
Spahr: Generative engine optimization relies heavily on traditional SEO authority metrics
“GEO takes its cues from SEO, and so search engine optimization has a variety of ways of telling just how authoritative a link is and how meaningful it is, and that's the current way in which we're measuring a lot of the generative engine optimization scores, i…”
Spahr: AI systems currently source text significantly more strongly than video
“When it comes to video, AI isn't sourcing that as strongly as it's sourcing written online content, which is easier for it to digest.”
Spahr: Claude, ChatGPT, and Grok cite press releases as authoritative sources
“And we have even seen in some of the answers that we've received back that Claude or ChatGPT or Grok is citing a published press release as an authoritative source of content.”
Spahr: AI-friendly FAQ sections help secure top rankings in generative search
“I think making sure that you have a AI friendly frequently asked questions with answers is another important way in which people can invest in their own online properties and online identities to make sure that you are coming up at the top of any answer.”
Spahr eliminates em-dashes from his content because they signal AI generation
“Now that's just not going to be in my content moving forward because I know it's a tell.”
Spahr: Corporate communications will be forced to sound more human
“People are going to have to sound more human in this age of intense AI, and I think that's going to change the whole field of corporate communications, because right now there's nothing that sounds more robotic than corporate comms, and I think it's going to n…”
Spahr: Persistent user memory will be AI's next major step
“I think the next step of AI is really going to be AI remembering our settings, Because I think the challenge is, is that each time we go into a ChatGPT or Claude or Brock session, it's almost tabula rasa, and it forgets your preferences, it forgets your voice,…”
Weisbrot: ChatGPT retains user memory significantly better than Google Gemini
“ChatGPT is better at storing memory of you”
Spahr: Journalists immediately delete suspected AI pitches from their daily inbox
“And from a media point of view, when journalists see that and they kind of get the sense of, oh, this is AI, they hit delete because journalists are reading to delete. They get about a hundred to 200 pitches each day, and they are just trying to get to the goo…”
Weisbrot: All daily podcast guest pitches he receives are AI-generated
“I get about 10 to 15 pitches a day. A hundred percent of them were written by AI.”
Spahr: Effective PR pitches open with ten words establishing absolute newsworthiness
“I kind of like the pitch that starts off super short, it's about 10 words, and it gives me, this is new, And this is important. And it's compelling enough for me to read the second line. And if it's compelling enough for me to read the second line, I think, ok…”
Spahr: AI platform loyalty will evolve into a Coke versus Pepsi rivalry
“And I think in the future, it's going to become a situation almost like Coke or Pepsi. What kind of guy are you? Are you a Coke guy or a Pepsi guy? Granted, we might have a few more flavors, but I feel that that's going to be kind of the knee jerk reaction abo…”