Welcome to episode 30 of The GEO Show, the briefing on generative engine optimization, LLM citations, and AI search visibility. Brought to you by GEOforge.
In this episode, Paris Childress, founder of Hop AI and co-founder of GEOforge, covers ten stories from the September 13 brief. The throughline: real AI prompts look like conversations, not SEO keywords.
In this episode:
- 🧭 AirOps Quill AI agent captain
AirOps launched Quill to find AI search gaps, execute changes, measure results, and learn from prior runs. Asana +93% ChatGPT citations in two weeks; Parallel +165%. Complex GEO tools need an agent captain (GEOforge's equivalent: Veck). - 📉 Reddit ChatGPT citations hit zero after robots.txt
BrightEdge fixed US education panel: Reddit ChatGPT citation presence 17%→3%→0% over two weeks after a robots.txt change. Timing supports the mechanism, not proven causation. Steeper than AI Overviews. Access policy can erase visibility without content changes. - 💬 Zero-citation answers can still recommend brands
Ospia: ChatGPT returned zero citations on 12/20 answers yet named a vendor in 13/20. Gemini median 47 annotations; Perplexity 20. Mentions ≠ citations. Mentions are the GEO prize and get heavier weight in share of voice. - 🔌 Google partner-only full web search API
JSON REST/gRPC full web search for approved partners (docs surfaced Sep 11). Eligibility/pricing unclear. Search as programmable agent infrastructure. - 📈 LinkedIn jumps in Meltwater AI citation rankings
~7.3M citations / 8 platforms. LinkedIn +25% MoM to 100.2k; Perplexity alone 69,302 LinkedIn citations. Earned/news 33%→29%. Facebook −30%, Instagram −43%. Supports B2B LinkedIn article strategy (GEOforge Daily). - 🛰️ Context7 agent access tracking
Docs7 tracks visits from OpenAI, Claude, Perplexity, Cursor, OpenCode, Meta, Mistral, plus WebMCP SearchDocs separately. Agent request ≠ citation or final-answer use. - 🧠 THROUGHLINE: Real prompts aren't keywords
What If Web: 300 New Zealanders / 1,200+ self-reported prompts. Median 9–14 words. <10% keyword-like. One survey: only 2% named a brand. Directional (self-reported, 3 categories) but keyword→prompt volume extrapolation is the wrong model. - 🔍 95% of consumers verify AI search results elsewhere
Trade Desk / PA Consulting: 95% double-check AI results; 1.6× more likely to purchase on the open internet than via AI tools (3,000 US/UK). Lack of solution links in answers drives verification searches. - ⚖️ A-vs-B brand-first bias fails replication
Ospia: 102 AI Overview queries / 16 brand pairs. Word order changed recommendation in 0/16. First brand first 49% (coin toss). Query phrasing and surface mattered more. - 📊 Profound Sheets Templates — agents at spreadsheet scale
Sep 11 launch. Thousands of agents in parallel. Templates: translation, refresh, GEO FAQs, internal linking, briefs, PDP. Analytics→execution via narrow task agents (same architecture direction as GEOforge).
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💬 Question: If your prompt discovery still starts from keyword volume, what do you think you are measuring?