The daily briefing for AI marketers, growth hackers, and operators.

TL;DR — OpenAI co-founder admits feeling behind despite building these systems. Marketing parallel is direct: the gap between marketers using AI as a feature and marketers orchestrating AI workflows is widening fast. His vocabulary (agents, prompts, contexts, memory, tools, plugins, workflows) maps to marketing ops. The 10X productivity claim requires stringing tools together correctly. Key insight: failure to capture AI leverage is now a skill issue, not access issue. Same tools available to everyone. Competitive advantage shifts to those who build mental models for 'stochastic, fallible' systems. Marketers face identical challenge: learn to orchestrate unreliable-but-powerful AI across content, analytics, automation.

TL;DR — LLMs use the same probability system to explain themselves as they do to answer questions. When you ask 'why did you recommend that?', you get another statistical lottery, not truth. SparkToro tested 100 people asking ChatGPT identical knife recommendation prompts. Almost no two got the same brand list. When asked to explain, ChatGPT fabricated reasoning. Marketers making decisions based on LLM self-explanations are building on false foundations. The only honest answer: 'most likely token based on training data.' Applies directly to anyone using AI for brand tracking, competitor analysis, or content recommendations.

TL;DR — Brand web mentions correlate at 0.664 with AI visibility vs. 0.218 for backlinks. Top 25% brands earn 10x more AI Overview citations. AI search visitors convert at 4.4x traditional organic. 26% of brands have zero AI Overview mentions. Seven tactics: earned media, expert commentary, podcasts, conferences, content partnerships, analyst relations, community participation.

TL;DR — AI Overviews reduce clicks to top-ranking pages by 34.5% (Ahrefs). 60% of searches end without a click (Bain). CTR drops from 15% to 8% when AI Overviews present (Pew). 75% of AI Mode sessions end without external visits. Stop measuring by traffic volume. Track AI citation share across ChatGPT, Gemini, Perplexity.

TL;DR — Average domain age of ChatGPT-cited sources is 17 years. Schema markup moved from nice-to-have to mandatory. AI systems favor entity recognition over keywords and backlinks. Roy's Entity Authority Engineering framework: consistent structured data, mapped citations, multi-model testing.

TL;DR — Early-stage moats are 69% internal (team expertise, product velocity) and 31% external (workflows, data, integrations). Growth-stage inverts to 64% external, 36% internal. Late-stage is 96% external ecosystem. AI makes expertise and features easier to copy. Ecosystems take years to build and are extremely sticky.