Screenshots are very welcome. 📸

In 2019 it was about half. Now AI answers the question right on the results page, so for most searches nobody ever reaches your site. That doesn't mean visibility is dead. It means the goal has changed: you need to be the answer, not just a blue link. This is what we cover in The Vanishing Click, the first lesson in the AEO Mindset module. If you haven't gone through it yet, it's in the Classroom now. 💬 Let's make it practical: Pick one of your core keywords, search it on Google, and tell us: 1. Did an AI Overview show up? 2. Were you (or a client) cited in it, or was it a competitor? Drop your results below. Let's see how many of us are already losing the click. 👇

Your AI output is only as good as your prompting habits — before you build a single autonomous agent, get these 6 down first. We talk a lot in here about deploying agents, but the real lever isn't automation, it's clarity. The formula is simple: your leverage from AI = your skill × your clarity. 6 prompting habits worth stealing (full breakdown in the graphic): 1. "Explain this to me Eli 10" — cuts through jargon so you're not stuck in analysis paralysis on a new tool or concept. 2. "Ask me 5 clarifying questions before you answer" — forces the AI to interview you instead of guessing, so you stop getting generic output. 3. Show, don't tell — feed it real examples of work that's actually worked for you. Still more powerful than "make it better." 4. "Save this to memory" / "turn this into a skill" — stop re-explaining the same context every single time. 5. "Find my blind spots and weak assumptions" — your built-in sparring partner for strategy, pricing, and targeting. 6. Loop engineering — give it an exact definition of done so it can self-check instead of you reviewing 10 drafts. The order matters. Dial in habits 1-5 first. Only automate a workflow (habit 6) once you've proven it actually produces results — don't confuse generation with automation. Implementation Task: pick ONE of these you're not using yet, try it today on a real project, and drop what happened in the comments. That's how we all get sharper together 👇

Is this still the most recent AEO tools list https://www.skool.com/aeo/schema-markup-toolbox Thank you

We’re all deep in debates about schema types, markup frameworks, and JSON perfection — what to tag, where to tag it, and how Google parses it. But in the rush to structure everything for AI, we’re overlooking the single most valuable piece of the puzzle: measurement. Traditional analytics was built for clicks. A traffic drop meant something broke. A traffic spike meant a win. But what happens when AI-driven search — Google’s AI Overviews, ChatGPT, Perplexity, voice assistants — answers the question before the user ever clicks? That’s not future tense anymore. It’s the norm. Schema, structured data, and rich snippets are essential — but they’re not the finish line. They’re the instrumentation layer that allows analytics to survive in a zero-click world. Without measurement built into this new technical SEO stack, we’ll know our pages are marked up beautifully but have no idea if they’re being understood or surfaced. And we’ve seen this story before. We once pushed meta tags, H1s, and keyword counts so hard that clients eventually asked: “What’s our return on all this?” That question forced SEO to grow up. It gave birth to analytics — the proof that all that optimization actually worked. Let’s not repeat that cycle. If we don’t evolve measurement alongside schema, we’ll end up right back there: optimized, organized, and unaccountable. So here’s the real challenge: While everyone’s chasing perfect schema syntax, who’s building the dashboards that prove it worked? Clicks used to prove visibility. Now comprehension has to. The brands that measure that shift will own the next era of SEO.