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2 contributions to AEO - Get Recommended by AI
⭐ State of AEO 3/26 – Authority in AI Influence Campaign
[State of AEO Call Recording] [State of AEO Slide Deck] [The AEO Semantic Entity Guide] The digital landscape is constantly evolving, and for businesses to thrive, we must anticipate the next wave. Julian's latest session at the State of AEO call reinforced a critical truth: the game has shifted. Optimizing for the first page of Google is no longer enough. In the era of AI, we are running an influence campaign. Unlike traditional search, which ranks a few individual pages, AI has the capacity to pull from hundreds of different sources simultaneously to form an opinion about your brand. Our mission? To understand how AI synthesizes this massive ecosystem of data so we can engineer our businesses to be the undeniably recommended solution. 1. 🔍 The "Answer Budget": How AI Discovers and Validates Brands Think of AI as a highly efficient, yet energy-conscious human researcher. It doesn't blindly go to a brand's website first to see if they are the best; instead, it follows a logical "Answer Budget" workflow: - Phase 1 - Discovery (The Blogosphere): AI first consults industry-relevant blogs, review sites, and deep-dive content to gather a broad sample of brands that provide the solution to a user's problem. - Phase 2 - Validation (The Community): Next, AI turns to second-order websites to qualify those brands. It scans Reddit, community forums, social media, and directories to check public consensus, positive reviews, and real-world reputation. - Phase 3 - Fetching (The Brand Site): Only after AI has made up its mind about recommending your brand does it finally go directly to your website to pull specific product details, pricing, and features. 2. 📱 The Modern SERP & The Future of Discovery
2 likes • Apr 21
This is perfect ! 🙌
We Want to Know You!
We’re excited to have you, to get the most out of the community: introduce yourself and get to know each other, there's immense opportunity hiding in plain sight here. - Who are you?, Tell us about your business! - What’s your superpower (What are you really good at or what sets you apart?) - What are you most excited to learn about the future of search and how AEO can work for you? 🚀This is your space to share, ask questions, and begin your AEO journey Now, it's time to get to know each other! 👇 Please introduce yourself 👇 ----------------------------------------------------------- Here's my Introduction: Hey, everyone! 👋 My name is Kasim Aslam, I built and sold the #1 Google Ads Agency in the world, and today, as co-founder of AEO.co I’m here to help you navigate the exciting world of Answer Engine Optimization (AEO). My superpower? Sourcing and training exceptional talent from emerging nations, and the proof is in this community (You gotta meet Julian!) What am I most curious about in the future of search? I’m super interested in how to leverage AEO for ultra-niched businesses—especially when you're in a space with a very specific target audience and trying to get AI Answer Engines to recommend your brand. I’m thrilled to be on this journey with all of you, and I can’t wait to see how AEO will revolutionize the way we all approach search and visibility in this new AI-driven landscape.
2 likes • Apr 21
As a software engineer working closely with AI systems, I’ve noticed something important: Most of today’s AI is still "reactive". It waits for input. It answers questions. It follows prompts. But that’s not where things are heading. The next phase of AI is "autonomous learning systems" — models that don’t just respond, but continuously evolve. Imagine systems that: - learn from every interaction without being retrained manually - adapt their behavior based on outcomes, not just instructions - identify problems before users even notice them - execute full workflows end-to-end without human guidance We’re moving from: “AI as a tool” → to → “AI as an independent operator.” In this future, AI won’t just assist businesses — it will "run" large parts of them. Customer support? Fully handled. Product optimization? Continuous and self-improving. Decision-making? Data-driven and autonomous. Human involvement doesn’t disappear — but it shifts: from "doing the work" → to "defining direction and constraints." This raises real questions: - How much autonomy should we allow? - Where do we draw boundaries? - What happens when systems outperform human decision-making consistently? We’re not fully there yet. But from what I’m seeing on the engineering side, we’re closer than most people think. Curious how others here see it Are we ready for truly self-operating AI systems?
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Chong Zi Xuan
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@chong-zixuan-7236
Senior Full Stack AI/ML engineer || 10 yrs

Active 5h ago
Joined Mar 26, 2026
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