Another Crazy Day in AI: The End of Traditional SEO as We Know It
- Wowza Team
- Oct 30
- 4 min read
Hello, AI Enthusiasts.
It’s that time of week when your brain says “weekend,” but your inbox insists otherwise.
A seasoned entrepreneur talks about the rise of Generative Engine Optimization — a call for content that prioritizes credibility over clickbait as search evolves beyond the traditional keyword game.
Then there’s an AI creative who argues that while machines can process, only people can perceive... and that’s what keeps us essential.
Meanwhile, Google’s latest upgrades to NotebookLM make it less of a note-taker and more of a thought partner.
Weekend mode loading… but the stories don’t stop.
Here's another crazy day in AI:
Generative search and the future of content strategy
Why AI won’t outgrow humanity
NotebookLM gets smarter with goal-based chat
Some AI tools to try out
TODAY'S FEATURED ITEM: The Changing Rules of Online Visibility
Image Credit: Wowza (created with Ideogram)
Are you creating content for people to find, or for machines to recommend?
Bryan Cheung, co-founder and CMO of Liferay, discusses how search visibility is changing as generative tools like ChatGPT, Gemini, and Claude influence how people find and evaluate information. He describes a growing need for content that reflects genuine expertise, credible sources, and clear structure—qualities that help both human readers and language models recognize value.
Cheung refers to this new landscape as Generative Engine Optimization, an approach that moves beyond keywords and focuses on clarity, context, and trust. Drawing insights from CMSWire’s Dom Nicastro and VML’s Luis Fernandez, he highlights how brands can adapt to environments where AI systems curate and summarize content instead of just listing search results.
Points worth noting from the discussion:
Real questions guide discovery. Focusing on the questions audiences actually ask helps align content with how people search and how AI tools process intent.
Structure strengthens visibility. Clean formatting, clear headings, and organized metadata make information easier for both humans and AI systems to interpret.
Authentic expertise earns credibility. Content created by identifiable professionals with real-world experience signals authority and reliability.
Supporting data enhances trust. Referencing studies, surveys, or direct evidence provides verifiable context and reinforces informational depth.
Readable formats help comprehension. Bullet points and short paragraphs make complex ideas easier to follow and improve machine understanding.
Multimodal elements expand context. Pairing text with labeled visuals or videos offers richer insights and supports visibility in visual or generative search.
New metrics are emerging. Mentions within AI-generated summaries or chat responses are becoming new indicators of relevance and brand awareness.
More people are using AI tools as their first stop for information, and that changes how content gets found and evaluated. Cheung's observations about structure, expertise, and authenticity reflect patterns others in the field are noticing too. There's no blueprint yet for how this all plays out—AI systems are still developing, and different platforms handle content differently. But thinking about how these tools assess credibility and usefulness seems like a reasonable place to start, especially when those same qualities also serve human readers well.
Cheung isn't suggesting you abandon everything you know about creating content or chase after algorithmic tricks that might stop working next month. He's pointing out that certain fundamentals—clear writing, verifiable expertise, logical organization—may matter even more now that AI systems are part of how people discover content. Whether you're writing for a search engine, an AI tool, or a person reading directly, those elements tend to hold up.
This walks through several questions worth sitting with. How do you make expertise visible and verifiable? What does good structure look like when both humans and machines need to parse your information? And as AI tools continue to grow in influence, how do you create work that remains useful and discoverable across different platforms? The answers may still be taking shape, but asking the right questions feels like a reasonable starting point.
Read the full article here.
OTHER INTERESTING AI HIGHLIGHTS:
Why AI Won’t Outgrow Humanity
/Andrew Mayne, Artificial Intelligence Creative, Educator, and WSJ Bestselling Author
Andrew Mayne, an AI creative and former OpenAI technologist, argues that fears of AI replacing humans miss the bigger picture. While automation will excel at cognitive and physical tasks, it cannot replicate human networks of trust, empathy, and relevance — the very foundations of culture and economy. Rather than displacing people, Mayne sees AI as a force that amplifies human potential, enabling more meaningful work and creativity if societies focus on adaptation over resistance. The future, he says, belongs not to machines alone, but to humans who learn to work with them.
Read more here.
NotebookLM Gets Smarter with Goal-Based Chat
/Anuja Agrawal, Senior Staff Lead, NotebookLM, on Google Blogs – The Keyword
Google has rolled out major upgrades to NotebookLM, making it a smarter and more goal-driven AI research assistant. The update expands context windows to one million tokens, increases conversation memory sixfold, and improves response quality by 50%. Users can now personalize chats with specific goals, voices, or roles — turning NotebookLM into anything from a research advisor to a creative strategist. With these enhancements powered by Gemini models, NotebookLM evolves from a note-taking companion into a powerful, adaptive research partner.
Read more here.
SOME AI TOOLS TO TRY OUT:
That’s a wrap on today’s Almost Daily craziness.
Catch us almost every day—almost! 😉
EXCITING NEWS:
The Another Crazy Day in AI newsletter is on LinkedIn!!!
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