As AI search grows, should brands and publishers keep investing in SEO or shift to answer-engine optimization?
The strongest shared view is not to abandon SEO, but to treat it as the technical and editorial foundation for answer-engine optimization while selectively adding GEO, social, and citation-focused tactics.
63,407Words analyzed
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5h 25mAudio distilled
Summary
Across the excerpts, most voices reject a clean “SEO versus answer engines” tradeoff. They argue that brands and publishers should keep investing in SEO fundamentals because AI answer engines still depend on crawlable, authoritative, structured web and social content, while the payoff and ownership of newer GEO tools remain uncertain.
Keep SEO as the backbone, then adapt it for AI answers
- Anthony Casalena’s view is that even as users move toward chatbots, websites remain crucial because answer engines use them as source material; this supports continued investment in authoritative, updated, well-structured sites.
- Sandy Diao explicitly rejects the idea that SEO is dead, arguing that crawlability, structured data, user experience, and editorial content are still the signals both Google and generative engines need.
- Eric Sheridan’s data-driven stance reinforces a hybrid strategy: traditional search monetization has not collapsed, so optimizing only for AI-generated answers would be premature.
Answer-engine visibility is becoming a real marketing surface
- Rory’s bull case treats GEO as a pressing enterprise need because marketing leaders feel pressure to appear in AI-generated answers, even before the channel has fully measurable conversion data.
- Gary Vaynerchuk broadens the optimization problem beyond websites: social creative now influences how LLMs perceive and cite brands, so social content becomes part of answer-engine strategy.
- Aravind-Srinivas frames answer engines as a distinct search paradigm that reduces user effort by directly answering and citing sources, especially for informational queries.
The strategic uncertainty is timing, measurement, and platform control
- Jason’s bear case says some current GEO products may be unactionable and vulnerable to churn, especially if LLM platforms absorb the optimization layer themselves.
- Eric Sheridan cautions that AI query behavior could change in the long term, but current evidence still favors serving Google’s commercial search demand while preparing for answer-engine growth.
- The role of AEO or GEO depends on query type: answer engines may be most compelling for informational queries, while commercial-intent search remains economically important today.
Brands and publishers should keep investing in SEO, but evolve it into a broader answer-engine and citation strategy rather than treating AEO or GEO as a replacement.
Traditional SEO inputs—crawlability, structure, authority, site quality, and editorial usefulness—remain necessary because AI answer engines rely on indexed source material.
3 podcasts
There is disagreement over whether current GEO tooling is already a durable marketing category or an immature, potentially short-lived layer.
Rory sees enterprise demand for AI-answer visibility as urgent enough to justify GEO investment now.
1 podcasts
How far to shift toward answer-engine optimization depends on query type, social presence, measurement maturity, and whether AI interfaces start displacing commercial search.
For informational queries, answer engines may reduce friction and become highly influential because they synthesize and cite answers directly.
2 podcasts
Evidence & Sources
Advice Line with Anthony Casalena of SquarespaceHow I Built This with Guy Raz
“Anthony Casalena notes that while users are shifting from traditional search to chatbots, websites remain crucial because answer engines use them as source material. Effective AIO requires ensuring a site’s content is authoritative, well-structured, and frequently updated so that it can be indexed and cited as the definitive answer.”
6:49
20Growth: How to Build a Paid Marketing Machine: ROAS (Return on Ad Spend) 101 | The Rise of User Generared Content and How to Use It | TikTok Ads: Expectations vs. Reality | Hiring for Growth: When and Who with Sandy DiaoThe Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
“Contrary to “SEO is dead” narratives, Sandy Diao insists that foundational SEO remains essential—and is becoming more important as generative engines like LLMs rely on the same crawlability, structured data, and content signals to surface citations. Don’t abandon SEO fundamentals; treat them as the backbone for GEO.”
37:22
AI Exchanges: How tech giants are navigating the AI landscapeExchanges
“Eric Sheridan’s data-driven argument counters the cannibalization thesis. Since the launch of ChatGPT in November 2022, the total volume of human-to-computer queries has exploded rather than divided.”
12:10
20VC: Anthropic Raises $30BN from Microsoft and NVIDIA | NVIDIA Core Business Threatened by TPU | Sam Altman's "War Mode" Analysed | Sierra Hits $100M ARR: Justifies $10BN Price? | Lovable Hits $200M ARR & Rumoured $6BN RoundThe Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
“In the episode, the bull case (Rory) holds that GEO tools like Peak serve a pressing enterprise need: VPs of Marketing, under CEO pressure to appear in AI-generated answers, will pay for visibility even before the channel can deliver measurable traffic or conversion. The bear case (Jason) argues that the product is currently unactionable, relies on credit-card capture tactics, and faces high future churn, especially if LLM platforms eventually absorb the optimisation layer.”
66:00
GaryVee on how to make Super Bowl ads that are actually funnyMasters of Scale
“Gary Vaynerchuk observes that social creative—the text, images, and videos posted across platforms—now directly shapes how brands appear in LLM-based search and answer engines. GEO does not replace AEO; rather, it highlights the new frontier of social-creative feeding generative search.”
9:47
Aravind Srinivas - Building An Answer Engine - [Invest Like the Best, EP.363]Invest Like the Best with Patrick O'Shaughnessy
“The answer engine model leverages large language models and Retrieval-Augmented-Generation to read, summarise, and cite relevant snippets. This reduces the cognitive load on the user and can greatly improve satisfaction for “informational” queries.”
9:40
Extended Questions
Which SEO fundamentals are most likely to influence whether an LLM cites a brand or publisher?
How should brands measure GEO success if AI answer engines produce citations and mentions instead of traditional clicks?
What role do Reddit, Quora, LinkedIn, and other community platforms play in shaping LLM-generated brand sentiment?