There’s a lot of debate right now about AEO and GEO—whether they’re just part of traditional SEO, a completely new discipline, or simply SEO under a different name. Every side has valid points, which makes it hard to take a clear position. But one thing is certain: search is evolving fast. Instead of arguing about labels, it’s probably smarter to focus on where these ideas overlap and build strategies from that common ground.
The Case Against AEO and GEO
Many SEO professionals believe AEO and GEO aren’t distinct enough to be treated as separate disciplines. In their view, these concepts are simply extensions of SEO—basically sharing the same fundamentals, just operating in a slightly different context.
Harpreet Singh Chatha of Harps Digital recently shared a thread on X about common AEO/GEO myths to leave behind in 2025.
Some of his key points included:
- The obsession with LLMs.txt as a magic solution
- Paying a “GEO expert” for so-called chunk optimization—when chunking is really just making content easier to read
- The idea that AEO/GEO has nothing in common with SEO (he joked that if you ask a GEO expert for 25 things that don’t overlap with SEO, they’ll block you)
- Claims that SEO is dead
The criticism around LLMs.txt comes from a simple reality: no major AI search engine actually uses it today. Expecting SEOs and publishers to maintain a separate markdown file for AI is also unrealistic—let’s be honest, it would inevitably be manipulated for rankings. That would force AI systems to double-check the markdown against the regular HTML anyway, which defeats the whole purpose of having a lightweight, convenient format in the first place.
Another driver behind the anti-GEO sentiment is the rise of a small but very vocal group of pro-GEO/AEO agencies and individuals with limited real-world Search Engine Optimization experience. Many of the solutions being pushed are, at best, repackaged SEO tactics—and at worst, outright spammy strategies. The SEO community has also noticed that some of the loudest voices in this space are fresh out of college with little to no hands-on experience, which has only fueled skepticism.
Greg Boser, one of the true pioneers of SEO since the mid-’90s, recently shared a perspective that cuts through a lot of the noise in our industry.
He basically said this:
At its core, what we do has always been about one thing — understanding how people use technology to find knowledge. That’s it. That’s the foundation. Not hacks. Not loopholes. Not trendy frameworks. Just human behaviour and how it intersects with digital systems.
Change the “E” in SEO from “Engine” to “Experience.”
Because ultimately, that’s what we’re optimizing — the user’s experience of discovering and consuming information.
If we did that, maybe we could stop obsessing over naming every shift in search and get back to the real work: understanding people, understanding platforms, and building things that actually help.
Inability To Articulate AEO/GEO
One reason people think AEO or GEO isn’t really a separate concept is that many people promoting it don’t clearly explain how it’s different from traditional SEO. We’ve all seen this on social media—someone shares a “new” tactic, and the SEO crowd immediately replies, that’s just SEO.
There’s no hidden trick to getting picked by AI systems—success starts with content that is fresh, authoritative, well-structured, and easy for machines to understand.
The post also reinforces the importance of core SEO fundamentals like crawlability, metadata, internal linking, and backlinks—but notes that these are just the basics. Microsoft also highlights that AI search doesn’t return a ranked list of pages like traditional search; it delivers direct answers instead. And that shift changes a lot.
Microsoft says the focus is now on which pieces of content are actually being selected and ranked by AI:
In AI search, ranking still matters, but it’s more about which content gets included in the answer, not which pages rank first.
That’s similar to what Jesse Dwyer from Perplexity AI recently mentioned about AI search and SEO:
When it comes to indexing technology, one of the biggest differences in AI search today is whether systems process entire documents or break them down into smaller parts.
The AI-first approach focuses on what’s called “sub-document processing.” Instead of indexing full web pages, the system indexes smaller, highly specific content snippets—though these are different from what SEOs typically call “featured snippets.”
Microsoft recently released an explainer titled “From Discovery to Influence: A Guide to AEO and GEO,” and it’s interesting that it focuses largely on shopping. That’s notable because more people are starting to recognize that e-commerce could benefit significantly from AI-driven search.
Unfortunately, the outlook is less positive for informational websites. There’s a growing sense that agentic AI could strip these sites of their branding and unique value, treating them mainly as raw data sources rather than destinations in their own right.
Common SEO practices that are now being labelled as GEO
A lot of what people are calling GEO or AEO today is simply classic SEO under a new name:
- Writing content as direct answers
SEOs have been doing this since featured snippets launched around 2014.
- Chunking content into tight sections
Short, focused paragraphs have long been best practice—especially for mobile readability—and good SEOs have used this approach for years.
- Using structured content
Clear headings and well-organized sections that reduce ambiguity have always been core SEO fundamentals.
- Adding structured data
Let’s be honest—this is pure SEO. Nothing new here.
Should You Turn Your Back on What Clients Want?
Some people in the “GEO is real” camp see themselves as adapting to the times, but they also admit they’re mostly responding to client demand. SEO professionals are in a tough position—do you stick firmly to traditional SEO, or do you follow what potential clients are actively asking for?
Many SEOs already recognize that there are differences in how AI systems cite and rank websites. Setting aside low-quality listicle content, a lot of what’s being marketed as “AI-ready” is still just SEO:
- Content clarity
- Structured content
- Structured data
- Semantic SEO
- FAQs
- Freshness
- Citations from other sites
It all looks very familiar, right?
The exception is citations. Being cited by authoritative sources so others can validate your content—and having that surfaced in AI search—is relatively new. This could be a real opportunity for authoritative informational sites, especially since current AI search and chat platforms tend to rank sponsored content that is fully FTC-compliant and uses Google-friendly nofollow attributes.
Googlers Say It’s Still Just SEO
Some Googlers, including Robby Stein (VP of Product), Danny Sullivan, and John Mueller, argue that SEO is still fully relevant. Their view is that, behind the scenes, AI systems are essentially running Google searches and pulling top-ranked pages to generate summaries, answers, and links.
Google has also played down the idea of GEO. But at the same time, we’re seeing plenty of low-quality, AI-driven SERPs, which raises questions about how this all actually works in practice.
Interestingly, OpenAI recently posted a job listing for a content strategist focused on SEO—not GEO. Some people see that as a sign that even OpenAI is still prioritizing traditional SEO fundamentals.
Optimization Is No Longer Just About Google
Manick Bhan, founder of the Search Atlas SEO suite, shared an interesting perspective on why SEO and GEO may be diverging into separate paths.
Manick shared:
He pointed out that while SEO technically stands for “search engine optimization,” in reality it has long meant “Google optimization.” Google shaped the interface, ranking systems, incentives, and even how the industry thought about search.
Manick also noted that calling GEO a sub-discipline of SEO is tricky, because the LLM landscape isn’t a single ecosystem. Plus, Google’s AI Mode is becoming its own generative surface, which changes how optimization works altogether.
Manick believes that GEO is fundamentally different from SEO and shared the following perspective:
My view is straightforward: GEO isn’t just SEO with a new label. Treating it that way overlooks a fundamental shift in how modern answer engines retrieve, rank, and piece together information.
The core tactics—on-page and off-page signals—are still in the same universe and haven’t disappeared. But the systems we’re optimizing for have changed, and that changes how everything works in practice.
Today’s answer engines:
- Retrieve information using different signals and pipelines,
- Combine and prioritize sources using distinct weighting models,
- Evaluate and apply recency in different ways,
- Assess trust, authority, and credibility through varying frameworks,
- Expand and decompose queries differently before retrieval,
- And feed user behaviour back into their RAG systems in different ways.
Even subtle technical factors—such as logit calibration and temperature settings—can lead to noticeably different retrieval results. That’s why using the same prompt across different engines often produces measurable differences in meaning and the sources cited.
This is why we consistently observe measurable differences in:
- The sources retrieved
- How answers are structured
- Citation behavior and patterns
- The semantic framing of responses
- Ranking and presentation across LLMs, AI-powered search interfaces, and traditional Google results
In this environment, experimentation and intellectual humility are more valuable than rigid frameworks. Treating this as “just SEO” underestimates how fundamentally different these systems already are—and how rapidly they continue to evolve.
Clarity Around GEO, AEO, and SEO
This debate feels unresolved because the industry is arguing over terminology while the underlying systems are still evolving. The clarity many people want won’t come from naming what’s new, which is why none of the labels feel fully accurate yet. The ambiguity isn’t a failure to define GEO or AEO—it’s a reflection of how early and fluid this transition really is.
There is no fixed GEO playbook today. What does exist are observable differences in how systems retrieve information, generate answers, and cite sources. On the output side, natural-language answers are the defining shift. On the input side, this makes it clear what matters most in content: explicit, high-quality answers and strong contextual structure so information can be reliably cited or synthesized by AI systems.
Real clarity in the SEO vs. GEO conversation comes from acknowledging a contradiction: dismissing GEO as imaginary while admitting that “something is different” avoids confronting the fact that those differences are already influencing how content is selected and surfaced. At the same time, treating GEO or AEO as mature, stable disciplines assumes a level of system consistency that simply doesn’t exist yet.
The core reality is that optimization is no longer for a single system or interface. What we call SEO is in transition, expanding across multiple retrieval and answer-generation surfaces rather than a single ranking paradigm.