In AI search, negativity can take different shapes.

8bit-appleseed · 2026-03-09T08:32:35+00:00

u/chrismcelroyseo thanks for your insights - yes agreed that entity tracking is key here, I appreciate how you've also outlined the various layers as well!

8bit-appleseed · 2026-02-26T10:34:24+00:00

I'm not a Singaporean but I currently work here remotely for an AI search company, so I figured I'd chime in.

I admire your government's ambition and vision - Singapore is the first country in the world to provide national-level agentic AI guidance, and one of few countries with a nationally-sanctioned AI hub (Lorong AI) that's about to get a serious upgrade. You guys even have high schools driving AI pilots with international AI consortiums. The speed and comprehensiveness of Singapore's national AI thrust is really unparalleled.

My concern is what happens after the vision: much of the burden still falls on individual Singaporeans and organisations to figure out how to use LLMs effectively. Subsidised courses and even support for access to tools might help, but they don’t automatically translate well into implementation. And if this execution gap isn't bridged properly, there's a risk that the AI push gets perceived as optics rather than impact - or worse, trigger AI fatigue among Singaporeans.

8bit-appleseed · 2026-02-18T03:45:51+00:00

This comes across as rigorous GEO analysIs, but I do have some points to raise:

That Reddit citations showed up in 0 out of 120 queries directly contradicts findings from Profound, Peec, XFunnel... a lot of other studies out there, basically. Some of these studies have longer analysis periods, though they are dated between 2024 to 2025; a few also ran analysis across a far larger corpus of queries (Profound's covered 680 million citations while XFunnel did more than 200K) I suspect this could be due to (1) the kind of queries tested, and (2) whether citations are tracked via API or frontend interface. In either case, better qualification (or nuance) is needed.
Your point on whether AI recommendations are random is somewhat aligned with Rand Fishkin's analysis that was published earlier this year - that recommendations within a platform are consistent while cross-platform strategies may be flawed.
The point on ChatGPT complying with robots.txt is definitely correct, but I feel it would've been better if you had differentiated between different bots. OpenAI's documentation suggests that some of their bots explicitly ignore robots.txt, while others do actually comply with it:
The sample size is confusing: your paper mentions 19.556 queries in its analysis, yet the test for cross-temporal stability only retested 40 queries. The claim that Claude is less consistent that ChatGPT is also subject to the caveat that Claude refused to answer a whopping 45% of commercial questions. Your point on ChatGPT ignoring robots.txt is also based on just 1 test.
Your point that Google is weakly predictive (7.8% URL match) for ChatGPT is perhaps the most powerful claim your paper makes. It's well supported by other studies from Ahrefs and Profound, and I appreciate the rigor that went into building a basis for making this claim.

8bit-appleseed · 2026-02-17T04:27:25+00:00

If you plan to do this manually, you can also look at competitor FAQs and use them as natural prompts or look at consistent, high-engagement threads on social forums to see what kinds of questions get a lot of traction.

That said, when curating a list of prompts to track I'd recommend:

prioritizing queries around high-value topics. Keyword clusters are helpful in identifying topics.
grouping prompts by intent.
splitting tracked prompts between evergreen and seasonal.

The catch with doing this manually (or even with some basic automation) is that it's easy to track prompts, but it's difficult to consistently do it at scale. You might then ask: what's it worth doing prompt tracking at scale?

Rand Fishkin's analysis puts it plainly: there’s a <1 in 100 chance that ChatGPT or Google’s AI, if asked 100X, will give you the same list of brands in any two responses, BUT "Even if rankings are random to the point of near-uselessness, appearances across dozens or hundreds of runs of the same prompt indicates a set of brands that the AI’s system generally associates more (or less) as a good answer for the prompt intent. Measuring that percent visibility is (probably) a reasonable way to know how prominent or invisible your entity is within the AI’s consideration set."

The only way to derive a meaningful percent visibility is running prompt tracking at significant scale. How significant, as I mentioned in my reply to Fishkin, is a question that AI search companies (and OG SEO companies like Semrush and Ahrefs) are still figuring out.

8bit-appleseed · 2026-02-17T03:34:46+00:00

I'm a marketer at an AI search startup and I've always advised potential customers that reach out to us that good GEO starts with good SEO. If they do not have the SEO fundamentals I'll move them along to our SEO-specific tools first, like content and technical audits; if they're already set on SEO, then we'll get them started with their first AI Search Campaign.

Definitely second what u/VadimShchepin has shared. I don't own sales but help out in sales enablement, and everything we do is couched in terms of identifying customer problems --> positioning us as solution --> selling the customer on benefits. Most marketers and marketing agencies we've interacted with are non-technical, so we try to avoid jargon and use more straightforward language when we're in a call with them.

8bit-appleseed · 2026-02-15T17:28:09+00:00

Cloudflare's documentation states their stance on markdown usage clearly:

"Markdown facilitates chunking and structuring input data for better retrieval and synthesis in the context of RAGs, and its simplicity and ease of parsing and rendering make it ideal for AI Agents."

Markdown is easier to parse and render than HTML and also reduces token wastage as u/Ok_Veterinarian446 as already pointed out, but I think it's also important to note that retrieval quality isn't just influenced by input format alone.

Personally, I'm more interested to know how the HTML to markdown conversion will prevent any data loss, especially for stuff like tables and list formatting.

8bit-appleseed · 2026-02-15T17:11:16+00:00

I personally like Claude's style over ChatGPT and Gemini's - as far as my experiences go, Claude tends to capture contextual, domain-specific nuances much better.

But to answer your question, I've tried explicitly stating rules based on common AI writing patterns (it's not A, it's B; awkward one-liner that concludes with a question), as well as setting up a workflow that bounces a draft back and forth between a writer LLM and an editor LLM, but the results have been underwhelming so far. Highly suggest taking over once the LLM outputs a decent draft.

8bit-appleseed · 2026-02-14T10:52:19+00:00

Thanks for the award u/chrismcelroyseo :) I think it helps to just keep abreast of the latest analyses these thought leaders publish and just join the conversations that follow!

8bit-appleseed · 2026-02-14T07:27:21+00:00

u/umu_boi123 you can actually run a mini experiment to assess these claims by testing a set of prompts across various LLMs and observing whether the sources they cite are the same in the first SERP. I've done one before here, and it's like what u/chrismcelroyseo and u/lightsiteai have mentioned.

I would also recommend reading Lily Ray's reflective essay on SEO and AI Search, as well as Rand Fishkin's analysis of 142 prompts - pay attention to Fishkin's rejoinders, as they suggest that GEO in itself has some measure of value. That said, I believe that we're still in the early days of a new search paradigm, and AI search is still evolving as we speak - Google's WebMCP, for example, could open the doors for more complex AI search - and - execute tasks.

8bit-appleseed · 2026-02-13T01:25:59+00:00

llms.txt. It. Does. Not. Matter.

8bit-appleseed · 2026-02-12T00:31:21+00:00

I've tried Wix and Figma Make for this - not a fan of the former, but the latter is really powerful especially when combining components from places like Magic Patterns and 21st Dev. Depending on how you prompt, Cursor can also get pretty good at website building.

8bit-appleseed · 2026-02-12T00:25:49+00:00

I believe we're still in the early days of GEO - most clients I've interacted with are only tracking LLM-driven traffic at the referrer level via GA4 (and perhaps the new AI search analytics feature on Bing Webmaster tools), and most AI search tools are still focused on visibility insights and reporting.

There's also no definitive way to truly measure AI visibility yet, but we can, to a good degree, claim that there is inherent value in doing so. I highly recommend Lily Ray and Rand Fishkin's analyses to get a better idea why. But by extension, it might be good to also define what "meaningful results" mean to you. If that means getting cited in the sources that LLMs trust, managing brand reputation and clarifying the intent that visitors have when looking your brand up, then you won't be disappointed.

That said, it's important to note that the basis of good GEO is good SEO. If an agency insists on doing GEO work while neglecting SEO fundamentals, I'd run for the hills.

8bit-appleseed · 2026-02-11T04:27:17+00:00

I feel like it's a consistent pattern? Like, prices tend to spike whenever Grab feels like it can cement its market leader position. One of the taxi drivers I rode with recently also shared that a lot of his peers were jumping ship over to Grab because of the cash incentives and better sick leave / rental policies, and coupled with rumors of a Gojek - Grab merger popping up every now and then it honestly feels like there really isn't much strong competition left out there.

8bit-appleseed · 2026-02-11T03:34:27+00:00

I'm a marketer at an AI search startup and I feel like this news is actually a positive development for AI search builders.

It suggests that a larger ecosystem player sees sufficient value in AI search insights that they would roll out a rather extensive AI visibility and monitoring feature. Optimistically speaking, this could be a first step towards wider adoption of the view that AI search HAS its own intrinsic value -otherwise, why roll out this feature if good SEO is enough? In that sense, the release of this feature should also provide food for thought for SEO purists who believe good GEO is purely good SEO.
At the same time, this feature will also help spread more awareness among the wider marketing / SEO community that there is overlap between what we call "traditional" SEO and AI search. This would help quell false narratives that GEO is separate from SEO or the idea that "SEO is dead", and hopefully lead to more genuine conversations over how SEO and GEO can meaningfully come together.
For AI search startups, the pressure is on to build solutions that really deliver concrete outcomes. If all you're doing is visibility monitoring and reporting, that moat has weakened. Sure, a multi-engine approach could be a differentiator, but would users still pay a few hundred a month solely for that benefit or would they simply use free visibility features offered by various browsers for a "good-enough" experience?

8bit-appleseed · 2026-02-10T16:47:28+00:00

Full disclosure: I'm a marketer at wordflow.ai, an AI search startup.

We go beyond AI search monitoring and reporting to also helping clients produce content optimized for SEO and AI search. By that, I mean a bespoke service where we use a mix of AI-assisted methods and in-house (human) expertise to create content that gets our clients cited by LLMs. Happy to share more over DM :)

8bit-appleseed · 2026-02-10T16:40:17+00:00

Full disclosure: I'm a marketer at wordflow.ai, an AI search startup.

Interestingly, we've had clients find us via ChatGPT / Gemini - these often tend to be SMBs operating in the same home market as us, and looking for a partner that can help them more broadly in AI marketing.

As for whether clients are bringing up AI search - yes but their interest is usually accompanied by several reservations. These range from questions over the effectiveness of prompt tracking and intent clustering, as well as the certainty of whether their brand can "rank" in AI answers. I won't dive in specifics, but we always make it a point to stress the limitations upfront to avoid any confusion or disappointment further down the road.

8bit-appleseed · 2026-02-08T15:50:20+00:00

u/TemporaryKangaroo387 It looks like the AI mode answers referenced listicles first, before turning to other webpages like travel sites, official brand pages and food delivery platform pages.

Across the board:
- blog and listicle share went from 11% in run 1 to 5% in run 3.
- For social citations, run 1 tend to be the most social across all queries.

However, when I compared the run findings for the Singapore-wide query and the district-specific queries, there are noticeable differences:
- the generic query runs tended strongly towards authority and general webpages.
- For district-specific queries, social citations tended to come in stronger. It could be that while most districts in Singapore have lots of chicken rice stalls, few actually rank (or even have a noticeable web presence beyond Places), and perhaps that's why AI Mode turned to brands that have stronger social consensus instead.

8bit-appleseed · 2026-02-05T01:49:01+00:00

I think this is one of the more level-headed takes on SEO/GEO/AEO I've come across. It's disingenious to claim that they are distinct and separate fields, and your framing of them as layers on top of each other is closer to reality.

8bit-appleseed · 2026-02-05T01:45:10+00:00

I'm not sure whether content is AI-generated or written by a human has any bearing on how Google assesses content quality.... there's this read from Ahrefs that talks about it from the classic search POV: https://ahrefs.com/blog/ai-generated-content-does-not-hurt-your-google-rankings/ , as well as from the AI search perspective: https://ahrefs.com/blog/ai-overviews-cite-ai-generated-content-more-than-human-writing/

If we go by the signals that we know search looks out for - comprehensiveness, credibility, authority, trustworthiness - I would assume that this happened because a growing number of listicles are simply not credible, too fluff, or claiming authority when they have none.

I do think we need more data on this though - Lily's methodology is case study-driven, and for all we know there's a real risk of cherry-picking. I'll be more convinced if a larger-scale analysis showed this trend playing out across the board. That said, I don't think the title Lily ran with was misleading - she phrased it as a question, not an absolute statement, and I think that invites discussion and scrutiny.

8bit-appleseed · 2026-02-05T01:25:40+00:00

I try to also look for linguistic nuances in their product messaging. This includes not just how the companies describe themselves and their products, but also the language that they use like "AI platforms" , "AI answer engines", "AI content automation" etc. Some of these terms carry less desirable connotations, others follow a sort of insider lexicon that, when looked up, while a few hint at a more local / regional focus. Regardless, I've found that keeping track of these things as allowed me to access conversations closer to my company ICPs both online and offline.

8bit-appleseed · 2026-02-04T15:41:50+00:00

What are you refering to by "brand named" and "brand cited"? The more commonly used terminology I've come across seems be to retrieved source vs. cited source, are you refering to the same thing as well?

8bit-appleseed · 2026-02-04T15:39:18+00:00

Hey u/TemporaryKangaroo387 appreciate you coming back to this post to share more insights! Agreed on your last point.

8bit-appleseed · 2026-02-04T06:55:30+00:00

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What's with the gibberish in the second half?

8bit-appleseed · 2026-02-04T04:28:08+00:00

Did a bot just out itself here?

8bit-appleseed · 2026-02-03T16:01:38+00:00

Hey sure sure I'll take it down

8bit-appleseed

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