So here's a fun thing that happened while we were all busy arguing about whether AI is going to replace us or just make us slightly more anxious: Reddit went from being the single most-cited website inside ChatGPT to basically not existing there at all. In about a week. With no warning, no announcement, and — this is the really fun part — no confirmed explanation.

If you've ever woken up to find your listing suppressed, your account flagged, or your organic ranking evaporated for reasons that Amazon support can only describe using what appears to be a random sentence generator, congratulations. You already understand exactly what happened here. The rest of the marketing world is just catching up.

Let me give you the numbers, because they're genuinely absurd. Over the summer, Reddit held roughly four percent of all citations inside ChatGPT's answers. That might sound modest until you realise it was ahead of every other social platform, some of which barely registered at all. Adding "reddit" to a search query had become the internet's unofficial hack for getting real opinions instead of SEO-optimised content farms, and the AI engines had essentially formalised that habit by leaning heavily on the platform.

Then, across a handful of days in mid-August, that share dropped to around half a percent. An eighty-six percent relative decline. A channel that had felt like permanent infrastructure turned out to be, and I cannot stress this enough, a preference setting that someone changed.

Here's where it gets genuinely interesting, in the way that plumbing problems are interesting when you own the house.

The first shift was about how ChatGPT goes looking for information. When the model needs current data to answer a question, it doesn't just rummage through its memory like I rummage through my kitchen drawer looking for batteries. It runs background searches, reads what comes back, and assembles a reply from whatever it finds.

Two things changed at once around early August. First, the model started breaking single questions into several parallel searches rather than one broad one — a technique called query fan-out. Second, a large chunk of those searches suddenly started targeting specific chosen domains rather than the open web. The proportion of searches aimed at a single named site jumped from basically nothing to nearly seventeen percent.

The plain-English version: ChatGPT stopped asking the internet an open question and started deciding in advance which sites it trusted for a given topic, then going straight to them. When you do that, a broad general-purpose forum is exactly the kind of thing that loses ground to narrower, more specialist pages. No ban required. Just a quiet change in who gets asked.

That shift produced a first, modest dip. But the really steep collapse came several days later, around the fourteenth, and here's the part that should make everyone uncomfortable: nobody has accounted for it. The search-behaviour change and the sharp fall are separated by roughly a week, which means the first doesn't cleanly explain the second. The researchers who flagged the decline are refreshingly honest about this — they say their data shows when the shift happened, not why, and they go further, noting that a fault in their own measurement can't yet be ruled out.

That honesty isn't a footnote. It's the whole lesson. (We'll come back to it. Dramatically.)

The collapse was almost entirely confined to ChatGPT. Over the same window, Reddit's presence in Google's AI-generated answers barely moved. If Reddit had genuinely become less useful or trustworthy, the decline would have appeared everywhere. It didn't. The same content that vanished from one engine remained perfectly visible in the others.

Which means this was never a judgement about what Reddit is worth. It was one company quietly changing its mind about who to ask. That distinction matters enormously, and it's the bit most of the commentary has been skating over.

If this feels familiar, that's because an almost identical thing happened roughly a year earlier. Reddit's ChatGPT citations collapsed in much the same way, the coverage moved Reddit's share price, and everyone scrambled to figure out what had gone wrong.

The most persuasive explanation that eventually emerged pointed somewhere genuinely wild: Google had quietly removed a setting that let data tools pull back up to a hundred search results at once instead of the standard ten. That single adjustment meant the intermediary data providers who feed information to the AI engines could no longer see deep enough into search results to find forum threads — which tend to live way down the rankings. When the intermediaries lost that depth, Reddit's presence in AI answers thinned as a downstream consequence.

Sit with that for a second. The cause of a visibility collapse was not the platform whose visibility collapsed, and it was not the AI company doing the citing. It was a third party, two steps removed from either, making an unrelated change to its own product. Nobody announced it as a decision about anyone's AI presence, because to them it wasn't one.

Twice now, the same pattern: an opaque upstream cause no marketer could have predicted, detectable only after the fact, and never fully confirmed even in hindsight. (This is the dramatic return I promised. Worth the wait? No? Fair.)

The advice the industry has reached for, almost in unison, is to diversify. Don't depend on a single source. Spread your presence across channels so when one falls, the others hold.

This is sensible. It's also the advice equivalent of telling someone who just watched their house flood to "maybe get insurance next time." True, but not quite meeting the moment.

The trouble is partly that different AI engines don't draw on the same sources. A brand can be heavily cited in one model and completely invisible in the next, because each engine has its own retrieval habits and its own idea of who counts as authoritative. Looking dominant on one engine isn't resilience. It's concentrated exposure wearing a disguise.

But the deeper problem is the assumption buried inside the diversification metaphor. It implies you can see your baskets, count them, and check on them. What these two collapses actually demonstrate is that your presence inside an AI answer can be undone by a party you've never heard of, for a reason no one will confirm, in a supply chain you cannot observe. The risk isn't just that too much sits in one place. It's that the whole arrangement is opaque from end to end. Diversifying across channels you equally cannot see doesn't solve that. It just distributes the anxiety more evenly. (Which, to be fair, is how I handle most problems in my life.)

Here's where the story stops being abstract, because every seller reading this has already lived some version of it.

Platform dependency is the native condition of the Amazon seller. You build a business on rules you didn't write, inside a system whose logic you can only infer, and you accept that a change made elsewhere — for reasons you will never be told — can reprice your entire operation overnight. You've spent years developing a wariness about exactly this. You know the quiet powerlessness of appealing a decision to a company that owes you no explanation.

AI visibility is that same dependency, reproduced one layer further up and, if anything, with even less to hold onto. On a marketplace you can at least read the policies and watch your own dashboards. Inside an AI engine, you often can't even see your own exposure clearly, let alone the machinery that governs it.

The seller instinct that says "never build your whole house on rented land" is not outdated in the age of AI search. It's the single most relevant instinct there is.

Because here's the flip side of all that citation value: when a source becomes valuable to AI, people rush to exploit it. And the exploitation this summer got crude.

The practice of trying to get cited inside AI answers — generative engine optimisation, answer engine optimisation, pick your acronym — produced a familiar playbook in its cynical form: brands creating fake accounts to post questions, then having their official account step in with the answer, seeding threads engineered purely to be picked up by a model. Done at scale, this is influence laundering — manufacturing the appearance of authority rather than earning it.

The predictable result is that platforms tighten up, moderators start removing the promotional posts, and the models grow warier of the very signals that made the source useful in the first place. The tactic corrodes the thing it feeds on. Whatever combination of causes sits behind this particular drop, that dynamic is real, and anyone who built their presence on it was always riding something that was going to buck.

Nobody knows which sources the AI engines will favour a year from now, or why they'll change their minds when they do. That uncertainty isn't going to resolve. If it makes you feel any better, it won't resolve for anyone — including the people building the engines, who, based on all available evidence, are also figuring this out as they go.

The only asset that doesn't reprice on someone else's decision is the one you actually own: your own site, your own product pages, your own body of genuinely useful content, and a real reason for a model to reach for you rather than a substitute. Everything else is a channel, and channels are borrowed.

The question worth asking yourself — honestly, uncomfortably — is whether you're trying to be genuinely worth citing, or merely trying to appear cited. Because one of those survives a mid-August algorithm change at 2 AM. The other doesn't. And you won't find out which one you built until it's too late to switch.

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😍It was great, all I needed

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