What happened
In late July, Zuckerberg posted on X for the first time in about three years, announcing Meta’s new AI model Muse Spark 1.1, with the link tucked into a reply out of old habit.
The habit has a history. X used to suppress the reach of posts carrying external links, for an obvious reason: links pull people out of the app, which costs both session time and ad revenue. So everyone who works in social learned the same move — content in the post, link in the comments.
Nikita Bier, X’s head of product, replied under the post: you don’t need to put links in replies anymore. Paul Graham followed up — so you no longer penalize posts with external links? On 29 July, Musk answered personally: we haven’t done that for over a year.
A rule lived or died on one reply from the owner. From question to authoritative answer, under a day.
Someone can explain X’s algorithm. There is a person named Musk, you can ask him, he can answer, and his answer is the answer. One of the people who understands social distribution best on earth was still operating under a rule that expired a year ago — that is just information failing to travel. One question fixed it.
Why this matters to you
Now ask an AI engine the equivalent question: why did you cite this page last month and drop it this month?
Nobody can answer you. Not because it’s confidential — because nobody knows, including the people who built it.
You don’t have to take an outsider’s word for it; the labs themselves say it more plainly than anyone. OpenAI’s CEO has stated publicly that they have not solved interpretability. More than forty researchers from OpenAI, Google DeepMind, Anthropic and Meta co-signed a paper warning that we can currently glimpse a model’s decision-making by watching it “think out loud,” but that this window is fragile and may close as the technology advances — companies fighting each other for the same market sitting down to issue a joint warning tells you something on its own. Anthropic’s CEO wrote a long essay on the urgency of interpretability containing the bluntest line of all: we do not understand how our own creations work, and that is essentially unprecedented in the history of technology.
Let me be precise here, because the loose version of this claim is easy to knock down. Engineers are not powerless.
AI search has two layers. The retrieval layer — which sites make it into the index, how often crawlers return, how much weight freshness carries, whether there are source allowlists — is a real set of engineering settings that real people tune, no different from X’s algorithm. The only difference is that no Nikita Bier comes out to announce the change.
The generation layer is another matter. Why A appeared in the answer and B didn’t, why the same question asked twice gives different results, why a competitor suddenly entered the answer this month — these are behaviors that grew out of training, with no rule anyone can point at and switch off. Engineers can change it (different training data, different alignment work, a different system prompt), but why it turned out the way it did afterwards is something they observe after the fact too.
So the precise statement is this: the people who can change it cannot explain it.
The implication for you is direct. If what you’re paying for is “we’ve figured out how the engine currently ranks things,” you’re buying something nobody holds. The people who wrote the model can’t produce that rulebook — so where did the vendor selling it to you get a copy? We took this pitch apart once already in the emperor’s new clothes piece, and this news kicks another block out from under it. Evidence runs the other direction too: models can already read the intent of people tampering with a page. You can’t work out its rules; it can work out yours.
Do you need to act
Nothing on your site needs to change because of this news. What needs to change is how you question a vendor.
The next time someone tells you they know how the engine ranks right now, ask two things: where did you learn that rule — which official source said it, and when? And the last time it changed, how long before you noticed? If they can’t answer both, they’re guessing, with your budget.
Put the money where it doesn’t depend on knowing the current rules. Content that can be verified, facts that hold up across your pages, consistent mentions from enough external sources, machines that can read what you actually do — these conditions are worth investing in because they survive every model refresh and every rewrite of retrieval logic. Anyone chasing the rules starts over at each refresh, and nobody sends them a notice that it’s time to start over. X at least had a head of product step in to say so. AI engines don’t have even that.
Nobody can tell you the date of the next rewrite, and nobody can promise that doing all this gets you cited. Anyone offering that guarantee is selling something. Only one thing is certain: the rulebook you want to buy doesn’t exist, and not even the person in Musk’s seat can produce it.
If you want to know where you stand right now, managed GEO from geoweb.tw starts with a diagnostic — we look at how you actually appear across AI answers first, then decide whether to move and where. None of the individual pieces are hard to understand. What’s hard is watching whether each one is still alive after every refresh, and that takes someone doing it continuously.