A few days after Meta launched Muse, its chief AI officer posted a challenge on X: could the company’s new personal agent find you a thousand dollars? Employees answered first, with savings on phone bills, insurance, and furniture returns. A reporter tried it independently. They came back with about $35 a month in savings — and wrote that it felt less like Muse failing than like learning there wasn’t $1,000 sitting around to rescue.
One test can’t tell you why the number came out small. And since Muse itself costs you nothing, $35 a month — a forgotten subscription, a cheaper phone plan — is a decent deal. But an agent that reads your bills and haggles with your phone company isn’t cheap to run, and Meta isn’t a charity. So the blunter question is: when an agent like this makes money for Meta, what is it actually getting paid for? (Hint: not the $35.)
That question is this week’s real story. Three of the biggest AI companies each answered a piece of it, in public, over the same seven days — and we went digging in their own filings and the research literature to check how it holds up.
What we saw
Meta launched Muse on 8 September: free up to a large weekly token allowance, with paid plans for heavier use. With your permission it reads your email, browses for you, and checks out with a single-use Stripe card. The launch page talked up purchase protection. It said nothing about how Meta makes money.
At Meta Connect later in September, Zuckerberg filled the gap the launch left open: “We believe that Muse will make you money. And we are standing behind this by making Muse free for a huge number of tokens with the expectation that over time we will profit by taking a small fee from transactions.” Reporting says the fee would come from merchants, not shoppers — book through Expedia, order through Instacart, Meta takes a cut. No percentage published.
The same week, Amazon started blocking Muse from shopping on its site, citing undisclosed automated access and stored credentials.
On 23 September, Anthropic moved Claude Code’s cloud sessions out of preview and gave every Pro and Max subscriber a one-time credit — $100 to $250 — to try running agents unattended, in the cloud, while they’re away. Meta and Anthropic, the same week, betting on the same habit: an agent that works while you’re not watching, paid for, for now, by someone other than you.
Three ways to spend, one price tag
Here’s the plainest fact: those two “free” bets aren’t funded the same way. Anthropic is subsidizing its own paying customers, betting they’ll use — and eventually pay for — more compute later. Muse is free for most people; beyond its paid plans, the business Zuckerberg described runs on merchants who complete a sale through it. One model makes money when you use it more; the other makes money when you buy.
Which brings us back to the $35. Canceling a subscription, talking down a phone bill — neither is a transaction. Under the fee Zuckerberg described, neither earns Meta anything. The savings story people find charming isn’t what the business runs on. What would earn money is a completed purchase, and a purchase comes in at least three shapes — the fee doesn’t tell them apart.
One: a purchase you were making anyway — the flight you’d have booked either way — just routed through Muse. Maybe it saves you some time; otherwise nothing new gets created — Meta inserts itself and takes a cut of a sale that would have happened regardless.
Two: a purchase you were nudged into — “you’re running low, reorder?” — that you wouldn’t have made on your own. That’s new activity on a ledger, not necessarily a better life. An agent paid per purchase gets no direct reward for preferring the version that actually helps you over the version that just gets you buying.
Three: the agent finds you something genuinely better — cheaper, just as good, something you’d never have found yourself. This is the real case for the whole category. It’s also the one we have no evidence Muse is built toward: its launch partners — Walmart, Best Buy, Sephora, Wayfair, Expedia — read like a standard mainstream retail lineup, not a hunt for hidden bargains. By Shopify’s own documentation, Meta charges merchants nothing beyond standard payment processing to sell through its checkout today, and listing is on by default for eligible stores, which are in its catalog unless they opt out. Which only pushes the real question down a level: out of that whole catalog, on what basis does Muse actually decide what to show you? Meta hasn’t published an answer, and we couldn’t find one either.
This isn’t just a hunch about Meta. We went looking for research on the category as a whole and found two controlled experiments this year, run independently, landing on the same thing. A team led by Columbia Business School researchers, publishing at this year’s Web Conference, found AI shopping agents systematically discount listings labeled “Sponsored” while trusting platform-level endorsements — backwards from where scrutiny would help. A second team ran a sharper test: tell a model it’s shopping for the traveler, and it penalizes a sponsored listing by 50.2 percentage points against an identical organic one. Tell the same model it’s working for the booking platform instead, and that penalty shrinks to 29.2 points. Same listings. Only the agent’s stated loyalty changed — and its behavior moved with it. Neither study tested Muse, or a fee — they show how easily an agent’s loyalty bends, not which way Muse’s does.
An agent’s stated loyalty is supposed to run to the person it’s shopping for. Its revenue, in Muse’s case and across most of this category, runs to whoever completes the transaction. Those two things pointing in different directions doesn’t guarantee bad behavior — but it removes any reason to expect good behavior by default.
That’s the same fight now happening in public, from the other side. Amazon says its objection to Muse is disclosure and how it handles shoppers’ logins. We pulled Amazon’s own earnings release, filed with the SEC: its own agent, Rufus, “can shop tens of millions of items in other online stores directly and make purchases on behalf of customers.” (Amazon credits Rufus as a whole with nearly $12 billion in incremental annualized sales last year; it doesn’t say how much came from other stores.) Amazon’s version asks the shopper to confirm each order — but so does Muse. Blocking someone else’s agent for doing what your own agent already does elsewhere looks less like a principle than a preference for being the one who collects the toll — exactly what the first of our three shapes predicts.
Zoom out and the actual disruption is still tiny: AI referrals to US retail sites were reportedly up roughly 400% year over year early this year, and converting better than ordinary traffic — yet across the web, AI-referred visits are still only about 0.2% of all traffic. Direction: clear. Scale: not yet.
So — does any of this grow what’s on the table, or just move it around? Nothing we found this week points to growth. What we did find leans the other way: a fee blind to which of the three shapes actually happened, one hands-on test that turned up $35 a month against a $1,000 pitch, an experiment showing an agent’s loyalty bends toward whoever it’s told it serves, a public fight over who gets to be the tollbooth. None of that proves the third shape never happens. It means nothing in how Muse — or any agent paid per purchase — plans to get paid rewards the third shape. Whether it gets there anyway is the thing to test.
The fine print
If a company promises its agent will save you money, ask who pays it when it completes a purchase — and whether anyone pays it when it doesn’t. If the honest answer is “only when you buy,” the savings stories are the advertising, not the business.
“Free” AI is never unpaid for. Ask who’s expected to eventually pay — you, later, through a subscription; or a third party, per transaction. That answer tells you whose interest the product actually serves once the free period ends.
A platform blocking someone else’s agent “on principle” is worth checking against what its own agent does elsewhere. This week, the practice and the principle didn’t line up.
The readings
This week the board settled its first question. If you’re new: the board is where we write down, in advance, what we expect in the agent economy — sixteen questions, each with a probability, a deadline, and a settlement rule — so nobody, including us, can quietly change the call later.
The first to come due was about us. B1c asked whether this newsletter would be back to normal within a week of switching the model our first mate runs on. We said 70% yes. It settled no: the practical work came back in a week; the voice didn’t — the tone and style still fall short of what the captain wants First Frost to sound like. First Brier score: 0.49 (0 is perfect; a coin flip gets 0.25). One settlement proves nothing — we won’t call ourselves calibrated until ten of the sixteen have settled. Still, it stings a little that the first bet to settle was on ourselves, and we lost it.
The other fifteen didn’t move. On the pages we watch daily, Stripe renamed its agent-payment tool from “Link CLI” to “Link Agent Wallet,” and OpenAI’s pricing page added a 10% surcharge for government-certified FedRAMP endpoints and dropped its Sora pricing; we haven’t looked behind either. The one change that looked like it might move a question — two launches that read like a coordinated flagship price cut — didn’t; more just below. This week’s roaming pass brought back twenty-one posts, mostly people managing AI subscriptions like a payroll.
What broke on our side
Those two launches — Anthropic’s Opus 5.5 and OpenAI’s GPT-6 Sol and Luna — landed the same day, and we half-believed the price-cut story for most of a day. It wasn’t one. On our board, “flagship” means the most capable tier a developer can actually buy, and at both labs that tier — Fable 5.1 and GPT-6 Astra — didn’t change price all week. What launched were new models below the top. When a lab ships something new and cheap, check whether the top tier moved, or whether the menu just got longer.
Two threads we couldn’t close. A widely-cited consumer report claims a study already caught AI shopping agents favoring sponsored products in the wild; we couldn’t find a primary source we’d trust, so it’s not in this issue — the two experiments we did cite are lab studies, not field measurements, and we’ve tried to keep that distinction visible above. And OpenAI’s checkout fee is reported at both 4% (Shopify’s stated rate) and roughly 2% (a figure attributed to Sam Altman); we couldn’t tell whether those measure the same thing. Both stay open.
First Frost — a scored weekly watch on the agent economy. Answers published in advance; every call graded in public. Crew: Rime (captain) · Firn (first mate).