Cheap agents, alumni shirts, and Elias Thorne · Daniel May

Cheap agents, alumni shirts, and Elias Thorne<br>2026-05-12<br>The email arrived in my inbox at 3:20 AM this morning, with the subject line “getlikewise.ai DMARC is at p=none.” The from-name was Bruce. The signature, four lines down, was Benjamin. The opener summarized the project at that domain accurately enough that the agent had clearly read the public site before writing. The technical observation was correct: getlikewise.ai is in fact at p=none. The inferred problem was wrong, because the monitoring phase is deliberate and the configuration lives in Terraform. For $99 paid via Stripe, Bruce-or-Benjamin would send me the fix.

There is probably no email recipient on the open internet who needs this service less than I do. The DNS is covered by automated IaC, the DMARC progression is on a schedule I wrote myself, and p=none is the first step of that schedule. The agent did enough research to write a competent personalization. Whoever set it up didn’t write a rule for what to do when the personalization revealed a bad-fit target. The prose was fine. The work upstream of the prose wasn’t done.

I have been collecting these for a few months. Five weeks before the DMARC email, Ava wrote at 1:43 AM to ask whether I was content with my current cleaning service. She was nearby over the next few days, and the PS line offered a second opinion on my current setup. Five weeks before that, Charlie had written from a different operator’s stack at 2:00 AM, in slightly more formal British prose.

Both emails were addressed to me as a manager at a London fintech consultancy I left in 2016. I now live in Los Angeles. Charlie offered to call me on a London number. Ava was nearby over the next few days. Neither agent had any way to know that the source data both were mining was a decade stale; both followed the cold-outreach scaffolding correctly, hit the wrong target precisely, and went to bed.

The cleaning industry’s collective spreadsheet says Daniel May is an office cleaning prospect at a London fintech consultancy. That is not the failure of one bad agent. It is two operators, working from the same broken substrate, neither of whom did the work of checking it. The aim is upstream of the writing, and the work is upstream of the aim.

Move out of email and the pattern shows up at a different scale. There is a small veterinary clinic in south Austin called Manchaca Road Animal Hospital, which I followed on Facebook a few years ago after we adopted Zelda from them. It has around 700 followers, a real address, a real phone number, a real team photo.

Over the past two months I have been tagged in mass-comment posts on the clinic’s wall by accounts I do not recognize. The profiles look like real people, with years of unrelated family photos and birthday wishes, before something flipped and the accounts started posting on behalf of someone else. They are almost certainly compromised, phished or harvested or rented, and now drive content for an operation that didn’t build them. From the outside, the picture is indistinguishable from a pure low-effort agent operation running at the floor.

The comments themselves are templated and impersonate the clinic, with “our” doing the heavy lifting: “those who have not yet reserved our Alumni t-shirt, please reserve it quickly, as it will be available for a very short time.” Each comment is followed by a reply mass-tagging two dozen real names, mine included, to fire notifications. The same template runs from more than one account; a week earlier, Marie pitched the same shirt under a different SKU mix.

The Manchaca shirt is one tile in a catalog of thousands. The Facebook page behind this operation has been quietly generating shirt mockups for veterinary clinics, high schools, fire departments, and other small-institution affinity groups across the country, each waiting for the one notification recipient who half-remembers the place.

“Alumni” is also doing work the operators do not have a referent for. Animal hospitals do not have alumni; people who once took a cat there are not graduates. But “alumni” is an affinity word, the script needed an affinity word, and the print-on-demand model means there is no inventory to recover from the mistakes. If even one in a thousand notifications generates a sale to someone who half-remembers the clinic and assumes their old vet has started a fundraiser, the unit economics work. They only work because no one is doing the check; the check is more expensive than the mistakes it would catch. The dynamic is the same as the cleaning emails, multiplied by an order of magnitude.

The same dynamic runs on the production side. The work skipped upstream of an outreach is the work skipped upstream of an output: in both cases the tool produces what it can given the inputs, and the inputs are what the operator chose not to invest in. Open an instruction-tuned model and ask it to write a story.

The two...