Dan Shipper, co-founder and CEO of Every, a website that reviews new technology, has been experimenting with using AI to automate tasks. The company's editor-in-chief, Kate Lee, was cloned in digital form after collecting 30,000 of her historical edits and building a copy-editing agent based on the data. This effort aims to capture Lee's expertise and distribute it throughout the enterprise. Shipper estimates that almost every writer is using AI in their work, but few admit it publicly.
Written by the local model on 2026-08-21,
using this article's own text rather than the other coverage of the
same event (that is the story summary below).
My fiancé works at Anthropic, whose models Every reviews and builds on, and which comes up below.
asserted
which → work → models
Earlier in our miniseries on productivity in the AI era, Replit's Amjad Masad described a "self-driving company" where most engineers don't look at the code anymore.
asserted
engineers → describe → code
For our penultimate episode, I wanted to visit someone running a version of that experiment in a somewhat unexpected place: the media business.
asserted
I → want → place
Dan Shipper runs a website that reviews new technology alongside a product lab that’s building it — and for some time now I’ve wondered what it’s like to work in a place like that.
asserted
it → run → that
Shipper is the co-founder and CEO of Every, which he launched in 2020 with Nathan Baschez as a bundle of business newsletters.
asserted
he → launch → newsletters
Today Every is a publication about AI that draws attention across the industry — for Shipper's column Chain of Thought, his podcast AI & I, and especially for the "vibe checks" in which he and his coworkers get early access to new frontier models and put them through their paces before their general release.
asserted
he → draw → release
The roughly 30-person company offers Cora, an email assistant; Sparkle, a file organizer; Spiral, a writing tool; and Monologue, a dictation app — all of which are bundled with the journalism into a $20-a-month subscription.
asserted
all → offer → subscription
Shipper says AI now writes essentially all of the company's code, while humans still (mostly) write the essays.
asserted
humans → say → essays
But AI is changing the way that the company writes.
asserted
company → change → way
Shipper told me Every has tried to clone the taste of its editor in chief, Kate Lee, by collecting a dataset of 30,000 of her historical edits, using it to build a copy-editing agent, and back-testing it against her past work.
asserted
Every → tell → work
It’s an effort to capture the expertise of a single employee and distribute it more broadly throughout the enterprise — a preview, I think, of how more businesses will think about the relationship between AI and employees in the years to come.
asserted
businesses → ’ → years
Shipper was also candid about what it's like to publish a critical review of a frontier model from a lab the company depends on, arguing that Every's role as an arbiter may be one of its most durable assets.
uncertain
role → publish → assets
"No one trusts a model company to tell you where they objectively sit,” he said.
asserted
he → trust → you
More controversially, Shipper told me that far more writers are integrating AI into their workflows than will admit it publicly.
asserted
writers → tell → it
"I think there is a real dirty secret right now, which is that almost every writer is using it,” he said.
asserted
he → think → it
“Just, most of them are not saying so."
asserted
most → say → them
I also had to ask Shipper a question at the heart of our miniseries: if AI automates the work, why does Every keep hiring?
asserted
Every → have → work
The company doubled from about 15 people to around 30 over the past year while loudly automating everything it can.
asserted
it → double → everything
His explanation — that AI is "trained on the residue of human expertise," but can’t see beyond it — may be good news for jobs in general, at least for as long as it holds true.
uncertain
it → train → jobs
An excerpt of our conversation is below, edited for clarity and length.
asserted
excerpt → edit → clarity
Listen to the entire conversation wherever you get your podcasts — just search for Platformer — or watch it on YouTube at youtube.com/caseynewton.
asserted
you → listen → youtube.com/caseynewton
And let us know what you think — we welcome your feedback at casey@platformer.news.
asserted
we → let → casey@platformer.news
Every does “vibe checks” of new models.
asserted
Every → do → models
I found when I worked at a site that reviewed gadgets, there was sometimes a tension between what the companies want from early reviews and what you give them as a critic.
asserted
you → find → critic
You published what I would say was a fairly critical review of Sonnet 5 — "a model pitched for everyone impresses no one."
asserted
I → publish → one
How did that affect your relationship with Anthropic, and how much did you think about that before you hit publish?
asserted
you → affect → publish
Obviously, we know a lot of people at OpenAI and Anthropic, and you never want to be totally mean to people you're friends with.
asserted
you → know → people
But actually, even before we publish anything, they're asking, "What do you think?"
asserted
you → publish → What
Because they want to make the model better, and they know that if we don't like it, it means something — and they'd rather know beforehand, honestly, than find out from a ton of other people who use it.
asserted
who → want → it
They would probably also prefer that we didn't publish a big thing saying this model sucks.
asserted
model → prefer → thing
But they know we're not trying to be mean.
asserted
we → know → ?
We just have to say what we think, and if we think that, it's pretty likely a lot of other people are going to feel that way.
asserted
lot → have → people
My goal is never to shit on them; it is to help make better AI happen, and I think we do that in partnership with them.
asserted
we → shit → them
Sometimes it can get a little bit heated every once in a while — they're like, "I don't see how you could feel that way."
uncertain
you → get → while
The labs are enabling you to do these vibe checks, and you're using their models to build products.
asserted
you → enable → products
But it also seems like they are encroaching on your terrain, and everyone else's.
asserted
they → seem → terrain
Every ran a piece in June called "Built on Moving Ground," about the vertigo of building on models you don't control, where there's always a risk the labs will release as a feature something you spent the last year on.
asserted
you → run → year
How do you think about that risk, and where do you see the durable value in a bundle like yours?
asserted
you → think → yours
It's a really good question, and I don't have an answer to it.
asserted
I → have → it
There is just this dynamic where they're going to make their models better, and their models getting better does actually take a lot of the stuff that you build and make it less relevant.
asserted
it → be → that
…and 127 more, not listed.
