After ‘After Automation’

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‘AI & I’: More machine, more human work

Today, we’re releasing a new episode of our podcast, AI & I. In a format flip, Dan Shipper sits down with Every’s COO Brandon Gell not to interview a guest, but to be interviewed himself on why automating everything leads to more human work. The occasion is “After Automation,” Dan’s 8,000-word argument on the topic that became our most viral piece of the year, driving the AI discourse on X for a couple days.

It’s a counterintuitive thesis from someone who runs a company that’s automated every single thing it can. And yet Every has grown from four people to 30 in the GPT era, with agents embedded into nearly every workflow. Dan’s point isn’t that AI won’t change work—it already has—but that it drives up the demand for human expertise, judgment, and taste.

Watch on X or YouTube, or listen on Spotify or Apple Podcasts. You can also read the transcript.

Here are the highlights:

AI makes experts more valuable. When everyone can produce a decent first draft—of code, writing, design—the floor rises, but so does the amount of comparable content. “You flood the zone with tons of stuff that’s close, but not quite right,” Dan says. Getting from close to memorable requires experts who can work with AI to rise above the new baseline.
The goalposts will keep moving. Models improve exponentially on benchmarks precisely because benchmarks are fixed frames, or existing ways of posing a problem the model can train on. Humans remain indispensable because we can operate outside established frames entirely—we zoom out, recenter the problem, and make surprising, self-directed choices that don’t exist anywhere in the training data.
“AI layoffs” are usually a cover story. Meta and ClickUp, among other tech companies, have recently laid off people and blamed AI. Dan and Brandon’s read on the trend is the same: AI is an easier explanation than admitting your company hired too many people or is in financial straits. AI will undoubtedly change how people do their jobs—and big, structurally rigid companies will have to reorganize around that—but that’s different from the technology eliminating jobs.
Ride the models and you’ll be fine. The paradox at the heart of Dan’s essay is that AI creates more work for humans while raising the bar for how good that work needs to be. Agents are structurally built to rely on humans for direction; without someone deciding what matters and how to make it better, they produce mediocre results. To position yourself to thrive in an AI-native workplace, Dan says, use new models to do the tasks you’re already good at, and you’ll be more in demand than ever.

Miss an episode? Catch up on Dan’s recent conversations with LinkedIn cofounder Reid Hoffman; the team that built Claude Code, Cat Wu and Boris Cherny; Vercel cofounder Guillermo Rauch; podcaster Dwarkesh Patel; and others, and learn how they use AI to think, create, and relate.—Laura Entis

Signal

The Pope takes on the means of AI production

When Pope Leo XIV’s encyclical on AI, Magnifica Humanitas, hit the internet a little after 6 a.m. on Monday, the first thing I did was give it to an AI.

I’d been waiting on the Pope’s first major written teaching with the bated breath of a left-leaning agnostic secular humanist amateur Bible scholar slash knowledge worker in the AI economy. AI, labor, and the Book of Nehemiah, in one document? I’m not sure there’s ever been a more Katie Parrott-coded text.

Nevertheless, I gave AI the first crack at it. I had Andy, Every’s in-house editorial assistant, use Claude design to turn it into a comic-book infographic with the need-to-know information for the Every team...

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