He argues cheaper competence actually increases demand for human experts.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Positive users praise the insightful analysis and metaphors showing AI automation boosts demand for human experts, while negative users dismiss the claims as misleading sales pitches that ignore ongoing layoffs.
There is no paradox. The economics of near-AGI are extremely simple.
Expert verification is the bottleneck.
And the intelligence tide keeps rising.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
This is a fantastic post about why jobs aren’t going away in the way some predict. We are constantly making the mistake of confusing task completion with AI with being able to eliminate the whole job.
Even as we can automate one or many tasks within a job, the definition of the job almost inevitably just expands to do vastly more of those tasks, do them at a higher quality, or move on to the type of task that hasn’t been automated yet.
And as a result of being able to do more of the tasks or at a higher quality level, the job becomes valuable in a new way. And in many cases for now an entirely new audience as well.
This will be true for coding, legal work, sales, or marketing. The small business or non-tech company that wants to now take on larger software projects finally can, and they’ll hire to do so. The small business that couldn’t afford a full marketing agency can hire or contract out to a marketer that can do as much as an agency did before now with agents. And so on.
Don’t fall into the trap of confusing tasks with jobs.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
I read through this twice. It's so well done.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
This is good
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Very high IQ high perception conclusion and execution. This is exactly what should be happening
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
this was probably my favorite read on AI this year. kudos to Dan for writing it
his core point:
more AI = more work for humans, not less
this seems to be universally true: AI is helping everyone get more done, but me and everyone i know is working more than ever, not less
here's why that's happening:
1. AI is really good at the stuff humans used to be good at. writing, coding, design, research. it can do all of it now, fast and cheap
2. so everyone starts using it. the person in customer support is shipping code. the engineer is writing blog posts. the marketer is making videos. way more stuff gets made
3. but everyone is using the same AI. so the stuff it makes all starts to look the same
4. when everything looks the same, people get bored of it. they can smell it a mile away. it becomes worthless
5. so now what's valuable is the opposite. stuff that doesn't look like everything else. stuff that's actually good. stuff that fits the exact moment
6. and the only one who can do that is a human who knows what they're doing. someone who can look at what the AI made and say "this part is good, this part is bad, do it again like this"
7. that human now has way more work to do than before. because the AI is making 10x more stuff, and all of it needs a human to make it actually good
you can see this play out every time a new AI model drops.
people panic that the jobs are gone.
but the same thing happens every time. the AI gets really good at the part of the job that used to be hard.
that part becomes easy and cheap. and the humans who used to do it move up to a new harder part the AI can't do yet
example: writing a decent blog post used to be a skill. now AI can do it in 10 seconds. so the human job moved up a level.
now the skill is knowing which blog post to write, who it's for, and whether the one the AI wrote is actually any good
the bar keeps moving up. the humans keep moving with it
even when AGI shows up, someone still has to tell it what to work on and check if the work is any good
the easiest way to see why is to think about a toddler for a second.
a toddler can't write code, can't summarize a spreadsheet, can't pass a single benchmark. the AI beats him at everything
but the toddler wants stuff.
he wants to poke the balloon with a fork. he wants to see if you'll laugh when he throws his food. he comes up with his own little experiments all day long
the AI doesn't want anything. it just sits there until someone tells it what to do
that gap doesn't close.
the AI can do the work. but a human still has to be the one who wants something done in the first place, and who decides if what came back is actually what they wanted
at Every (Dan's company), they've automated everything they possibly can.
and they have more human work to do than ever. that's the proof
the people who win this are the ones who get good at directing the AI.
> telling it what to work on > checking if the work is any good > and pointing it at problems nobody has figured out how to solve yet
that's the new skill.
not doing the work yourself, but rather knowing what work is worth doing and whether the AI actually did it well
read the full piece, it's worth it
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Excellent essay! Well worth reading.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
read the PDF: https://every-s-manifesto-production.up.railway.app/after-automation.pdf
read on @every: https://every.to/p/after-automation
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Core argument is that AI commoditizes yesterday's competence, which creates sameness, which creates demand for difference. A few loose thoughts:
1. Dan says the value moves to the "framer," the human who supplies live judgment that the model can't generate. How do you keep the "frame" consistent across an organization? 2. The frame problem is a narrative problem before it's a talent problem. A company without a worldview has no basis for distinguishing its AI-assisted output from anyone else's. 3. This is why I'm less excited about "10x employees" or whatever the new meta is. Hiring competent people doesn't solve the slop problem at scale. Individual taste compounds only against a company's philosophy of business. 4. Who is building the narrative infrastructure to frame every output against what they actually believe?
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Will there be an AI jobpocalypse?
My view gyrates wildly—depending on my mood and who I talked to recently
I think this is totally reasonable
No one in tech has special training or insight on future employment trends
Economists have some training, but they’re uncertain too 🤔
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Why human work is very important! Love this read
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
You’ve felt it too… the past 2 years is the most you’ve ever worked. What happened to AI automating our jobs?
We feel this intensely at Every. Long days, lots of new hires, ever expanding scope.
AI enables us to do more, which in turn makes more work for us, because humans are always one step ahead of our models.
Behind every agent is a human…
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
CEO of Every @danshipper says AI increases the demand for human experts because it provides "cheap competence" that only humans can turn into valuable, differentiated work.
What he said:
"Every agent needs a human. The further away an agent is from a human who's doing it, the worse it does."
"You also see this inside the scaled AI companies, like OpenAI or Anthropic. They have company-wide bots that you can @, but they're run by teams of people."
"And I think that's a really interesting, and pretty stable phenomenon based on how these agents work."
"AI collapses tasks that used to take hours into a few minutes, but the human is like a sandwich on either end. Bookending the process, framing the task, or evaluating it when it's done."
"Even though AI can do expert human work, it actually increases the demand for human experts."
"You can get pretty good writing, images, or code [from AI]. But it's all based on yesterday's competence. It's all based on what's in the training data from yesterday."
"What that does is it floods the market with PRs, images, or writing that's kind of good, but not quite right for the situation. And what you need are human experts to come in and take the cheap competence that AI enables anyone to have, and turn it into actually good, valuable, differentiated work. Otherwise it's just the same thing everybody else is doing. And it's not valuable."
"That's a dynamic inside how the models work — and how they function in the economy — that kind of gets lost when people are worried about it being able to do all this great stuff."
"It can, but in order for that great stuff to be valuable, it needs to be done by a human."
Yeeeees- I’ve been so wanting someone to write basically this exact article, and of COURSE you were the perfectly suited person to write it, @danshipper!! 🙏🏻☺️👏🏻
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Dan is so far ahead of the rest of us sometimes.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
Finally a positive take on automation
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
must read as everyone strives to agentify their orgs at rapid pace - more humans needed as more work and more decisions to be made - counter to prevailing narrative
also reminds me of this - "a computer can never be held accountable"
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
"Every agent needs a human. The further away an agent is from a human who's doing it, the worse it does.
Even though AI can do expert human work, it actually increases the demand for human experts. "
~ CEO of Every @danshipper
this tracks with my experience too. Using AI amplifies the information throughput, which results in a need for far greater cognitive + emotional capacity from the humans in the loop.
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
.@danshipper has consistently led on AI and this is a glimpse at what’s next.
Take the time to read it then use the agent mode to deep dive.
You’ll be 6 months ahead of competitors
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://every.to/p/after-automation
