What Humans Do Next
On 5 types of human work in the gentle singularity.
In The Relationship Is the Job, I argued that relational labor — the work of presence, context, care, and ultimately, trust — will be central to working with people as manual and cognitive tasks are automated. This essay extends that thinking about the future of human work amidst the many predictions about an AI-dominant world.
The Artist’s Utopia Fantasy
The AI kings keep promising us the same fairy tale: humans won't need to work at all, that we'll spend our days creating art while robots handle everything else.
On a long enough timeline, maybe. It's one of those unprovable predictions where skeptics can always be told they're "still too early."
But there’s been a notable shift recently. We've pulled back from the breathless talk of imminent, world-ending AGI. The conversation has turned to something more calming to the nervous system: Sam Altman’s "gentle singularity" — a gradual progression where humans and machines coexist and co-contribute:
The rate of technological progress will keep accelerating, and it will continue to be the case that people are capable of adapting to almost anything. There will be very hard parts like whole classes of jobs going away, but on the other hand the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before … If history is any guide, we will figure out new things to do and new things to want, and assimilate new tools quickly.
Five Domains of Human Work
We've invented superintelligence of some kind, but I'm skeptical about how fast it replaces human-run systems. Machines become the "core" of operations, but we'll still need a "human layer" in every domain. The digital singularity arrives before the physical one, both with humans in the loop.
The question isn't whether humans will work, but what kind of work humans do in the ‘gentle singularity.’ It's not just art, and creativity isn't the only skill we'll need. Human work will live in Trades, Research, Art, Community, and Stewardship.
1) Trades: when lawyers look like electricians
The lawyer billing $1000/hour and your electrician, the surgeon and your auto mechanic: each pair will soon have more in common than you think.
When cognitive work gets automated, everything starts looking like trade work. Traditional "blue collar" trades like plumbing and electrical work persist and improve, with AI increasingly handling diagnostics and business operations while humans handle problem-solving and customer interaction. "White collar" professions (doctors, lawyers, engineers, accountants, therapists) start resembling trades. Reasoning gets automated while judgment and relationships stay human.
Machine core, human layer. This is the organizational paradigm of the future. Machines think better than us but can't truly be us. If software engineers all used to be inventors, now they’ll be operators. Humans orchestrate and polish; machines man the middle. You might still sit in an office behind a laptop, but the work becomes more procedural over cerebral and intertwined with people and context.
New trade-like roles emerge: AI trainers, workflow engineers, system monitors. Operating AI systems, not just designing them. The four-year degree as pre-requisite will give way to trade schools. Education is replaced with apprenticeship. When knowledge has a half-life measured in weeks and months, adaptation becomes everything.
2) Research: the golden age of human curiosity
We're about to enter the golden age of human curiosity. When research becomes faster and cheaper, we ask bigger questions and pursue bolder answers. AI will unleash R&D everywhere it's been bottlenecked — whether opaque, slow, expensive, or all of the above. We'll see big leaps in technology, health science, longevity, materials research, space exploration, even consciousness studies.
The most interesting work today is already happening at the research frontier. The top engineering jobs aren't about coding features anymore — they're about figuring out how cutting-edge AI actually works, training models, assessing risks. OpenAI is as much a research company as a tech company as a consumer product company. Executives leave to start rival research labs; employees get poached for their research genius. Either way, investment flowing into research is massive — expect frontier tech companies to look and act more like “science” companies.
Humans remain the essential question-askers. Trades execute within known systems; research pushes into uncharted territory, exploring the unknown. You can't automate what you don't yet understand — what’s as much art as science. The AI 2027 manifesto calls this "research taste." AI matches top experts at research execution but only hits the 25th percentile at "deciding what to study next, what experiments to run, or having inklings of potential new paradigms."
Eventually research becomes more trade-like too, but on a much longer timeline. The advantage will belong to whoever can spot the hardest unsolved problems, build models to attack them, and iterate quickly — whether that's an independent researcher, a startup, or a trillion-dollar company.
3) Art: the power laws of creativity
When we automate away so much of what we do, what's left but fostering beauty, reflection, and connection in the world? We'll make more art, yes. But we call art our last refuge as if it's the only thing that lacks utility, when it's loaded with it.
Art isn't just traditional fine art like painting and sculpture. There's art we consume like books, music, movies, podcasts. There's experiential art like concerts, theater, and dance, where live performance is everything. There's also vast applied art like designing websites, apps, phones, clothing, buildings. The masses crave "entertainmeaning" — the alchemy of entertaining and meaningful.
So much of "art" is and will be about influence and attention: creators building audiences, shaping culture, directing where people look and what they value. The biggest economies of our time revolve around the media-machine fusion. Creating "content" as an endeavor will never fade. But the economic reality is that art follows brutal power laws—few artists capture most attention and value.
Better tools give us leverage, but art is defined by its humanity. It wants a human signature, a point of view that machines can't replicate. In the future, art becomes even more personal, more participatory, more defined by its human lore — not just individual masterpieces but bodies of work with novel aesthetic frameworks.
Not all 8 billion of us will make our living from traditional art, but creation will be central to our lives. Local art becomes valuable via experience and presence, not global scale. Human art becomes an artisanal good with unique value. Making something meaningful and being valued for it is always how humans find purpose.
4) Community: 8 billion local creators
The dominant non-utilitarian work will be what I call "local social craft." The real opportunity isn't everyone making art — it's everyone building community. The future we think of as an artist's utopia may actually be a community builder's utopia.
