People don’t know what work should look like next, but everyone has a slide deck about it.
Here are a few models worth thinking about, some real, some hypothetical, and some slightly absurd.
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Maximize time off. Work when you want, where you want. Sounds liberating. Requires a very specific kind of person to thrive in it. Culture fit isn’t a buzzword here, it’s load-bearing.
Maximize profit. Work as a machine. Efficient, disciplined, predictable. Some people actually want this. They like the structure. The cog knows where it fits.
Organize around innovation. Tasks get done, but the real currency is exploration. Output is balanced against discovery. The tension between the two is the whole game.
Flip the org chart. Leaders at the bottom, enabling everyone above them. The least experienced people organize as they see fit. AI matches tasks to skills in the background. Management fades into infrastructure, present but invisible, like plumbing.
The empowered individual. Everyone manages a team of agents. You only do work that aligns with your abilities. AI routes everything else to someone better suited for it. Not your problem.
Humans at the center. Slow, deliberate, intentional. AI runs in the background like electricity, available when you need it, invisible when you don’t. Decisions take longer. They hold up better.
The anarcho-syndicalist commune. For fans of Monty Python and the Holy Grail, work is organized by AI but governed by rotating committees and collective decision-making. Supreme executive power derives from a mandate of the masses, not some farcical aquatic ceremony. Unclear how the sprint planning works.
The task marketplace. Sign in. Complete tasks. Get paid. Log off. Fiverr and Upwork already live here. The question is whether this scales into something that looks like a career or just an endless series of gigs with no throughline.
Place and community. Hyperlocal work ecosystems where your contribution stays within a geographic radius. The opposite of remote-everything. Work tied to where you live, the people around you, the problems in your immediate environment. A return to the village, but intentional.
Life stage work. The structure of work shifts depending on where you are in life. Early career looks different from mid-career, which looks different from late. Not a ladder, more like a series of different games with different rules at each phase.
Contribution cycles. Intense periods of deep work followed by deliberate rest, learning, or exploration. More like an athlete’s training schedule than a 40-hour week. Output measured in bursts, not hours logged.
Scarcity and need. Work is allocated around what society actually needs most, not what the market values most. Teachers, caregivers, and infrastructure workers are organized differently than growth-at-all-costs roles. A needs-first model.
Work as commons. People contribute to shared public goods — open source, community infrastructure, civic systems — and receive a basic floor of support in return. Tied to contribution, not just existence.
Work as craft. Slow, mastery-focused, anti-scale. The opposite of optimization. AI handles the volume, humans return to the discipline of doing one thing extraordinarily well. What the Japanese have known about for centuries.
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The list could go on. But before we pick a model, a few questions probably deserve an answer first.
What work is actually worth doing? What do people genuinely need to function, not just economically, but as humans? What happens to the people who want none of this, no infrastructure, no AI, no grid? As the AI layer evolves, who decides how it evolves, and in whose interest?
The model matters less than the answer to those questions.
We keep designing the system before we’ve decided what it’s for.
