AI Will Kill Packaged Meaning. Let It.

In Part 7: We’re Less Than a Decade From the Next Economic System, I showed why the next economic system is less than a decade away, and what history says we should have ready when it comes.

But a map of the economy skips the question most people actually ask when they hear about machine labor. If the machines do the work, what am I for?

This is Part 8 of The World We Want, and the last part of Book One. It’s condensed from a piece I published in April.

So, Sam Lessin wrote the most important essay I’ve read about AI this year, and I agree with every word of it. If you’ve read it too, then that statement might terrify you. But I think what he’s saying is actually good news, because it’s only after we accept his diagnosis that we can start building the cure.

His essay is called “AI Is Not a Labor Crisis. It Is a Meaning Crisis.” The warning at its center is blunt: kill human meaning “and you eventually kill human civilization.”

If you haven’t read it, here’s the short version.

Sam’s argument in five points

There are three paths to meaning. Drawing on Viktor Frankl, Sam identifies Creation, Pleasure, and Dignity in Struggle as the three ways humans generate purpose. All three are achievable today, but they’re hard. Most people struggle to organize their lives around any of them (at least consistently).
Civilizations solved this by packaging meaning at scale. First through religion (“your life will be hard, but it has meaning after you die”), then through the industrial narrative (“your life will get better if you work hard, and your kids’ lives will be even better”). These “retail” forms of meaning gave ordinary people a story to live inside without having to generate purpose from scratch.
The industrial meaning story was already cracking before AI. The Mike Mulligan problem: being strong and willing to work stopped being enough decades ago.
AI is the nail in the coffin. AI either tells people they can stop striving and still receive abundance (which removes the purpose from the industrial story), or it tells them the ladder is gone and their striving no longer matters (which is even more demoralizing). Both options kill meaning (in the traditional, pre-packaged sense).
Creation and pleasure won’t save us either. Prompting tools alongside everyone else isn’t a unique expression of the individual. And after you’re fed and housed, more massages and sunsets won’t solve the meaning problem.

Sam then lays out four possible futures: a return to religion, a fragmentation into cults and micro-communities, billionaire Star Trek missions that leave most people as passive spectators, or Frankl’s dignity-in-suffering path, which Sam respects but doubts can scale.

He finds none of them fully satisfying. I think he’s right about that too.

But I think there’s a fifth option he didn’t see.

Packaged meaning was always a crutch

Sam’s core insight is that AI destroys meaning. I’d sharpen that: AI destroys packaged meaning. The industrial narrative, the story that hard work leads to a better life for you and your children, was always a proxy for meaning, not meaning itself. What Sam calls “retail meaning” is meaning-as-a-service: institutions packaging purpose so individuals don’t have to generate it themselves.

The industrial narrative worked because it happened to align personal striving with collective progress. AI breaks that alignment. The striving and the progress decouple.

But here’s what Sam’s analysis reveals when you look at it from the other side: the people who found the most meaning during the industrial era were never living off the packaged version anyway. They were the doctor who loved medicine. The teacher who cared about students. The engineer fascinated by the problem.

They had real meaning through Creation, through Dignity in Struggle, and through two important aspects of humanity I think Sam left out: genuine Curiosity (pursuit of knowledge) and genuine Care (service: fulfillment in helping others).

So the question is: can we build infrastructure that helps people generate real meaning at scale in an AGI-pilled world?

Viktor Frankl, the psychiatrist who survived the Nazi camps and wrote Man’s Search for Meaning (1946), described three avenues to meaning: the things we do, the things we feel, and “the stance we take toward situations.” Can we make those accessible to ordinary people, instead of just the self-directed few?

I believe we can. And I believe the answer lies in two traits so fundamental to being human that no AI can automate them away: curiosity and care (service).

Purposelessness is dangerous

Meaning is purpose. And people who are purposeless are the most dangerous people on the planet.

Purposeless, disaffected young men are more likely to commit violent crime and terrorism, and to engage in all sorts of other reckless, self-destructive behavior. Henrik Urdal’s 2006 study of “youth bulges” found that large generations of young people raise the risk of armed conflict, terrorism and rioting. The absence of purpose doesn’t produce peaceful idleness. It can often produce rage, addiction, radicalization, and despair.

Once machine labor covers the work nobody chooses, most of us get our time back. On the individual level, this could be great. On the society level, it could be very dangerous. A bunch of purposeless people walking around trying to find something to do all day? We’ll need structures to guide this.

The structure I find most satisfying is something Sam buries in his notes at the very end, almost as an aside. He writes that the coming meaning systems may look less like “belief” and more like:

Identity + Ritual + Boundary + Mission.

He’s right. And I think I know what that looks like in practice.

Identity, ritual, boundary, mission

Let’s break it down:

Finding identity in the pursuit of a mission. That’s purpose.
Rituals are how we define the tactics of pursuing that mission.
Boundaries are the physical constraints of the mission itself, or the emotional, intellectual, and philosophical constraints we apply to it, including who we decide to ally ourselves with and who we decide to let in.

Sam writes that our local community used to apply these boundaries for us. I believe the local community needs to become more important again as a central, grounding feature of the world we live in.

Perhaps you can turn off the global internet and focus on the local net, the network of people in your immediate surroundings, and pursue rituals that improve the spaces you actually inhabit instead of focusing your attention on places you’ll never visit and arguments you’ll never resolve.

After all, the popular ”Dunbar’s number” theory, from the British anthropologist Robin Dunbar, proposes that you can really only maintain a cohesive community of about 150 people. Unfortunately, the modern world has made us locally isolated, and so our villages are digitally united by group chats and friends lists instead of our immediate neighbors.

For some, the local net will be enough. But it can be rare to find neighbors you genuinely connect with over shared interests, while it’s relatively easy to do the same online. You can’t “block” or “hide” a neighbor unless you physically shut your blinds. So it could turn out that, just as people used to move for a job, people begin to move for a purpose.

My first post on this blog introduced one version of this, which I called Data Foundries: places where people learn, practice and contribute to a shared body of human knowledge, each one built to supply identity, ritual, boundary and mission. I see this as a potential stepping stone between our current system of schools, jobs, and older institutions, and whatever comes next.

That first version pictured campuses people would move into. I’ve since rethought it as a workshop in your own town, and that’s the version I’d build, in Part 20: Get Paid to Train the Robot That Takes Your Job.

The two things AI can’t automate

Sam’s point is that we can’t help but imagine the future, which is why AI is a meaning crisis. Why do we do this to ourselves? Because our survival relies on us predicting the future. Curiosity, the drive to think, and therefore predict, and ultimately understand, is our most important capability. It keeps us alive.

AI doesn’t make curiosity less meaningful. It makes curiosity more accessible. Right now, if you’re curious about quantum physics, but work as a cashier, you’re stuck reading Wikipedia at night. In a world designed around learning and sharing knowledge, you pursue that curiosity full-time, with an AI tutor, with others who share your interest, documenting everything you learn along the way.

Sam would push back here. He’d say: if AI already knows quantum physics better than you ever will, what’s the point of you learning it? You’re just a hobbyist. And this is his strongest argument. But I think it rests on a confusion between meaning and competitive advantage.

The point of learning isn’t to know something the AI doesn’t know. The point is that you didn’t know it, and now you do. Meaning comes from personal growth, not from market position. The marathon runner doesn’t run because cars don’t exist. The chess player doesn’t play because computers can’t beat them. They do it because the struggle, the improvement, the mastery, that’s what being human feels like.

What Sam calls “dignity in suffering” doesn’t require that the suffering be economically productive. It requires that it be chosen and purposeful.

And here’s the critical difference between this vision and Sam’s “drugged out VR pleasure pods” scenario: this preserves struggle. Learning is hard. Mastering a craft is hard. Pushing your physical performance is hard. This doesn’t eliminate difficulty. It redirects difficulty from surviving to growing.

And then there’s care, or service. Many people get purpose from serving others, or even just from the act of being in community. That’s important and deeply human.

So if I had to distill my entire argument to its finest point: following our curiosity and helping others should be our two defining organizing principles going forward. If we can align our social contract around maximizing these two things, we can all be better off for it.

This is the human-will rule from Part 2: If a Human Wants to Do a Job, a Machine Shouldn’t Take It, seen from the inside: “if a human wants to do it, a human gets to do it.” Curiosity and care are what humans will want to do. And they map onto the two organizations from Part 4: Quests Should Replace Corporations. You join a guild to follow your curiosity into a craft. You form a party to serve a goal bigger than yourself.

I fundamentally don’t believe that AI changes either of these. You will always be curious. You will always want to help the people you care about. Everything else is scaffolding around those two impulses.

Why profit alone is the wrong organizing principle

What is profit, really? Taking in more revenue than you pay out in expenses. It’s required for any entity to survive. You must retain more energy than you spend… or you die.

So while yes, companies today answer to their shareholders and are expected to pursue profit, why is that the defining organizing principle of our modern world? Could a model that holds profit important only insofar as it serves the central mission also work? Could it offer us a better world?

Production vs extraction

Profit itself isn’t the problem. How it’s made is.

Some companies make things. Others make money by standing between you and the things you need.

Economist Mariana Mazzucato calls this the difference between value creation and value extraction. Creating value means combining resources into something new: a medicine, a bridge, a better tool. Extracting value means moving existing things around and taking a cut far bigger than what you added.

This isn’t a radical idea. Adam Smith, the founder of free-market economics, wrote that landlords “love to reap where they never sowed.” John Stuart Mill said they ”grow richer, as it were in their sleep.”

Sitting in the middle isn’t the problem. Plenty of middlemen earn their keep: they move goods, catch fraud, and help buyers find sellers.

A middleman becomes extractive when its cut is set by its control of a chokepoint, not by what it adds.

Take the companies that manage prescription drug benefits. The three biggest handle about 80% of American prescriptions, and the FTC found they marked up some specialty generic drugs by hundreds or thousands of percent, taking in $7.3 billion in extra revenue from 2017 to 2022.

Or take finance itself. Economist Thomas Philippon found that moving money through the financial system has cost about 2% of the money moved, every year, since the 1880s. Computers made nearly every other kind of information cheaper. That fee held steady.

And when companies do earn a profit, more of it goes back to shareholders than into making things. From 2003 to 2012, the biggest American companies spent 91% of their earnings on buying back their own stock and paying dividends.

In the year to September 2025, S&P 500 companies sent a record $1.7 trillion back to shareholders. To be fair, many of the same companies are also pouring money into AI data centers right now, and that’s production. But the steady pull is toward paying out.

Extracted money doesn’t vanish. It goes looking for something to buy, and most often that’s what already exists: stocks, homes and land. It bids those up instead of building something new.

So why do companies drift toward extraction? Most people assume the law forces them to maximize profit. The truth is subtler.

Day to day, it doesn’t. Courts let directors pass up profit for almost any reasonable long-term reason, under what lawyers call the business judgment rule.

But in Delaware, where most big American companies are incorporated, a for-profit company’s directors must ultimately serve their stockholders. When craigslist’s founders put their community ahead of shareholder value, eBay sued, and in 2010 the court sided with eBay: “The ‘Inc.' after the company name has to mean at least that.”

And when a company is sold, its directors become, in the Delaware Supreme Court’s words, ”auctioneers charged with getting the best price for the stockholders.”

The rest of the squeeze comes from outside the law: executive pay tied to the share price, activist investors, takeover threats, and the quarterly earnings call.

Underneath all of it sits one quiet default. Unless its charter says otherwise, a corporation lives forever.

A company that lives forever and answers to its shareholders has one job that never ends: keep the returns growing.

Public benefit corporations were meant to fix this. They’re for-profit companies with a public mission written into their charter, and in Delaware the mission can’t be making money for shareholders.

But only shareholders with at least 2% of the company, or $2 million of stock in a public one, can sue to enforce that mission. There are no money damages, and since 2020 a simple majority can vote the mission away.

In April 2026, Allbirds, a public benefit corporation and certified B Corp, announced a pivot from shoes to renting out AI chips, and asked its shareholders to drop its environmental mission.

A company built for production needs two things a PBC can’t give it: a finish line, and a mission its members can enforce.

That’s not a new idea. It’s the original one. The English East India Company, chartered in 1600, financed its first twelve voyages one at a time: investors paid in for a single voyage, split what it brought home, and wound it up.

In America, about two-thirds of the 319 business corporations chartered before 1801 were bridges, canals and turnpikes. Each was created for one named purpose, and most for a set number of years. The single-use companies of Part 4 are a return to form.

Then a company adds a feature because it makes the thing better. Profit tells you people want it. It isn’t the reason the thing exists.

Keynes saw where this leads. He argued that people who live off owning capital get paid because capital is scarce, and that once it’s plentiful, their hold fades on its own. He called it ”the euthanasia of the rentier.”

That’s the bet of this whole series: make the things abundant, and extraction loses its grip.

Mission first

Consider how the leading AI companies have structured themselves.

Anthropic is a Delaware Public Benefit Corporation whose stated purpose is “the responsible development and maintenance of advanced AI for the long-term benefit of humanity.” It created something called the Long-Term Benefit Trust: an independent body of financially disinterested members with the power to elect a growing share of Anthropic’s board. As of April 2026, the Trust’s appointees make up a majority of that board.

OpenAI went through its own dramatic restructuring. In October 2025, it converted its for-profit arm into a Public Benefit Corporation called OpenAI Group PBC, controlled by the nonprofit OpenAI Foundation, which holds roughly a 26% stake and appoints all of the PBC’s board members. In March 2026, the Foundation said it expects to invest at least $1 billion over the following year, as early steps toward a $25 billion commitment to curing diseases and AI resilience.

Notice the direction this is heading? Traditional corporations optimize for profit only. B-corps and PBCs balance profit with mission. The next evolution is an entity where the mission and the economic engine are the same thing.

That’s what I meant in Part 4, when I wrote that where a corporation answers to shareholders, “a party would have what’s called a charter obligation to complete the quest it’s on.”

This doesn’t have to look like work in the traditional sense. It might look more like work in the nonprofit sense, or the volunteer sense. Like the Peace Corps, or AmeriCorps. Except it’s permanent, it’s self-sustaining, and it scales.

In Part 4’s terms, the permanent part is the guild, which runs the standing services. Parties come and go with their quests.

And in a future of material abundance, attention will be the final finite resource, so what you dedicate your time to will naturally give it value.

Sam’s four futures, synthesized

What I’m describing borrows the best parts of three of Sam’s four scenarios while avoiding their failure modes:

From religious revival, it takes the power of shared narrative, ritual, and community. But the narrative is open-ended (the pursuit of knowledge) rather than forced into some fixed doctrine. It doesn’t require belief in the supernatural, though it doesn’t exclude it either.
From cults and micro-communities, it takes the power of chosen boundaries and niche identity. But it connects these communities through shared infrastructure and trade, which prevents isolation and hostility. You choose your community, but your community remains interdependent with others.
From dignity in suffering, it takes Frankl’s insight that meaning comes from chosen struggle toward a purpose. But it makes that struggle accessible and structured, with mentors, AI tutors and a community of practice, instead of leaving each individual to figure it out alone. Which is exactly what Sam says is needed but doubts is possible.

The one scenario it doesn’t incorporate is billionaire Star Trek, and for good reason. Sam himself identifies its fatal flaw: you just don’t need most people for these missions, which makes everyone a passive consumer of someone else’s narrative. This model inverts that. Everyone contributes. Everyone’s curiosity matters. There are no spectators.

If billionaire Star Trek quests are what some choose to pursue, they are welcome to. After all, what’s the point of all that knowledge if you don’t put it to use advancing human civilization into the stars? My bias, of course.

What about the people who don’t want any of this?

Let me be direct: not everyone will find this compelling. Some people don’t want to learn. Some people want to be told what to do (even if they won’t admit it). Some people DON’T want to be told what to do, and find this idea repulsive on merit. Some will see a utopian fantasy that ignores human laziness, selfishness, and cruelty.

Fair enough. This is an opt-in system, not an escape-proof one. The traditional economy continues for those who prefer it. Traditional religion continues. Traditional communities continue. You can leave anytime, no questions asked.

The catch is that a whole society never does anything one way. So the best path is a decentralized network of networks, interacting with one another, exchanging information and resources and time to pursue their unique purposes. Some high-tech and rapid-learning focused. Others contemplative, low-tech, and slow. Some traditional. Some radically experimental. It would be a system of many models, not one.

But here’s what I believe: when you offer people the choice between a system that says “your striving no longer matters, here’s a check” and a system that says “your curiosity is valuable, your growth matters, here’s a community that will support you while you pursue what interests you most and share what you learn with others,” most people will choose the second one.

Because that’s what humans actually want. We want to grow, and we want to matter.

Build it before the old story collapses

Sam is right that AI kills the industrial meaning story. He’s right that creation-through-prompting and pleasure-through-abundance won’t fill the void. He’s right that we need something new.

But what we need isn’t a new version of packaged meaning. What we need is infrastructure that makes real meaning accessible. Communities of practice built around curiosity and service. A shared mission broad enough to include everyone. An economic model where contribution and purpose are the same thing. And the honesty to admit that this will be messy, imperfect, and will require decades of iteration.

The networks we build must encourage sharing at the system level and serving at the local level.

We could build this. A world where humans stay intellectually engaged at the frontier while AI handles the repetitive work. Where you choose your purpose, your pace, and your community.

The tools to build it exist today. The need is urgent. The meaning crisis Sam describes is real, and it’s accelerating.

The question is whether we build the alternative before the old story finishes collapsing.

That’s where Book Two picks up: what living in this world actually looks like, starting with the planet itself, in Part 9: The Earth Should Be a Garden, Not a Mine.