University degrees will need a radical reshape. Here are four new Bachelor's Degree programs that we may need after AI

The infamous, terrifying Anthropic Economic Index, March 2026.

I'm making a biweekly LinkedIn newsletter about the commodification of intelligence. Thos affects all of us professionals in strategy, design, innovation, creativity and intellectual work. What changes? What remains? What to do next?

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# The Humanities and Social Sciences have non-human thinkers now

Most university programs were designed to train people for a world where intelligence was scarce and expensive. You went to school to become the person who knew things (the one who could research, analyse, synthesise, and produce a coherent output that others couldn't produce on their own). That was the value proposition of higher education for the better part of a century, and it worked.

It's hard to think of the role of University and how the focus on what is learned needs to change after commodified intelligence. It's time to speculate.

The problem is that this core value (knowledge) now also applies to a $20-per-month subscription. Does it mean the entire University experience is replaceable? No. The immersion and social connections that happen in that time, for example, cannot be exchanged by an AI subscription. But if University needs to form people for the upcoming civilizational challenges we have, what needs to adapt?

The Anthropic Economic Index, published earlier this month, maps where AI is already displacing cognitive work. And that's only the language-and-reasoning layer. It doesn't account for computer vision reshaping transport and logistics, or autonomous systems changing manufacturing, or biotech rewriting what laboratory work looks like. Each of these is commodifying a different capability. The cumulative effect is that a very large portion of what higher education currently trains people to do is becoming a commodity input.

# How should we redesign a bachelor's degree from scratch?

So if you were designing a bachelor's degree from scratch — not retrofitting an existing program, not adding an "AI module" to a business degree, but starting from a blank page — what would you build?

I've been thinking about this, and I want to share four programs that I think address the gap. A few things worth saying upfront about scope. These four focus on a specific cluster: the space where intellectual, strategic, and governance work used to live, and what needs to replace it now that the production layer is dissolving. They don't cover the hard sciences, the physical trades, the care professions, or the arts as practice. Those need their own rethinking, and other people are better placed to do it. What I'm interested in is the territory that my work already touches — the layer of judgment, orchestration, meaning, and systemic navigation that becomes more valuable precisely because intelligence got cheap.

With that said, here are the four.

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# Systems Governance

A law degree teaches you to navigate a civic system designed by and for humans. That's still useful, but it's increasingly insufficient. The systems we need to govern now include AI agents making decisions at speed, algorithmic markets, autonomous infrastructure, and synthetic media — alongside human citizens who are trying to make sense of all of it.

Systems Governance takes the core of law, public policy, and political science and recombines them for this reality. The curriculum would include institutional design — how you build rules, incentives, and boundaries for complex systems with non-human actors. It would draw on game theory, constitutional theory, and ecology, because ecological thinking remains our best available model for understanding how complex adaptive systems behave. Ethics would be taught not as abstract philosophy but as applied constraint design — the practical discipline of deciding what a system should not be allowed to do, and building that into its architecture.

The graduate isn't a lawyer. They're someone who can walk into a city, an industry, or a government and design the governance layer for systems where intelligence is distributed and abundant, and where the difficult problem is no longer "who knows the answer" but "who decides what counts as the right question."

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# Decision Architecture

In a post-AI world, the scarce resource is not analysis. AI can produce ten valid analyses in the time it used to take a team to produce one. The bottleneck has moved from "we don't have enough information" to "we have too much information and no reliable mechanism for choosing."

Decision Architecture replaces management, parts of design thinking, and behavioural science. The curriculum would include cognitive science — specifically how humans actually make decisions under uncertainty, which is quite different from how economic models assume they do. It would include information design: how to present complex material so that decisions improve rather than stall. It would include facilitation and orchestration — the discipline of moving a group of people from information to alignment without manufacturing false consensus. And it would include deep AI literacy, not as coding but as a rigorous understanding of what these systems can and cannot do, where they're reliable, where they hallucinate, and how to design the boundary between human judgment and machine output.

The graduate is the person who doesn't produce the analysis but who decides when the analysis is sufficient, which direction to pursue, and how to move a room from data to commitment. That role exists today in fragments — scattered across strategy consultants, product leads, senior designers, and the occasional executive who's good in a room. This program would train it deliberately.

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# Meaning Design

This might be the most counterintuitive one, and I think it could be the most important.

In a world where AI can generate convincing arguments for any position, produce beautiful prose, compose music, and design visual identities, the scarce capability is not production. It's discernment. The ability to look at ten well-crafted options and know which one actually resonates — not just functions — for this audience, this moment, this context. Understanding why a particular framing moves people while another, equally well-constructed one, doesn't.

Meaning Design takes what the humanities were always supposed to do — teach people to think critically about narrative, knowledge, value, and representation — and builds it into something with applied force. The curriculum would include rhetoric and narrative theory, epistemology (which becomes urgent when AI can produce plausible-sounding versions of anything), aesthetic theory and the deliberate development of taste, anthropology, and semiotics. The applied component would put students to work designing communications, experiences, brands, and cultural interventions that create shared understanding in a saturated information environment.

The graduate is someone who can create meaning — not content. Every organisation, government, and movement will need this capability, and almost none of them currently know how to hire for it, because it didn't previously exist as a named discipline. It was scattered across philosophy departments, design schools, and advertising agencies, and none of those places treated it as the core skill.

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# Transition Design

This degree does not have an existing equivalent at all.

The premise is that the world is going through continuous, accelerating structural change, and the biggest risk is not that the change happens but that existing systems — cities, industries, institutions, entire professions — collapse during the transition rather than adapting through it. Someone needs to be skilled at managing the passage itself. Not predicting the future, not building the replacement, but helping what exists survive transformation without losing the things that matter.

The curriculum would include systems dynamics and modelling, scenario planning, resilience engineering (borrowed from ecology and disaster management), economic transition theory, change psychology — how individuals and groups process structural disruption, including all the bike-shedding and self-sabotage patterns I wrote about last week — and design for adaptation: how you build organisations and infrastructure that can absorb shocks and reconfigure rather than shatter. The applied component would place students inside real transitions: a factory automating its workforce, a city redesigning its transport grid, an industry whose business model has just been invalidated.

The graduate doesn't tell you what the future looks like. They help you survive the passage from here to there.

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# Seeing is more important than knowing

The thread that connects these four is that none of them are primarily about knowing things. They're about seeing what matters, making decisions under genuine uncertainty, building shared understanding, and navigating change. These are the capabilities that become more valuable as intelligence becomes cheaper — because they were never really about intelligence in the first place.

I'll be going deeper into each of these in the coming weeks. If one of them resonates more than the others, or if you think there's a cluster I'm missing entirely, I'd like to hear about it.

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