I have been wondering how AI will change jobs. Not just in general, but concretely: how will roles look like in the future, which ones split apart, which new ones emerge. Most of what I've read on this has been disappointing. "X% of tasks will be automated" is not an answer. Breaking jobs into tasks and checking which ones AI can do is just Taylorism with a new label.
Sangeet Paul Choudary's Reshuffle is the first book that gave me a framework I actually found useful. Back then I enjoyed Choudary's book Platform Revolution (2016, co-authored with Geoffrey Parker and Marshall Van Alstyne), one of the foundational works in platform economics. So, I had a lot of expectations.
Fair warning: this is more of a structured summary with commentary than a traditional review. The book has a lot of ideas worth unpacking. I'll walk through the three hypotheses that stuck with me most, add my own take where I extended Choudary's thinking.
What the Book Is About
The Big Reframe: Coordination, Not Just Automation
The central argument of Reshuffle is deceptively simple: we've been thinking about AI's economic impact through the wrong lens. Most discussions focus on AI as a tool for automation, taking over tasks and processes. Choudary argues that the far bigger impact will come from AI as a tool for coordination, enabling components of an economy to specialize, align, and scale in ways that weren't previously possible.
His anchor metaphor is the shipping container. The standardized steel box didn't just make loading ships faster. It enabled outsourcing to low-wage countries, allowed companies to specialize, created entirely new port economies, for example Singapore, and fundamentally reshaped global trade. The container wasn't primarily an automation technology. It was a coordination technology which cascaded through the entire system.
Choudary argues AI will do something similar for knowledge work, expanding the coordination toolkit across several dimensions:
Unified representation: AI can establish a structured view of a situation across fragmented information sources.
Decision support: Analyzing trade-offs and either making decisions (agentic) or supporting human decision-makers (assisted).
Composition: In the past, agreeing on common standards between organizations was tedious and expensive. AI can bridge those gaps dynamically.
Governance: Setting up shared governance frameworks used to require painful negotiations. AI can do this more flexibly, based on preferences.
This has real strategic implications. If you only see AI as automation, you optimize existing processes. If you see it as coordination, you start asking different questions entirely: what new organizational forms become possible? What previously impossible collaborations can now work?
Unbundling and Rebundling — But Around Constraints, Not Tasks
The second hypothesis is where the book gets really interesting. There are broadly two views on how AI will reshape work. The role-based view says AI will replace entire roles, like programmers, designers, analysts. The task-based view says roles are bundles of tasks, and AI will replace specific tasks within them, for example writing unit tests or cleaning data. Choudary goes further than both.
He introduces a distinction between economic value and contextual value of tasks. Economic value is straightforward supply-and-demand: if AI can do a task, the scarcity premium drops. Even when AI can't fully replace a task, enabling more people to do it "good enough". One of his examples is how GPS navigation depleted the value of knowing your way around a city and taxi drivers took a hit.
Contextual value is more subtle and, I think, more important. It's the value a task carries because of where it sits in a workflow. Great example: A student taking notes has lower contextual value than a CEO taking notes. Same task, vastly different value. Contextual value can arise from internal company knowledge, expensive intra-role communication, or simply the decision-making context surrounding the task. (Although Choudary is not so clear here.)
Choudary's key insight: both economic and contextual value will drop for most existing roles as AI improves. But the right question isn't "what tasks can humans do better than machines?" You'll never win that race long-term. The right question is: where will the constraints be?
He identifies three types of constraints that will shape new role boundaries:
Scarcity-based constraints: Something remains genuinely scarce (supply and demand still applies).
Risk-based constraints: Someone needs to be responsible. Accountability doesn't automate easily.
Coordination-based constraints: Communication between teams, organizations, systems still needs human judgment.
New roles, Choudary argues, will emerge around these constraints. Thinking about the future of work through constraints rather than skills is a much more productive frame.
From My Personal Experience: Future of Software Engineering
To make this concrete, I've been applying Choudary's framework to software engineering, a domain I know well from my own work.
Previously, a developer would look at specs, design a solution, write code, and test it (among other stuff). The full bundle. Now, AI coding tools are restructuring that bundle. AI can understand large codebases, generate solutions, and handle much of the routine coding work. The coordination of specs and solution design is increasingly AI-assisted.
So where do the constraints land?
Scarcity: We can now build far more things than we can actually verify. Security audits, best-practice reviews, deployment validation. These become the bottleneck, not the coding itself.
Risk: We still want a responsible, knowledgeable human in the loop, especially for production systems where failures have real consequences.
The effect is a general trend toward specialization. We no longer need a single developer who holds the entire codebase and context in their head. That's a coordination problem AI can help solve. But constraints are building around security, responsibility, platform engineering, and fixing things at scale. The coding itself becomes less valuable; the surrounding constraints become more so.
This isn't from the book, it's my own extension of Choudary's framework. But I think it illustrates the power of thinking in constraints rather than tasks.
What This Means for Organizations
The third major thread in Reshuffle addresses how companies themselves will change. Organizations face a constant tradeoff between autonomy, how well individual teams can work independently, and coordination, how well teams work together. Right now, coordination costs are incredibly high. A huge number of employees in any large organization are essentially moving information around.
When AI dramatically lowers coordination costs, through shared knowledge bases, better execution tools, improved decision support, the autonomy-coordination tradeoff shifts. Teams can specialize more, organizations can become more modular, and the overhead of alignment shrinks.
Choudary also makes an important point about competitive advantage in this new landscape. AI turns knowledge into scalable, rentable components. Competitive advantage comes from how well you bundle these components and critically, from overcoming the constraints I described above. He cautions against over-relying on external AI tools, since they can lead to lock-in, give away learning effects, and shift pricing power to your vendor. Owning the tools that give you an advantage matters.
Risk becomes another source of differentiation: delivering outcomes rather than products, guaranteeing reliability, building trust. Companies that can navigate these dimensions will be better positioned than those simply "adopting AI" at the task level.
What I'd Take Away for Strategy
This is my own synthesis, not directly from the book, but building on Choudary's frameworks:
Acknowledge the shift. Lower coordination costs and partly automation will change the value architecture of most industries. This isn't a "maybe." The question is how fast and where first.
Look outward. How is value creation changing in your industry? Where are new constraints through scarcity, risk or coordination emerging? This is where competitive advantage will concentrate.
Build around constraints. Can you build a position around these constraints that others can't easily replicate? That's where strategy meets the new reality.
Reorganize accordingly. How does all of this require you to change your organization and the roles within it? If the constraints are shifting, the org chart should follow, not the other way around.
These aren't revolutionary steps. But I find it clarifying to have a framework that connects the macro-level economic shifts to specific strategic questions.
My Verdict: Brilliant, but Could Be Clearer
I want to be honest about one thing: the book's style can be tough to follow. Choudary jumps between ideas from shipping containers to Shein to Formula 1 pit stops and the connections, while often brilliant, aren't always easy to track on a first read. The depth of thinking is impressive, but the density means you'll probably need some time to digest. Some chapters could have benefited from tighter structure or clearer signposting.
That said, intellectual ambition more than compensates. Most AI books give you one idea stretched across 300 pages. Reshuffle gives you a full framework, coordination vs. automation, economic vs. contextual value, constraint-based rebundling and then applies it across work, organizations, and industries.
What I'm watching: whether Choudary's constraint-based model holds up as AI capabilities continue to expand. If coordination costs keep dropping as fast as he argues, the rebundling he describes should start becoming visible in how companies reorganize not just in theory, but in actual org charts and value chains. That's where the real test will be.
AI Disclosure: The research, structuring and notetaking was done by myself, Claude wrote a draft that I improved iteratively. No links or sources were added by Claude. Image made by [tool].