The Generalist Misunderstanding
What We're Getting Wrong When We Talk About the Generalist Imperative
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We have a problem, and it is costing us clarity on the operating future that companies are actually building towards. The companies where we’d like to work. The future we all keep talk about building. The “revolution” we are incessantly engaged in discussing.
For decades, the term “generalist” has carried a subtle, often unspoken stigma. It suggests a “Jack of all trades, master of none,” someone who floats between departments, translates between teams, and manages projects, but who ultimately lacks the granular, technical depth of a specialist. We view the generalist as the “connective tissue” of an organization, while the specialists are the “muscle.”
This role has been thrust to the forefront of the popular conversation about what the future of work portends. But we’re conflating “being general” with “lacking depth,” and that’s a problem.
Simply being a specialist in a single domain—marketing, operations, finance—is no longer enough. Thriving companies are being built around individuals who achieve depth across multiple domains simultaneously, rather than those lazily trading depth for breadth.
The primary driver of this shift is the collapse of the “learning curve” brought on by the technological and productivity revolution machine learning has created. Historically, becoming a “T-shaped” employee (deep in one area, broad in others) took a career’s worth of time. You spent 10 years mastering financial modeling, leaving little bandwidth to master Python or digital marketing attribution. You had to choose your vertical because human time was the bottleneck.
AI has removed that bottleneck.
New tools and platforms allow us to accomplish accelerated learning across unrelated domains and bypass the administrative burden of execution.
When the time to perform the “mundane” work of execution moves toward zero, the capacity for a single individual to acquire deep, actionable expertise expands dramatically. You can now be a strategist who actually builds the financial model, writes the marketing copy, debugs the system, and deploys the operational workflow.
This is more “multi-specialization” than “generalism” in the traditional sense.b Researchers and investors are spending considerable time forging a new understanding of “polymathy.”
The Market Signal
The instinct that the future demands more than narrow specialization is not contrarian. It is aligned with what the leaders shaping the future of business are actively communicating.
Sam Altman has explicitly stated: “I think that the best founders are generalists all the way through.” He isn’t describing someone who knows a little about everything; he is describing founders who “specialize in generalization,” individuals who maintain the cognitive range to execute across product, sales, and strategy simultaneously.
Vinod Khosla takes this further, predicting a world where “expertise becomes free.” In his view, AI democratizes skill sets to such an extent that the traditional scarcity of expertise is largely eliminated. What remains valuable is the person who can wield that expertise across the widest possible surface area.
Even the often-resistant academic establishment agrees. Harvard Business School recently reclassified its entire MBA program as a STEM degree, while Wharton has launched an “AI for Business” major. These institutions are betting that the future manager cannot be a “non-technical” leader. They must be fluent in the engineered systems and data science that will underpin every business.
Three Companies Redefining the “Generalist”
Salesforce
“AI is handling 30-50% of our workload.” — Marc Benioff, CEO
The Shift: Salesforce eliminated 4,000 customer service roles but didn’t just automate, they empowered remaining employees to orchestrate AI agents across sales, service, and marketing simultaneously. Their “Agentforce” platform now drives their top deals, with individual contributors using AI to execute work that previously required entire specialized teams.
Microsoft
“We’re hiring employees with a lot more leverage than the pre-AI workforce.” — Satya Nadella, CEO
The Shift: Microsoft no longer hires “developers” or “marketers.” They hire people who can think strategically about business problems, then use AI agents (like Copilot, which now writes 30% of Microsoft’s code) to execute technical work themselves. Recruiters now prioritize “practical, cross-domain skills” over narrow specialization.
Shopify
“Before asking for more head and resources, teams must show why they cannot achieve their objectives using AI.” — Tobi Lütke, CEO (April 2025 Memo)
The Shift: The most radical example. Shopify made AI usage a baseline expectation and performance evaluation criterion. They’ve grown 20-40% annually while reducing headcount from 11,600 to 8,100 employees. Case study: Ridge Wallets achieves $5M revenue per employee by having individuals orchestrate AI across customer service, data analysis, engineering, and inventory—collapsing what would have required 50 specialists into teams of one or two polymaths.
The Pattern: All three companies expect individuals to hold the CEO’s strategic view (macro) while using AI to execute specialized work (micro) themselves. They’re not hiring coordinators. They’re building teams of builder-strategists.
The future belongs to the person who can synthesize strategy at the macro level and execute at the micro level, using AI as the connective tissue to generate extroarindary leverage and to drive hefty financial results.
This is the core of my belief: Companies will require individuals to step back and take a macro view, looking at things from a CEO’s strategic perspective. However, simultaneously, we, as individual contributors, will be required to drill down and utilize new tools to execute the micro-strategy, building the applications and executable tools needed to deliver on that strategy.
The work of operating a company will increasingly have less to do with project management and much more to do with developing and launching the agents and applications that perform the targeted work and functions our elaborate project plans, and never-met-deadlines, have historically tracked towards.
1. The Macro Perspective (The CEO View)
At the macro level, your role is to see the entire organization. You must understand how marketing impacts operations, how financial constraints shape product strategy, and how customer acquisition costs flow through the P&L. You must learn to think across silos and with a keen awareness of the underlying requirements and tradeoffs embedded within these highly specific towers.
2. The Micro Execution (The Builder View)
The person who holds that macro perspective must also be able to drill down and execute.
Rather than delegating execution to specialists and hoping they understood the strategy, you will build AI agents to:
Deploy the financial models yourself.
Build the dashboards yourself.
Direct AI teams to execute specific micro-workflows.
In Practice
Imagine a product leader working on a go-to-market strategy.
The Old Model: You write a memo. You send it to Finance (wait 1 week). You send it to Marketing (wait 1 week). You hold alignment meetings to translate between the two.
The New Model: You understand the financial mechanics well enough to build the model yourself using an AI financial agent. You understand the marketing mechanics well enough to simulate customer acquisition scenarios yourself. You spend a morning building out the entire strategy and the execution assets.
You aren’t expected to know 20% of each domain. You are anticiapted to know 80% of each domain. The difference between the future and the past is that our new technology has compressed a 5-year learning curve into 6 months.
The future will not reward coordination, administrative execution, or task-based expertise. Companies will reward breadth of execution matched with keen strategic awareness and novel development.
To be a generalist in this new era is to have a holistic perspective, to view the board like a CEO, and to develop the skills to delve deeply into all the requisite domains of an organization.
Don’t make the mistake of thinking that to be a generalist is to know a little bit about a lot. Rather, it is a requirement to use the newly available tools to scale out to the strategic level and then drill down to direct agents, build tools, and execute immense volumes of activity for the organization.
This is the future of the company I most expect. And with it, I expect many hours of work, growing demands, more complex requirements. I expect the opportunity to drive more impact and have more influence over the operating reality of the organizations we serve than at any other point in the history of business.
This is the generalist misunderstanding. We’re not being asked to generalize. We’re being asked to know, do and create more. What a time to be alive and operating.
- j -
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John Brewton documents the history and future of operating companies at Operating by John Brewton. He is a graduate of Harvard University and began his career as a Phd. student in economics at the University of Chicago. After selling his family’s B2B industrial distribution company in 2021, he has been helping business owners, founders and investors optimize their operations ever since. He is the founder of 6A East Partners, a research and advisory firm asking the question: What is the future of companies? He still cringes at his early LinkedIn posts and loves making content each and everyday, despite the protestations of his beloved wife, Fabiola, at times.
John, the industrial age sold us a specific lie: that hyper-specialization was safety. It told us to become the perfect gear for a machine that would last forever. You are correctly identifying that the machine is changing. The "Specialist" is now a liability—a single point of failure in a volatile system.
I read your piece not just as career analysis, but as a survival manual. As I’ve been writing about the "Great Unlearning", I realized that while the specialist waits for instructions or optimization, the Generalist sees the whole board.
We are moving from an economy of components to an economy of architects. You are effectively giving your readers permission to stop being tools and start being builders.
Thank you for mapping the terrain. The signal is strong.
Stay sovereign
This really clicked for me. What stood out most is how judgment and systems thinking become the real differentiators. If AI handles more execution, the ability to see the whole system, make good calls, and connect domains thoughtfully feels more important than ever.