M is the new T
For years, companies optimized for T-shaped talent: people with a broad base of general knowledge and one deep area of expertise. It was a useful model in a world that was transitioning toward greater collaboration and where roles were clearly defined and expertise was based on having both experience and deep knowledge, and where technologies evolved at a predictable pace.
But AI has changed the rules. Boundaries between disciplines are dissolving. Innovation no longer happens within silos, it happens at the intersections. To thrive in this new landscape, being T-shaped isn’t enough. The future belongs to M-shaped professionals. That is people who have deep knowledge in multiple areas, especially more than a passing familiarity with AI.
The T-shaped model assumed disciplines like design, engineering, product, and marketing could operate as neighboring but separate specialties. The horizontal part of the T allowed for individuals to able to both understand and evaluate the impact of the other disciplines. Today, with ready access to AI the overlap between disciplines so heavily that the edges are nearly indistinguishable. However, AI still is not 100% reliable and requires people to have a deeper know of these other professions to assess both the generated results, and to assess if the models and data being used by the AI are themselves correct.
Today Designers work with data models, Engineers think about user flows, Product managers shape model behavior and Marketers operate inside personalization algorithms. In a world powered by AI, depth in one area is valuable—but range across multiple areas is what makes someone adaptable, resilient, and high-impact. It makes them valuable.
What Makes Someone M-Shaped?
An M-shaped professional has multiple areas of depth—multiple vertical strokes—not just one. But more importantly, they integrate those areas to create a more unified understanding of the problem.
To design, build, or manage AI-driven products, every modern builder needs fluency across at least four dimensions:
Technology acumen: understanding the behavior, constraints, and opportunities of AI systems.
Business acumen: recognizing how AI generates value, shapes strategy, and transforms markets.
Data acumen: knowing how data is sourced, structured, biased, governed, and used.
Craft depth: the foundational expertise in your home discipline—design, engineering, product, marketing, or another field.
This isn’t about being a “jack of all trades.” It’s about knowing enough across multiple domains to innovate, collaborate, and execute without waiting on handoffs. Its about being able to accelerate delivery, while maintaining the vision behind the work.
Think like an Entrepreneur, not an Enabler
AI compresses the distance between idea and implementation. Designers who are able to make the shift from enabling someone else’s vision, to trusting their instincts about their own ideas, their own products and services will be unstoppable. One M-shaped professional can now do what previously required a small team: define the problem, design the solution, shape the data, and build a working prototype, and iterate based on market responses and customer feedback.
This shift favors people who think like entrepreneurs—people who:
take initiative rather than wait for direction
prototype instead of pitch
understand feasibility and viability, along with desirability
live in ambiguity, making decisions with incomplete information
own the problem end-to-end
For Designers this means being able to bring an idea to life, while maintaining the nuance of the execution, and ensuring the results address the users’ needs in a meaningful way. Execution specialists are still valuable, but the highest-impact people will be those who combine specialist depth with entrepreneurial breadth and turn ideas into POC’s and MVPs.
Radical Collaboration Is the New Default
In modern teams, collaboration looks different from the traditional “handoff” model.
Designers write logic.
Engineers sketch interfaces.
PMs build in Figma and Python.
Marketers shape positioning through data and personalization insights.
The question isn’t “What’s your major?” or “What’s your title?”
The real question is: Can you work fluidly across disciplines to solve complex, evolving problems?
Continuous Learning Becomes the Core Skill
AI is evolving too quickly for static expertise to remain relevant. The most valuable people will be those who treat learning as a constant discipline. Being M-shaped isn’t a category—it’s a mindset:
curiosity over comfort
range over rigidity
growth over protectiveness
Your depth still matters, but your range determines your relevance.
Agents Will Become the New Code
Software has long been built with code as its foundational structure—like 2x4s in a house. But AI is ushering in a world where we compose behaviors, orchestrate agents, and shape intent rather than labor over implementation details.
As agents become the new code:
designers become builders
engineers become experience architects
product managers become behavioral composers
Discipline boundaries dissolve because the tools themselves dissolve them.
The M-shaped professional isn’t just useful in this world—they’re the only kind of professional who can fully participate in it.
The Bottom Line
Craft still matters. Expertise still matters. But they’re no longer the full story. To lead in the era of AI, you must be adaptable, multi-specialized, entrepreneurial, data-aware, and technologically fluent.
The question is no longer “What is your one area of depth?” It’s “How many dimensions can you bring together to create something meaningful?”
Because in the age of AI, M is the new T.
