Step outside your lane, be a generalist problem-solver
Thinking about future-proofing your career in an age of AI? Here's what I learned about asking better questions, rather than knowing more answers.
“Thank you Lucinda, for the great article…. If you don't know, ask questions, do some research, listen and read, talk to people, that fosters connection, understanding and collective intelligence. Ta for the good words " - Paid Subscriber
We need generalist problem-solvers in an AI era
This week marks one year since I met my co-founder at Mondus Capital - Nir Davidson — and dived headfirst (again) into founder-mode. Early-stage companies are tough in a way that’s hard to explain if you haven’t lived it. You become a chameleon problem-solver. You're navigating constant uncertainty, wearing every hat in the company. It’s chaotic
But this new venture opportunity came with an added layer of complexity - moving into a new vertical: finance. While I’m an urbanist intimately familiar with city and housing problems, I’ve never specifically worked from the angle of mortgages and lending. It’s a totally different language and a different system.
And while that made it feel like unfamiliar territory, it also made the opportunity clearer: if we want to solve the housing crisis in Australia, we need to be willing to operate in the systems where change actually happens—even if that means moving into entirely new verticals.
Outsiders bring new innovation
I’m a firm believer that often takes an outside view to bring new innovation. We;ve seen this time and time again. Think:
Didier Elingzer (Culture Amp) - A visual effects specialist, not HR
Brian Chesky (Airbnb) – a designer, not a hotelier
Whitney Wolfe Herd (Bumble) – brand and marketing, not tech or dating industry.
Now more than ever in the age of AI, success demands something more than just domain expertise, it demands being a generalist problem-solver.
Defining your career by the problems you solve, not the job you have.
People have asked me: Why mortgages? Isn’t that a huge leap from urban design and data analytics? At first glance, yes. But I’ve spent 20 years trying to make cities work better for people. That’s meant exploring housing from nearly every angle:
As an architect – designing public spaces that make communities more connected
As a placemaker – leading community-led initiatives to improve neighbourhoods
As a technologist – using big data to help city leaders make smarter decisions
And now, as a fintech founder – creating a new kind of mortgage to make homeownership more accessible
The throughline? Personally, I’m agnostic about the tools. I care about impact. When you define yourself by the problems you solve, not the job you have, your career becomes more agile and resilient. Particularly now, when AI is set to disrupt the knowledge economy.
Domain Expert vs. Generalist Problem Solver
We’re often told to “stay in our lane.” To become domain experts with deep knowledge. Until now, that was a safe bet. Yes, expertise matters. But in an era of AI, where knowledge can be out-brained to a large language model in milliseconds, being an interdisciplinary thinker—someone who connects dots across fields—might be even more powerful.
Here’s some attributes to consider
Attributes of a Specialist Domain Expert:
Deep subject matter knowledge
Focuses on technical precision and accuracy
Optimisation within a field/vertical
Trusted authority
Linear career progression
Attributes of a Generalist Problem-Solver:
Connects disparate ideas across domains
Focuses on asking questions and what ifs
Optimisation across interdisciplinary fields
Moves between strategy and execution
Non-linear career path.
The AI Lens: Less knowledge, more questioning
Here’s the challenge: in an AI-powered world, we have less need to know everything—its more about asking the right questions, the right prompt.
With more knowledge than we could ever access just a prompt away, the real skill is knowing how to frame the right question, spot the right pattern, and challenge the status quo. It’s not about having all the answers. It’s about being curious enough to find better ones.
Final thoughts
Generalist thinking isn’t about being shallow. It’s about building a deeper kind of adaptability—the kind that helps you lead through change, not just survive it.
And it starts with being brave enough to step outside your lane.
📣 How is your work changing with the surge of AI tools? Do you consider yourself a specialist or a generalist?