I am Glenn Gow, The Scaling Executive Coach and host of The Scaling Executive Podcast. In this episode, I talked with John Podlewski, founder and CEO of Wealthy Planet, about a problem more CEOs will face as AI reshapes every industry: how do you lead a team that understands the technology better than you do?
Podlewski’s answer: act as the domain expert, not the developer. When a CEO cannot code the product personally, Podlewski holds that the job is to translate real-world experience into product direction, while a technical team owns execution. He built that model at Wealthy Planet, where his non-technical leadership now directs an AI engineering team building ABI, an AI-native financial planning platform, staffed largely by University of Waterloo computer science Olympians and a NeurIPS award recipient.
Before founding Wealthy Planet, Podlewski served eight years as a medic in the Canadian Armed Forces, spent nearly a decade as a senior vice president at Primerica leading branch offices across six provinces to triple-digit annual growth for nine consecutive years, then founded Debt Freedom Canada in 2003 and built The Bridge, an early digital financial-needs-analysis platform, years before “fintech” became a common term.
This episode is for CEOs who must lead engineers, data scientists, or AI teams despite having no technical background themselves.
Key Takeaways
- When Wealthy Planet needed interns and received about 3,000 applications with no HR department, chief architect Andre Murciano built an in-house AI screening tool in roughly four to eight hours that narrowed the pool to 50 candidates, then 25, before any human interview.
- Podlewski leads Wealthy Planet’s engineering team, built largely from University of Waterloo computer science Olympians and NeurIPS award recipient Andre Murciano, by acting as the domain expert who sets product direction while engineers own the technical build.
- Podlewski says using AI to draft and verify code lets Wealthy Planet operate with roughly half the staff and half the cash burn a traditional software build would require.
- Eight years as a Canadian Armed Forces medic trained Podlewski to make split-second decisions under pressure, a discipline he credits with his ability to pivot Wealthy Planet toward an AI-native platform after a Silicon Valley Bank-linked funding deal collapsed post-pandemic.
- Podlewski warns that CEOs who keep staff on administrative work AI could handle lose ground to competitors who redirect that same money to marketing and specialist hiring.
How CEOs Without a Technical Background Can Lead an AI Engineering Team
If you are not the most technical person in the room, Podlewski’s experience says that will not stop you from leading a technical company. He built Wealthy Planet’s engineering team almost entirely from University of Waterloo, recruiting a NeurIPS award recipient, Andre Murciano, at age 22 to serve as chief architect. Murciano is now pursuing a PhD at the University of Toronto. The rest of the technical team are Waterloo alumni and self-described computer science Olympians, joined by Dr. Steven Watt as interim CTO and Cyrus Mystery, a former Google product leader, on the advisory board.
Podlewski does not write code. “I’m not a tech guy by nature,” he told me. His role instead: guide engineers who have deep technical skill but limited financial services experience toward what the market actually needs. He credits three decades in financial services, including his stretch at Primerica, with giving him the domain knowledge his engineers do not have.
The rule for you as a non-technical CEO: your engineers will out-build you on execution. Your job is to keep translating what the market needs into product requirements they can build against, and to keep repeating that translation through every product cycle until it matches the problem.
How CEOs Can Use AI to Cut Hiring Time and Reduce Burn Rate
AI does not just build product, in Podlewski’s view. It also removes work that would otherwise force you to hire. When Wealthy Planet posted an internship opening with no HR department to manage applications, the company received about 3,000 applicants, more, Podlewski said, than Google or Microsoft drew from the University of Waterloo that year. Murciano built an in-house AI screening tool in about four to eight hours. It narrowed 3,000 applicants down to 50, then to 25, before the team conducted a single human interview.
Podlewski applies the same logic to engineering itself. His team uses AI to draft code alongside developers, then verifies that code against in-house best practices before it ships, a workflow he says lets Wealthy Planet operate with roughly half the staff and half the cash burn a traditional build would require.
His warning to other CEOs is direct: “If you have human capital that’s being deployed on minuscule administration that can be replaced by AI and you’re not, you’re never going to win. You’re just not going to win.” The money saved on administrative headcount, in his framing, should move to marketing and to hiring the specialists AI cannot replace.
How Military Decision Discipline Shapes CEO Leadership Under Pressure
Podlewski’s leadership style traces back to eight years as a medic in the Canadian Armed Forces, including training in trauma medicine, where decisions had to be made in seconds. “You’ve got to be able to adapt and overcome,” he said, describing the mindset he carries from that training into the boardroom.
That discipline was tested directly after the COVID-19 pandemic. A funding deal involving Silicon Valley Bank collapsed, leaving Podlewski and his team without the capital path they had planned around. Rather than wait, he pivoted the company toward building an AI-native platform, recruiting Murciano and assembling the technical team that now builds ABI.
Podlewski’s rule for CEOs facing a similar collapse: act first and adjust the plan as new information arrives, the same instinct trauma medicine trains into a medic who cannot wait for complete information before treating a patient. He frames slow adaptation as an existential risk rather than a competitive disadvantage.
What CEOs Can Learn From Podlewski’s Leadership Framework
| Principle | What it means in practice | Named evidence from this interview |
| Lead as the domain expert, not the developer | A non-technical CEO directs product strategy from market experience while engineers own technical execution | Podlewski’s domain-expert model, applied without writing a line of code himself, produced ABI: an AI-native financial planning platform built by a technical team with no prior financial services background |
| Let AI absorb work before it becomes headcount | Route administrative and screening tasks to AI tools so hiring dollars go to specialists AI cannot replace | Murciano’s AI screening tool narrowed 3,000 internship applicants to 25 finalists in under a day, without an HR department |
| Adapt and overcome when the plan collapses | Treat a sudden loss of capital or partners as a signal to act, not a reason to wait for certainty | After a Silicon Valley Bank-linked funding deal fell through post-pandemic, Podlewski pivoted Wealthy Planet toward building its AI-native platform rather than continuing the prior plan |
Quotes from This Episode
- “Debt is modern day slavery.” — John Podlewski, Founder and CEO, Wealthy Planet
- “You don’t evolve, you’re extinct. Simple as that.” — John Podlewski, Founder and CEO, Wealthy Planet
- “I’m not a tech guy by nature.” — John Podlewski, Founder and CEO, Wealthy Planet
Frequently Asked Questions
How can a CEO without a technical background lead an AI engineering team?
A non-technical CEO can lead an AI engineering team by acting as the domain expert who defines the market problem while engineers own execution. Wealthy Planet founder and CEO John Podlewski, who says he is not a developer, built his company’s technical team from University of Waterloo computer science Olympians and NeurIPS award recipient Andre Murciano, then applied three decades of financial services experience to shape ABI’s product direction rather than its code.
How can CEOs use AI to reduce hiring costs and burn rate?
CEOs will cut both hiring time and burn rate by routing administrative and screening work to AI tools before adding headcount. At Wealthy Planet, an in-house AI screening tool built in about four to eight hours narrowed 3,000 internship applicants to 25 finalists without an HR department, and the company uses AI to draft and verify code with roughly half the staff a traditional build would require, according to founder John Podlewski.
How should a CEO respond when a funding deal or key partner suddenly falls through?
A CEO should treat a collapsed deal as a signal to act immediately rather than wait for more certainty. When a funding deal involving Silicon Valley Bank fell through for Wealthy Planet after the pandemic, founder John Podlewski pivoted the company toward building an AI-native platform instead of continuing the original plan, a decision he traces to decision-making habits formed during eight years as a Canadian Armed Forces medic.
CEOs Work with Glenn Gow to Scale Their Companies and Careers
Glenn Gow is The Scaling Executive Coach. He coaches ambitious executives into the CEO seat and CEOs into successful exits. With 25 years as a CEO and 5 years in venture capital, Glenn helps leaders scale their companies by scaling themselves first. If this conversation was useful, you can apply for executive coaching with Glenn Gow or apply to be a guest on The Scaling Executive Podcast.
