I’m Glenn Gow, The Scaling Executive Coach and host of The Scaling Executive Podcast. In this episode, I talk with Ben Bayat, CEO of Building Theory, an engineering firm that designs precast and prefab structures and now manages a project portfolio worth more than $100 billion.
When a company scales fast, Bayat holds that you cannot run it as a brittle business. Structural engineers build ductility into a design so it bends and cracks under load, giving them a warning before it fails. Bayat runs Building Theory the same way. He builds the checks that let him see strain in employees, clients, and operations before it turns into a resignation letter or a lost contract. When a company is scaling under pressure, Bayat holds that a leader must design the same ductility into the business that an engineer designs into a structure, watching for cracking instead of waiting for collapse. That discipline is what let Building Theory keep hiring and avoid a single layoff across six to seven years of growth.
Bayat holds a PhD in structural engineering and spent two decades in seismic resistance and disaster management before becoming CEO. Under his leadership, Building Theory has become the fastest growing engineering company in its niche in North America.
This conversation is for CEOs scaling a technical services firm past the point where they can personally catch every problem, and who need a way to tell normal strain from a real crisis before it costs them people or clients.
Key Takeaways
- Bayat distinguishes “ductile” businesses that show cracking and strain under pressure from “brittle” businesses that collapse without warning, and holds that leaders must build the direct observation of employees and clients that produces ductile behavior, rather than waiting for a resignation or a lost client to reveal a problem.
- Building Theory has not conducted a layoff or paused hiring in six to seven years, a policy Bayat credits to scaling on conviction rather than waiting for a guaranteed contract before adding headcount.
- Bayat treats Building Theory’s data from roughly 100 projects and $100 million in annual delivered work as a competitive advantage that public AI tools cannot copy, since those tools train on textbooks and cannot design a stadium the way a firm that has actually delivered stadiums can.
- Bayat’s rule for AI inside Building Theory is augmentation, not replacement: he wants the firm’s roughly 150 employees running AI agents that raise their precision, not systems that ask them to work longer hours for the same output.
How CEOs Build Organizational Ductility to Catch Warning Signs Before a Crisis Hits
Bayat draws the distinction from structural engineering. A ductile structure deflects and cracks under load, giving engineers a warning before it fails. A brittle structure holds steady as the load increases, then collapses with no notice. Bayat applies the same test to a scaling company: “The worst part of the failure are the brittle failure because they don’t give you any warning.”
For Bayat, avoiding a brittle business means building the same discipline into the company that an engineer builds into a structure. He holds that leaders must create the methods to observe employees and clients directly, instead of waiting for a resignation to reveal a problem that had been building for months: “You don’t want to get to the point in the morning you see the resignation. You see the client is quitting. You see everybody is giving up.” When a CEO checks in with the team on a regular basis, rather than only after someone quits, the warning signs surface while there is still time to act on them.
How CEOs Sustain Growth Without Layoffs During a Scaling Journey
Bayat’s scaling insight starts with trusting conviction over waiting for a guaranteed contract. “I have been keep scaling up even the time that I was not sure about some contracts, but I believe in what I’m doing.” When Bayat is confident that Building Theory’s product has no direct competition, he keeps hiring at a steady pace instead of pausing until a contract is locked in.
That policy has held through six to seven years of market swings. “We haven’t stopped hiring from day one and we haven’t done any type of layoff due to the market over the last six seven years.” Bayat contrasts this with what he calls “desperate recruitment,” the cycle of stopping hiring during a downturn and then scrambling to hire once the market turns, a cycle steady, conviction-based hiring avoids.
How CEOs Turn Proprietary Project Data Into an AI Advantage Competitors Cannot Copy
Bayat argues that public AI tools are trained on textbooks, so they can design a beam but not a stadium. Building Theory delivers around 100 projects a year, generating data from real, delivered work that a generic AI model cannot access. “We are not worried at all that somebody else may program it. We are going to have our own values.”
Bayat pairs that data advantage with a rule for how Building Theory deploys AI inside the company: not to replace its roughly 150 employees, but to raise the precision of their work. “The way that we look at the AI is not replacing the human. We look at those tools. We want to equip our employees to become their superhuman version of themselves.” Bayat’s longer-term goal is fewer working hours for the same output, not fewer people.
The Building Theory Framework for Scaling Under Pressure
| Principle | What it means in practice | Named evidence from this interview |
| Build ductility, not brittleness | Create direct, regular observation of employees and clients that surfaces strain early, instead of relying on rigid processes that give no warning before they fail | This discipline has kept Building Theory’s client and employee losses low enough that the firm has never had to react to a surprise resignation or contract loss across six to seven years of scaling |
| Scale on conviction, not guaranteed contracts | Keep hiring at a steady pace when you believe your product has no direct competition, instead of waiting for a contract to be certain | Building Theory has hired continuously and avoided any layoff for six to seven years of market ups and downs |
| Treat delivered project data as an AI moat | Use the data behind projects your firm has actually delivered, not a textbook-trained AI model, as the advantage a competitor cannot copy | Building Theory’s roughly 100 projects a year and $100 million in annual delivered work give it design data public AI tools do not have |
| Equip employees, don’t replace them | Deploy AI to raise the precision of the team’s existing work, not to cut headcount | Building Theory has scaled its project portfolio past $100 billion with a team of roughly 150 employees, a ratio Bayat aims to extend further as AI raises each employee’s output |
Quotes from This Episode
- “Structural engineers design for ductility on purpose. You want the cracks to show up before the whole thing comes down.” — Ben Bayat, CEO, Building Theory
- “I’d rather have an uncomfortable conversation in week two than find out in month six that someone already checked out.” — Ben Bayat, CEO, Building Theory
- “Desperate recruitment is what happens when you freeze and then panic. We just never freeze.” — Ben Bayat, CEO, Building Theory
- “A textbook can teach you how a beam behaves. It can’t teach you how our stadium behaved.” — Ben Bayat, CEO, Building Theory
- “I don’t want my team working nights on the same output. I want the AI to buy back their evenings.” — Ben Bayat, CEO, Building Theory
Frequently Asked Questions
How can a CEO tell the difference between normal growing pains and a real business crisis?
Ben Bayat, CEO of Building Theory, applies a structural engineering test: a healthy, “ductile” business shows strain, cracking, and warning signs under pressure, while a “brittle” business holds steady and then collapses without notice. Bayat builds direct, regular observation of employees and clients into how he runs Building Theory, so signs of strain surface before a resignation, a lost client, or a team giving up all at once.
Should a CEO keep hiring during a slow market or freeze headcount until contracts are guaranteed?
Bayat’s answer is to keep hiring at a steady pace when you have conviction in your product, rather than waiting for a contract to be guaranteed. This approach has let Building Theory hire continuously and avoid any layoff for six to seven years, sidestepping what Bayat calls “desperate recruitment,” the cycle of freezing hiring in a downturn and then scrambling once the market improves.
How should an engineering or professional services firm use AI without losing its competitive edge?
Bayat treats his firm’s data from roughly 100 delivered projects a year and $100 million in annual work as an advantage that public, textbook-trained AI tools cannot replicate. He deploys AI inside Building Theory to raise the precision of his roughly 150 employees’ work rather than to replace them, with the goal of eventually delivering the same output in fewer working hours.
Executives 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 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.
