David Montz

My career has run through consumer e-commerce at scale, VC-funded cybersecurity, enterprise modernization, and AI-native software. A few markers along the way:

• →2025 Arizona CIO ORBIE Finalist for Enterprise. Recognized among Phoenix's top enterprise technology executives.
• →Co-founded Able Software. Built an AI-native collections platform 0-to-1 in six months with a three-person team, and made a disciplined exit when the standalone market didn't materialize.
• →CTO at Sunstate Equip Co., a $2B+ rental-asset business. 110-person technology org. Took $12M+ a year out of operating costs, with a 27x first-year return on the AI bet.
• →CTO at Tracer.ai (formerly Appdetex), a VC-funded cybersecurity SaaS. 225% revenue growth on AI-driven threat intelligence. U.S. Patent 11,831,417 for the Threat Mapping Engine.
• →VP of Engineering and Product at Bodybuilding.com. Consumer e-commerce platform with 60M monthly visits.
• →Co-pitched The Original Stretchlace on Shark Tank Season 12 Episode 24 with my wife Jamie. Closed a deal with Robert Herjavec.

Tech strategy is interesting only insofar as it serves business strategy. Most of my focus is companies whose operations run on technology. For them, technology is leverage on the whole P&L: relieving margin pressure, taking out cost, making the operation more efficient, and responding quickly when the market moves. Getting there usually means modernizing the legacy systems the business runs on, without breaking them. A company whose product is technology is a different game: there it's speed of delivery and learning cycles. Two different situations, two different strategies. The work is matching the right strategy to the right situation.

I spend a lot of cycles on that alignment. Where is the business actually going. What does technology need to look like to enable it. What gets built, what gets bought, what gets retired. The hardest part is consistently trying to do too much with limited understanding. Strategies should be executed in iterations to accelerate the learning cycle and allow for quick adaptation. Especially now in the world of AI.

The last time I ran that play, software delivery went from 12-18 months to weeks on a 25-year-old core, without breaking the business.

The teams I've enjoyed building share a trait. Inside the team, the people closest to the work make the calls. Outside the team, the work shows up consistently and on time. Both halves matter. Autonomy without delivery is a vacation; delivery without autonomy is soul-crushing.

Getting both halves right is mostly being deliberate. Hiring for the shape of person the team needs at the moment it's in. Naming what good looks like and then protecting it. Removing the kind of friction that makes good people quietly disengage. Trusting people with the hard problems and getting out of the way once they've got it.

I run the P&L like the money is mine. In practice that means I know exactly where every dollar of the technology budget is going and what return it's expected to produce. It also means I'm comfortable saying no to spend that doesn't earn it, and equally comfortable doubling down when something is clearly working.

The discipline isn't about being frugal for its own sake. It's about earning the credibility to invest big when the moment is right. CFOs trust me with budgets because the receipts are always there. CEOs trust me with bets because the discipline is always there.

At my last seat that discipline ran every technology investment through the same return gate as any other use of the company's capital, with finance in the room. It's also how more than $12M a year came out of operating costs, line by line: contract development that wasn't earning its rate, software and licensing the business didn't need, infrastructure nobody could justify.