The Manufacturing Executive

The headlines say American manufacturing has a workforce crisis. Alex Torrey, co-founder and CEO of AIC, America's Innovation Corporation, will tell you the real constraint is workflow. He sees component shops running at 20 to 50 percent utilization when world class is north of 90, held back by decision-making infrastructure built for a world that doesn't exist anymore. In this episode, we'll explore physical AI, the shift from software that moves data to software that moves matter, and the small, founder-led manufacturers whose components make it possible. You'll hear why Alex calls those shops national treasures, why he thinks the goal is outmaneuvering dependence on China rather than outproducing it and what owner-operators nearing a transition should know about the third option most of them have never been offered.

Books are more than 80% bought online. Electronics, more than 50%. Custom manufactured parts? Less than 1%. CEO of Xometry, Sanjeev Sahni, believes that gap makes custom parts the most underpenetrated e-commerce category in the world, and that closing it has less to do with manufacturing capability than with speed and data. In this episode, we'll explore why an engineer can design a part in an afternoon and then lose days to manual RFQs and hit-or-miss supplier matching. You'll hear how online marketplaces are dissolving the 30 to 50 mile radius that defined machine shops for generations, why a Houston shop built on oil and gas is now doing aerospace work, and what changes for a shop owner who would rather make parts than chase sales. We'll also touch on why Sanjeev insists his company call manufacturers partners rather than suppliers.

Robots rarely break. Vision systems keep getting smarter. In automation, the technology has gotten so good that it's no longer what separates one company from another. Darragh de Stonndún, CEO of Automated Industrial Robotics, will tell you what does: the people and the culture behind it. In this episode, we unpack how he built AIR across six facilities in the US, UK and Ireland by evaluating every acquisition on culture first and walking away from impressive companies when the fit wasn't right. You'll hear what he looks for in a capital partner beyond the capital itself, how he gets a customer the identical experience no matter which facility touches the project and why he assembles the best experts across the whole company rather than handing the work to the nearest plant. We'll also get into where he expects AI to earn its keep in manufacturing, and the line he draws between using a new tool to do better work and using it as a shortcut.

Founder and CEO of Klear, Chris Hale, will tell you that companies rarely fail for lack of demand. They fail when capital falls out of sync with operations. In this episode, we dig into what Chris calls the success trap: the moment a manufacturer finally lands the transformational contract it's been chasing for years and discovers that's where the hard part begins. You'll hear why a career-making order is often the most dangerous moment for a business, what actually has to change inside a company to scale 10x into a massive backlog and how to turn tough payment terms with a much larger customer into a moment of leverage instead of weakness. We'll also get into why traditional bank tools are built to look backward and why the smartest teams build a capital strategy before the big order lands rather than after.

Founder and chief strategy officer of LeanDNA, Richard Lebovitz, will tell you that one of the biggest causes of part shortages isn't what you'd expect. It's failing to tell your suppliers what you don't need. In this episode, we dig into why supply chain teams get stuck firefighting shortages while executives chase working capital, and how those two goals drift out of sync. Richard makes the case for running a supply chain the way a good marketer runs a campaign: short, targeted and measured, then adjusted. You'll hear the difference between predictive and prescriptive AI, why the prescriptive kind is so much harder to get right, and the mistake he sees manufacturers make when they hand AI a decision it isn't ready for. Underneath all of it runs a simple idea he picked up early from the partners who taught him Lean: the point of any technology is to make the work easier for the people doing it.