Machine Minds

There’s a huge difference between making a robot work in a lab and making it reliable enough to survive the chaos of a real warehouse. For Michael Bearman, Chief Legal and Safety Officer at Vecna Robotics, closing that gap has been a 23-year journey spanning legal, operations, customer deployments, fundraising, safety, and industry standards.
Michael joins Greg to share how he went from outside counsel to becoming one of Vecna’s longest-serving leaders, taking on everything from contracts and customer implementations to financial modeling and even an all-night soldering session before a robot demonstration at Congress. That willingness to jump into unfamiliar problems gave him a front-row seat as Vecna evolved from experimental robotics projects into industrial automation deployed across warehouses and manufacturing facilities.
They explore why impressive robotics demos are very different from commercially viable products, how an early rescue robot helped Vecna learn that lesson firsthand, and why a major FedEx deployment pushed the company toward industrial mobile robots. Michael also breaks down Vecna’s approach to automated forklifts, tuggers, and CaseFlow, including how one customer doubled throughput with half the staff by rethinking the traditional case-picking workflow.
In this conversation, Greg and Michael explore:
Michael’s unconventional journey from outside legal counsel to Chief Legal and Safety Officer, and the many operational, financial, customer, and leadership roles he took on along the way
Why there is such a large gap between a successful robotics demonstration and a system that customers can rely on in real-world industrial environments
How Vecna’s early Bear rescue robot helped build the technology, team, and relationships that eventually supported its pivot into industrial robotics
The FedEx deployment that put more robots into a single site than Vecna’s entire existing fleet and helped reshape the company’s direction
How automated tuggers, forklifts, and CaseFlow tackle different material-handling workflows across manufacturing, automotive, and third-party logistics
Why close collaboration with an early 3PL customer helped Vecna build CaseFlow around the realities of warehouse case picking, ultimately doubling throughput with half the staff at that customer
How flexible Robots as a Service models allow 3PL customers to scale fleets up and down around seasonal peaks instead of paying for idle robots year-round
What Michael looks for during on-site safety risk assessments, from pedestrian traffic and crosswalks to routes that may look good in CAD but fail in the real warehouse
Why interoperability matters as warehouses deploy robots from multiple vendors, and how Michael helped shape the MassRobotics AMR interoperability standard that has now progressed into an international ISO standard
The challenges of writing safety standards for everything from multi-ton industrial robots to dynamically balancing humanoid and legged systems
Why spending time inside real customer facilities has made Michael a better lawyer, safety leader, and contributor to robotics standards
What Vecna looks for when hiring in a startup environment, including intelligence, flexibility, curiosity, and a willingness to figure things out rather than staying inside a narrowly defined role
Why customer trust depends on transparency when something goes wrong, and why hiding information is one of the fastest ways for a robotics company to lose that trust
Michael’s view that warehouses will continue to need people for edge cases, even as automation expands, with human workers increasingly supporting fleets rather than performing every task manually
Why robotics founders cannot afford to cut corners on safety, especially when a single serious incident can have enormous consequences for a young company
For robotics founders, operators, engineers, and anyone trying to move automation from a controlled demo into messy real-world environments, this conversation offers a practical look at what reliability, safety, interoperability, and customer trust actually require.
Learn more about Vecna Robotics: https://www.vecnarobotics.com/
Connect with Vecna Robotics: https://www.linkedin.com/company/vecna-robotics/posts/
Connect with Michael Bearman: https://www.linkedin.com/in/bearman/
Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

What happens when AI agents stop living entirely on screens and start controlling cameras, wheels, motors, and eventually full robotic bodies?
Chris Matthieu, VP of Developer Ecosystem at RealSense, joins Greg to explore the rapidly converging worlds of AI agents, computer vision, robotics, and physical intelligence. A lifelong hacker who started programming on a Commodore VIC-20 as a kid, Chris has spent more than four decades building technology, including five startup exits, before joining Intel as an entrepreneur in residence and eventually helping grow the RealSense developer ecosystem.
Chris shares how his fascination with connected machines evolved from IoT platforms and decentralized computing into his latest project, AgenticROS, an experimental system that gives AI agents direct access to ROS and allows them to perceive and control physical robots. His robot Bob can already use camera data to identify where Chris is, calculate his position, control its wheels, and follow him through a room without Chris explicitly programming every behavior.
Greg and Chris also dig into RealSense’s evolution from an Intel incubator project into an independent company, why depth perception is becoming foundational infrastructure for physical AI, and how open source software, cheaper hardware, and AI coding tools are dramatically lowering the barrier to building real robotic systems.
Highlights:
Chris’s journey from hacking on Commodore computers as a child to building and exiting five technology startups before moving into Intel and RealSense. - Why builders who avoid ROS can end up recreating infrastructure that already exists, and why the broader ROS ecosystem can dramatically accelerate robotics development.
How AgenticROS connects tools such as Claude, Codex, Gemini, and other AI agents directly to ROS, giving them access to cameras, perception data, and robot controls.
Why Chris believes increasingly capable AI models may eventually control robotic bodies without developers having to explicitly program every movement or create a predefined skill for every task.
The startup lesson Chris learned at Intel: stop building technology in search of a market and instead start with painful customer problems people are willing to pay to solve.
Why timing played such an important role in spinning RealSense out of Intel, especially as generative AI, physical AI, and robotics began accelerating simultaneously.
How RealSense depth cameras give robots an RGBD view of the world by calculating depth at every pixel, while increasingly moving AI and perception processing directly onto the camera itself.
How open source SDKs and AI code generation are shrinking prototype timelines from weeks or months to hours, allowing developers to validate ideas far more quickly.
Why side projects, GitHub activity, curiosity, and building in public can be some of the strongest signals for engineers looking to break into robotics and physical AI.
How one experimental LinkedIn post about Chris’s robot generated roughly 180,000 impressions and led to NVIDIA webinars, conference talks, and unexpected opportunities.
Why individual developers can sometimes validate ideas faster than large companies, especially when AI coding tools, inexpensive cameras, Raspberry Pis, and NVIDIA Jetsons make functional robotics prototypes accessible for hundreds rather than tens of thousands of dollars.
Chris’s philosophy of failing fast, testing the market early, and recognizing when either the technology or the customer demand is not ready yet.
Why he believes the enormous funding rounds flowing into physical AI may reflect the scale of the potential market, even while competing approaches such as VLAs, world models, and skill-based systems are still evolving.
His advice for anyone entering robotics: start with an inexpensive desktop robot, experiment with it, and remember that complex robots are ultimately systems of smaller components working together.
Where Chris hopes physical AI ultimately leads: robots that understand the people around them, safely operate in human environments, and perhaps finally bring him coffee in the morning and a beer in the evening.
For developers, founders, students, and anyone curious about where AI goes after the chatbot, this conversation offers a hands-on look at how rapidly robotics is becoming easier to prototype, program, and experiment with, and why the next wave of AI may increasingly have cameras, wheels, arms, and a physical presence.
Learn more about RealSense: https://www.realsenseai.com/
Learn more about AgenticROS: https://agenticros.com/
Connect with Chris Matthieu on LinkedIn: https://www.linkedin.com/in/chrismatthieu/
Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

What if the biggest bottleneck in defense technology is not designing better systems, but actually figuring out how to manufacture them at the speed, cost, quality, and scale modern warfare demands?
Eric Hostetler, CEO and co-founder of Volund Manufacturing, joins Greg to unpack why America’s defense industrial base needs more than individual manufacturing breakthroughs. Drawing on a career that spans Vans, Oakley, Fox Racing, Apple, Anduril, and high-end defense manufacturing, Eric brings a consumer goods mindset to one of the country’s most urgent industrial challenges: producing reliable defense hardware at scale.
At Volund, that philosophy is being applied to air-breathing propulsion systems for low-cost, attritable drones and other unmanned systems. Rather than treating the engine as the only innovation, Eric and his team are building a vertically integrated factory where manufacturing, quality control, software, automation, and production planning are designed as one system from the beginning.
In this conversation, Greg and Eric explore:
Eric’s unconventional path from BMX bikes and learning to weld to nearly 100 trips to China while building consumer products for companies including Vans, Oakley, Fox Racing, and Apple
How working on rifles for U.S. special operations helped push Eric from consumer products into defense, eventually leading him to join Anduril as one of its earliest employees
Why consumer goods taught him that cost, quality, production volume, and speed cannot be treated as problems to solve after a product has already been designed
The problem with designing defense hardware for the demo first and planning to “optimize for manufacturing” later
Why Eric believes manufacturers need to optimize the whole cost and complexity equation instead of focusing too heavily on individual technologies like AI, robotics, or automation
How Volund is building vertically integrated propulsion manufacturing for low-cost, medium-to-long-range unmanned systems
Why the factory itself is part of the product, with CNC machining, sheet metal processing, welding, heat treatment, balancing, quality systems, and other capabilities brought under one roof
How self-contained manufacturing cells can handle production tracking, metrology, quality control, and scrap decisions without creating downstream bottlenecks
Why factory software, IoT, MES integration, and automated quality systems may deliver greater gains than simply replacing human labor with robots
The propulsion supply chain challenges hiding behind bearings, investment castings, rare earth materials, chemical precursors, and other critical components
Why Eric believes parts of the existing defense industrial base may need to be replaced rather than simply funded to produce more
How aging machine shops, fragmented suppliers, cybersecurity requirements, and limited scaling expertise make rapid expansion especially difficult
Why vertically integrated, product-focused factories could become a stronger model for rebuilding domestic manufacturing capacity
What Volund’s $12 million seed round unlocks as the company works toward low-rate initial production of its first two engine sizes
Why COVID exposed the fragility of global supply chains and helped reignite investor interest in factories and domestic industrial capacity
Volund ’s approach to hiring experienced operators and engineers who understand legacy systems but are motivated to build faster, less bureaucratic alternatives
The Apple principle of “brief by exception,” and what defense companies can learn from eliminating meetings about things that are already going according to plan
Why investment casting deserves far more attention as a critical, skilled-labor-intensive foundation for propulsion and turbomachinery
For anyone building in defense tech, hard tech, robotics, or advanced manufacturing, this conversation offers a systems-level look at what it will actually take to rebuild American production capacity. The future of defense manufacturing may depend less on finding a single breakthrough technology and more on redesigning the entire factory around speed, scale, reliability, and manufacturability from day one.
Learn more about Volund Manufacturing: https://www.volundmfg.com/
Connect with Eric Hostetler on LinkedIn: https://www.linkedin.com/in/eric-hostetler-4421964/
Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

For decades, manufacturers have struggled with the same fundamental problem: there simply are not enough people to fill the jobs that need to be done. Matt Bush believes solving that problem requires changing the way manufacturers think about robotics entirely.
Matt joins Greg to share how nearly two decades running manufacturing plants shaped his approach to automation, from deploying some of the earliest collaborative robots on production lines to building robotic systems designed to feel less like engineering projects and more like everyday tools. His goal is simple: make automation easy enough that the people already working on the shop floor can deploy and use it themselves.
That philosophy led to Beacon, a unified software platform that gives manufacturers the same interface across robotic welding, plasma cutting, painting, and other applications, regardless of the underlying robot hardware. By combining standardized systems, cloud connectivity, fleet-wide software updates, and highly responsive support, Matt and his team are working to remove the friction that has historically kept robotics out of smaller and more flexible manufacturing environments.
Greg and Matt explore:
How nearly two decades running manufacturing plants taught Matt the importance of producing closer to the point of consumption, and why global supply chain fragility has reinforced that lesson
The story of "Waldo," an early collaborative robot that moved between jobs throughout a Tennessee factory and showed employees how flexible automation could become
Why employee attitudes toward robots changed once workers realized automation was taking over repetitive, uncomfortable, and undesirable tasks rather than eliminating their jobs
How labor shortages pushed Matt toward robotics as a service, including no upfront capital, limited commitment, and a model designed to reduce the financial and operational risk of adopting automation
Why decades of efforts to solve manufacturing labor shortages through education and recruiting have not been enough, and how demographic changes are making automation increasingly unavoidable
Matt's belief that robots should be viewed as tools, no differently than drills, grinders, computers, or other technologies that allow people to work more effectively
How the Beacon platform creates one consistent interface across welding, cutting, painting, and multiple robot brands while allowing manufacturers to manage entire fleets from a single system
What it takes to make industrial robotics feel "iPhone-esque," from shipping systems largely assembled to continuously removing friction from setup, programming, and operation
How customer demand has shaped the company's expansion from welding into plasma cutting, liquid painting, and powder coating
The engineering challenges of deploying robots inside potentially explosive paint environments, including intrinsically safe electronics, air-purged robot arms, and specialized operator controls
Why standardization allows robotic systems to ship in days rather than the weeks or months traditionally associated with custom automation projects
How cloud-connected robots enable fleet-wide software updates, production analytics, remote support, and fixes that can be deployed across every connected system at once
How an AI-powered support system now resolves roughly half of customer inquiries before a human needs to step in, while keeping engineers directly involved when more complex support is required
Why Matt believes robotics companies should be careful about becoming an "everything platform" and instead build deep expertise around a clearly defined set of customer problems
What Matt looks for when hiring, including attitude, curiosity, adaptability, and the willingness to ask questions rather than simply following instructions
Why engineers at the company work trade shows, interact directly with operators, and observe customers using the product so that real-world behavior can shape future software and hardware
Matt's concern that engineering education has become too theoretical, and why the next generation of robotics engineers needs far more hands-on experience
Why the biggest misconception about collaborative robots remains the idea that they are coming for people's jobs when, in Matt's view, they are increasingly filling the jobs manufacturers cannot fill at all
For manufacturers still thinking of robotics as a complicated capital project reserved for high-volume production, this conversation offers a different vision: automation that arrives in a box, works alongside the existing workforce, and eventually becomes just another tool on the shop floor.
Beacon platform: https://www.hirebotics.com/solutions/beacon-platform/
Cobot Welder: https://www.hirebotics.com/solutions/cobot-welder/
NEW Cobot Painter: https://www.hirebotics.com/solutions/cobot-painter/
New Tate case study: https://www.hirebotics.com/case-studies/tate-inc/
Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

Industrial companies apply extraordinary rigor to manufacturing, quality, and operations, yet their approach to revenue growth is often far less disciplined. Founder and principal Ed Marsh joins Greg to explore what changes when manufacturers start treating marketing and sales like an integrated system that can be measured, optimized, and continuously improved.
Ed brings decades of experience across engineering, the Army, industrial sales and marketing, international business, capital equipment, and consulting. Today, through Ed Marsh Consulting, he works primarily with middle-market industrial companies and private equity-backed manufacturers on organic revenue growth, spanning strategy, marketing, sales, technology, talent, and executive leadership.
A central idea behind Ed’s work is Overall Revenue Effectiveness, a framework inspired by Overall Equipment Effectiveness in manufacturing. Instead of accepting leakage throughout the customer journey as inevitable, Ed argues that companies should examine every stage of the revenue engine, from understanding the buyer and generating demand to qualifying opportunities, coaching salespeople, and closing business.
In this conversation, Greg and Ed explore:
Why industrial buyers care far more about operational outcomes than product features, and why sellers need to understand how a solution affects KPIs, staffing, downtime, shipments, capacity, and the buyer’s day-to-day reality
Why identifying customer pain is only the beginning of a sales conversation, and why the real focus should be the business outcome a customer is trying to achieve
How Ed developed the Overall Revenue Effectiveness framework by treating organic revenue growth as an integrated system similar to a manufacturing operation
Why small inefficiencies across marketing and sales compound into extremely low overall revenue effectiveness, even when individual parts of the system appear to be performing reasonably well
Why manufacturers would never tolerate the level of yield loss in production that they routinely accept in sales
The mindset shift required for leadership teams to bring the same accountability, rigor, process, and measurement to go-to-market functions that they already apply to operations
Why private equity-backed industrial companies often provide a fertile environment for transformation, while family-owned businesses may have completely valid reasons to prioritize margins, stability, or lifestyle over aggressive growth
What changes when Ed advises startups building AI-enabled software for manufacturers, and what remains constant about focusing on customer outcomes rather than product capabilities
Why a startup’s first salesperson can shape the company’s entire perception of sales, either reinforcing negative assumptions or establishing a powerful go-to-market culture
What founders should look for in an early sales hire, including business acumen, creativity, consultative selling skills, entrepreneurial instincts, and the ability to build systems while actively selling
Why hiring based primarily on resumes and interviews creates problems, and how a more carefully engineered and empirically informed hiring process can improve sales talent decisions
How founders should navigate the difficult transition when the person who helped build the early sales motion is no longer the right person to lead the next stage of growth
Why honesty, clear expectations, coaching, and a distinction between being "nice" and being "kind" matter when making difficult leadership decisions
How AI-first CRM platforms are transforming CRM from a manually maintained database into a memory, context, and orchestration layer that can automatically capture emails, meetings, messages, buying signals, and opportunity information
How AI can help sales managers identify coaching opportunities, prepare targeted role-playing exercises, improve forecasts, and spend more meaningful time developing their teams
Why sales coaching and role playing have declined despite their importance, and why companies often expect salespeople to perform without the structured onboarding and training provided to other functions
How manufacturers can begin experimenting with AI by building Claude skills, connecting tools through MCPs, and automating research and preparation rather than simply producing larger volumes of generic outreach
Ed’s own experiment building an AI-powered prospecting workflow that identifies ideal accounts, finds relevant contacts, enriches data, conducts research, populates CRM, and prepares prospecting blocks automatically
Why Ed believes sales is currently the bigger bottleneck than marketing, driven by fundamental changes in how buyers research, assess risk, and make purchasing decisions
The danger of vague claims around "value" in industrial marketing, and why companies need to communicate specific, differentiated outcomes
Why ethical guardrails such as the Foreign Corrupt Practices Act matter even when commercial pressure is intense, and the responsibility leadership teams have to reinforce the reasoning behind those standards
For industrial leaders, founders, sales teams, and investors trying to improve organic growth, this conversation offers a practical look at what happens when go-to-market performance is treated with the same seriousness as the factory floor, and how AI could make that revenue engine dramatically more intelligent.
Ed Marsh Consulting Website: https://www.edmarshconsulting.com/
Ed Marsh’s Youtube Channel: www.youtube.com/@EdMarsh
Connect with Ed on LinkedIn: https://www.linkedin.com/in/edwardbmarsh/
Connect with Ed on Twitter/X: https://www.linkedin.com/in/edwardbmarsh/
Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/