How Nominal Turned the Pentagon’s Slowest Gate Into a Growth Engine

Featuring Cameron McCord, CEO and co-founder of Nominal

About Cameron

Cameron McCord has seen the defense ecosystem from more seats than most. He started his career as a young submarine officer, operating, in his words, with “the best of 1980s technology” and learning what it feels like to be beholden to antiquated tech when the mission is on the line. He carried that frustration into operating roles at Anduril and Saildrone, where he watched fast-growing hardware companies scale and saw the same testing problem appear at every one of them. Then he went to Lux Capital, where he saw the same pain across a thousand more companies and turned a hunch into a thesis.

Today, that thesis is a company called Nominal, one of the fastest growing, well-capitalized, and highly touted defense tech companies in the industry.

About Nominal

Nominal is a software and data platform for hardware testing operations. The hardware test market is a bit anathema for us non-technical folks. But the reality is, anyone who builds anything in the real world, whether for a commercial market or the warfighter, has to test and validate it. Until recently, that was mostly done via spreadsheets, MATLAB scripts, and hard-to-reach data. Nominal took many of the processes that befuddle founders and seasoned executives alike, and automated them. The company was incubated at Lux Capital. They intended to serve both commercial and defense customers from day one. And they’ve been on a tear, recently announcing a sole-source $53 million IDIQ for the Air Force Test Center. Today, Nominal is active in the Navy at Pax River, developed partnerships with MIT, and has some exciting news with DARPA.

After speaking time with Cam, I left convinced that Nominal really is going after the single biggest (remaining) roadblock to meaningful acquisition reform. If we don’t solve test, we cannot meaningfully shrink the divide between cool ideas in R&D and capabilities that are validated and safe to deploy. If we’re entering a tech boom cycle (and if you’re even a slightly AI-pilled reader, it’s not hard to imagine that we are), then the need to quantify risk, readiness, and the value of a test (especially one you can skip) becomes a whole lot clearer. Cameron’s whole approach is a bet that the way across the valley of death is not to test less or test faster in a vacuum, but to finally be able to prove, with data, exactly how much testing is enough.

For more on Nominal: LinkedIn | Website | X

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How Machina Labs Compressed 4-Year Lead Times Into 1 Week

About Ed Mehr

Ed Mehr is the CEO and co-founder of Machina Labs. A builder since childhood (he attended a school that emphasized welding, carpentry, and craft) Ed started his career in software before crossing over into hardware as an early engineer at SpaceX in the early 2010s. The cultural shock of moving from “ship a prototype in days” software to “wait months for a single iteration” hardware became the founding wound that drove him toward agile manufacturing. After SpaceX, he joined Relativity Space to work on 3D-printed launch vehicles, then founded Machina Labs to build the missing infrastructure he believed was the real bottleneck to America’s next industrial age: a general-purpose manufacturing platform that didn’t require part-specific tooling or CapEx. He’s a self-described capitalist and car guy, and prints small batches of his own shirts when an idea strikes him. Kinda badass.

About Machina Labs

Machina Labs is building “RoboCraftsman.” These are autonomous robotic cells that form sheet metal parts the way a potter shapes clay. Two robots come at a flat sheet of metal from either side and progressively deform it into complex 3D geometries, eliminating the need for the dies, molds, and multi-story stamping presses that have defined sheet metal manufacturing for a century. The company serves a dual-use customer base spanning commercial (Toyota is both a major customer and an investor) and defense (Air Force depots, missile primes, NASA). Machina has already deployed production cells at Air Force depots, where they’re making C-130 panels and other legacy aircraft parts that previously required hunting down donor airframes in junkyards or waiting four years for new tooling. The company is roughly 70–80 people, hiring aggressively, and approaching the end of qualification testing with parts on track to fly soon. Machina is now entering its scale phase, and Ed teases that a missile-program prime announcement is imminent…

For more on Machina:

* Careers: machinalabs.ai/careers

* Follow Ed: X | LinkedIn

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Rebuilding America’s Thermal Imaging Supply Chain

About John Hong and Tallis Chang

John Hong is CEO and Tallis Chang is COO of Obsidian Sensors. The two have worked together for over 40 years, with backgrounds in aerospace before joining Qualcomm. At Qualcomm, they were part of the team that spent nearly a decade developing low-power displays using MEMS (Micro Electro Mechanical Systems) built on glass substrates. When Qualcomm decided the program no longer fit its core business, John and Tallis were given the runway to find a new application for the manufacturing know-how they had built. That pivot became Obsidian Sensors.

About Obsidian Sensors

Obsidian Sensors, headquartered in San Diego, manufactures microbolometers — the core sensor inside thermal imaging cameras — using a fundamentally different platform than the rest of the industry. Where incumbents builds them on silicon wafers, Obsidian builds these sensors on display glass, leveraging LCD fabrication infrastructure in Japan and Taiwan that already produces millions of phone and watch displays. This shift dramatically reduced unit cost while preserving sensor performance.

The company spun out of Qualcomm in 2017 with seed capital, transferred equipment, seven team members, and five patent applications. It initially targeted the automotive market before pivoting to defense after receiving a DIU OTA at the start of COVID. Today, Obsidian is a critical supplier of thermal cameras to the US drone ecosystem, with production scaling from 5,000 units in 2025 to a planned 1 million units per year by the end of 2026 at its Top Gun Street facility in San Diego. A Phase 2 facility targeting 10–20 million units annually is planned for 2028.

Follow John: https://www.linkedin.com/in/john-h-973b372/

Follow Tallis: https://www.linkedin.com/in/tallischang/

Learn more about Obsidian: https://www.obsidiansensors.com/

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About Brian Spurlock

Brian Spurlock is VP of Growth and Strategy at Persistent Systems, and a self-described “boomerang” employee, meaning he’s had two separate tenures at the company. He came up as a Special Operations acquisitions officer at Fort Bragg, which means he’s seen the Persistent Systems story from both sides: as the government buyer evaluating the technology and as the company executive selling it. He left for a stint at AWS, returned, and is now the one figuring out how to bring tactical mesh networking from Special Operations into Army divisions. He is based in the Fort Bragg / Pinehurst area of North Carolina.

About Persistent Systems

Persistent Systems builds tactical mesh networking hardware and software: specifically, the Wave Relay and Cloud Relay systems, delivered on hardware called the MPU (currently MPU5, with MPU6 in development). The idea is simple and hard: create a mobile RF network that moves with operators, passes real data at real speeds, and requires zero thought from the person holding the radio. Founded in 2007 by two Johns Hopkins PhDs — Herb Rubens and Dave Holmer — the company has never taken outside capital. It manufactures in Manhattan. It has customers across U.S. Special Operations, conventional Army (currently scaling into division-level exercises with 4th Infantry Division), the Air Force, NATO allies, and public safety. It is on the verge of Army program-of-record status after nearly 20 years.

Follow Brian: https://www.linkedin.com/in/spurs/

For more Persistent Systems: https://persistentsystems.com/

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Building the Physical AI Platform for the Industrial Base

ABOUT ARIYAN KABIR

Ariyan Kabir is the co-founder and CEO of GrayMatter Robotics. He started the company in early 2020 alongside two co-founders, building on PhD research conducted at USC’s Center for Advanced Manufacturing, where he and one co-founder studied the intersection of robotics and AI. The third co-founder, chief scientist Satyandra K. Gupta, has spent more than 35 years working at the intersection of AI, robotics, and manufacturing and sits on multiple national boards.

Ariyan’s framing of the problem is shaped by a realization that came from the academic environment: that manufacturing (long assumed to be “solved”) is in fact one of the largest unaddressed application areas for modern AI. The US is currently short half a million skilled manufacturing workers, a gap projected to reach four million in seven years and put $2 trillion of annual GDP at risk.

ABOUT GRAYMATTER ROBOTICS

GrayMatter Robotics builds the autonomy layer for high-mix, high-variability manufacturing, the roughly 90% of factory work that cannot be addressed by traditional pre-programmed robotics. The company’s robots perform tool-manipulation tasks: sanding, grinding, polishing, buffing, coating, blasting, and inspection. Underneath the robots sits the company’s real differentiator: a foundation model for materials and processes, trained on what Ariyan describes as the largest manufacturing process dataset in the world: 7 petabytes of multimodal sensor data spanning 14–18 modalities per cell.

The business is now six years old. This interview was recorded at the company’s 100,000 sq ft Physical AI Experience Center in Carson, California, which is the company’s fifth facility. Today, GrayMatter’s customers include Boeing, Raytheon, Oshkosh, Caterpillar, Riddell, the US Navy, the US Air Force, and Huntington Ingalls Industries, where GrayMatter is a partner on the HYPR (High Yield Production Robotics) program designing the next-generation American shipyard.

The company sells outcomes, not hardware. Robots are deployed on a subscription basis with multi-year commitments, and performance compounds quarterly through software updates, recipe upgrades, and hardware refreshes.

KEY TAKEAWAYS

1. Sequence the market. Commercial first, defense second.

GrayMatter spent its first three-plus years building almost entirely in the commercial world, despite the obvious dual-use relevance of factory automation. Their reasoning was that defense customers tolerate zero failure, and an unproven autonomy stack cannot debug itself inside an aircraft program. By the time the company turned toward national security work, they had already validated the technology, the business model, and the deployment muscle.

2. The business model can be the product.

Performance Composites — GrayMatter’s first customer — had been searching for a robotic sanding solution for five years before the conversation with GrayMatter. IT wasn’t so much a capability they were missing as it was a different risk appetite: manufacturers cannot tie up millions of dollars in Capex on unproven technology. GrayMatter’s response was to invert the deal entirely: zero upfront cost, deployment first, subscription payments only after the system was producing value in production. In exchange, the customer committed to a multi-year contract. The structure became the wedge that opened the entire Fortune 100.

3. Adoption became the geostrategic moat.

Asked how 7 petabytes of US manufacturing data compares to South Korea or Shenzhen, Ariyan reframed the question. The race isn’t about dataset size. The US ranks near the bottom of the top 10 in robot-to-worker adoption ratios; South Korea is #1 and China is climbing fast. Tonnage-wise, China has built more ships in the last 12 months than the US has built since WWII. This reframing has direct strategic implications: a defense industrial base strategy that focuses on technology sovereignty without obsessing over diffusion velocity will lose to one that does the opposite.

4. GrayMatter builds AI into every layer.

GrayMatter identifies eight distinct layers of engineering work that sit between a customer problem and a delivered outcome: industrial engineering, solution engineering, process recipe engineering, cell design, tool/fixture design, implementation, sustainment, and digital-twin operations. Most robotics companies put AI in one layer: the robot. This means the other seven can become bottlenecks. But GrayMatter is now deploying domain agents at every layer, coordinated by an orchestration layer the company calls Factory Super Intelligence (FSI). The focus on under-appreciated elements of the solution set has helped them differentiate.

5. Hire from the intersection. The mixing room doesn’t work.

GrayMatter’s most expensive hiring lesson was that you cannot assemble a great physical AI team by recruiting the best AI specialists, the best manufacturing engineers, and the best roboticists into a room. The translation cost is too high; each discipline optimizes for its own definition of the problem. What does work is hiring people who already live at the intersection of at least two of the three domains, then leveling them up on the third. The company’s head of customers came from Tesla. Their head of aerospace and defense was two steps below Boeing’s CTO. Their head of hardware also came from Tesla. This was a counterintuitive lesson, but one that stuck with me most from the conversation.

Follow Ariyan: https://www.linkedin.com/in/ariyankabir/

For more GrayMatter: https://factory.graymatter-robotics.com/

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About Ben

Ben Cipperley spent 26 years in the Navy. The first 18 he served as an Explosive Ordnance Disposal office, with three tours across the Indo-Pacific, three years between Iraq and Afghanistan, and command in Guam. Which is to say, he has more experience than most.

What makes his background unusual isn’t the operational experience; plenty of veterans make the transition. It’s the Pentagon chapter that came after. A fellowship at the Stimson Center led to a resource sponsor role writing the Navy’s budget, which led to being pulled onto the team drafting the 2022 National Defense Strategy (mid-process, while Russian forces were marshaling in Belarus). Which led to working under the CNO on what became the Navy’s first force design document in 50 years. It’s a classified vision for the fleet in 2045 that, he notes, had quite a few robots in it.

He put an “Open to Work” banner on LinkedIn when he retired. The CEO of Havoc called him 20 minutes later.

About Havoc AI

Havoc AI is a collaborative autonomy software company. The pitch is deceptively simple: one operator, thousands of autonomous systems. The technology is the connective tissue, the software layer that lets a surface drone, an aerial drone, and a ground vehicle share a common operational picture and respond to commands from a single interface, rather than requiring separate operators, separate control systems, and separate data pipes for each platform.

The company was born from a conference convened by then-Undersecretary of Defense Heidi Shyu around the concept of “Hellscape,” IndoPaCom’s deterrence concept for a Taiwan scenario involving massive swarms of autonomous systems. The question in the room wasn’t whether the platforms existed. It was: how do you make thousands of them work together when a human brain can only track so many things at once? Founders Paul Lwin and Joe Turner quit their jobs the next day and started building the answer.

Early validation came through Silent Swarm, an exercise run by Naval Surface Warfare Center Crane. Havoc showed up with 12 prototypes of their Rampage platform. Representatives from NIWC Atlantic watched, then bought the prototypes on the spot. Those units shipped to Portugal to support Task Force 66. That’s the loop Havoc is now trying to close, and why they recently acquired Mavrik (air) and Teleo (ground) to make good on the multi-domain part of the pitch.

The business model is worth understanding clearly. The government is bad at buying software. It tends to need software wrapped in a hardware container before it can conceptually acquire it. Havoc has internalized this and partnered with eight different maritime platform builders, plus air and ground hardware partners, so that their autonomy stack arrives pre-integrated with best-of-breed hardware. They’re not trying to be the OS layer that makes everyone else’s platforms work together. But they’ll sell you the hardware too, because that’s how you get the check.

For more about Havoc AI: https://havocai.com/

Follow Ben: https://www.linkedin.com/in/bencipperley/

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Crossing the Valley explores the journey from proof of concept to production in defense technology. New episodes weekly.

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About Luke Fischer

Luke Fischer is the CEO and co-founder of SkyFi. He is a former U.S. Army helicopter pilot and Special Operations veteran who transitioned through DIU (Defense Innovation Unit), Uber Elevate (as Head of Flight Operations), and Joby Aviation (leading government operations) before founding SkyFi in late 2021. He also spent time as an Entrepreneur in Residence in VC, which gave him direct exposure to what gets funded — and what doesn’t. That multi-domain journey across military, Big Tech, and venture is core to how he built SkyFi.

About SkyFi

SkyFi is a geospatial intelligence marketplace and platform that aggregates satellite imagery and analytics from hundreds of commercial satellite operators — making it accessible to any customer, anywhere, via web or mobile app. Rather than owning or launching satellites, SkyFi sits at the aggregation layer: abstracting away which provider owns the satellite and letting users task imagery or pull analytics with a button press. The business is currently approximately 80% government / 20% commercial, serving customers ranging from top global hedge funds and agriculture companies to Special Operations Forces, NATO, and allied governments across Asia. SkyFi closed its Series A in December 2024.

For more SkyFi: skyfi.com

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Follow Luke: https://www.linkedin.com/in/lukemfischer/

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About Todd Stiefler

Todd Stiefler is VP of Enterprise at WHOOP, overseeing the company’s B2B and B2G business lines. He brings an unusually cross-functional background to the role: a decade as a Senate defense staffer focused on missile defense and strategic nuclear deterrent, followed by product and commercial leadership roles at GE’s industrial IoT division, LMI, and Palantir. A self-described “tech nerd” and ultra-marathoner who finished the Leadville 100 in 27 hours, Todd found WHOOP the way most people find things that change their lives — by accident, scrolling LinkedIn late one night. He’s been building the company’s defense business ever since.

About WHOOP

WHOOP is a Boston-based wearable technology company focused exclusively on human performance and health optimization. Unlike general-purpose smartwatches, WHOOP does one thing: continuously measures high-fidelity physiological data — heart rate variability, resting heart rate, respiratory rate, skin temperature, and strain — and translates it into actionable metrics around sleep, recovery, and readiness. Its early customers included elite professional athletes, and it has since grown into a mass-market product worn by hundreds of thousands of consumers and, increasingly, military personnel. WHOOP is actively pursuing the DOD enterprise market, partnering with programs like SOCOM’s POTD and the Army’s Holistic Health and Fitness (H2F) initiative. The company’s enterprise division, led by Todd, handles everything from individual unit programs to large-scale institutional deployments.

Key Takeaways

1. Build for your most demanding user first.

In contrast to the “minimally viable product” framework, WHOOP’s early decision to build exclusively for elite athletes — with LeBron James and Michael Phelps among their first 100 customers — wasn’t a marketing stunt, but a product strategy. By targeting the most demanding performance environment, they built something rigorous enough to eventually serve everyone else. That same logic attracted special operators before conventional forces, and conventional forces before institutional DOD programs. They solved for the “edge cases” first rather than the average user, because they were solving their distribution challenge through their product design.

2. But the right product alone isn’t enough… you still have to solve the process.

Todd was direct about what WHOOP got wrong in its early defense push: they had a best-in-class product but hadn’t built the surrounding infrastructure. No contract vehicles. No data sharing agreements. No pricing architecture tuned to government procurement. “The DOD buys from people that solve their process, not their problem.” Getting that right — not just shipping a great device — is what actually enables scale. So while many of us laugh at high-ceiling IDIQs without real funding, the vehicle is a key ingredient.

3. The wearable itself is actually not the intervention.

This was one of the most important points from the episode: motivated, self-selected consumers who buy WHOOP on their own are signaling their desire to change their behavior. Warfighters handed a device in a conference room, with no context, no coaching, and no program design, often won’t. Even though the average warfighter may be more attuned to their body than the average civilian, in this case, if the warfighter doesn’t opt in, the product won’t deliver. This insight is why Todd never sees WHOOP going to a “push to all” rather than a “pull” based sales motion. If it’s foisted upon people, it will not produce the desired effect.

4. In federal sales, relationships and strategic partnerships beat conference booths.

Todd assesses that in the defense market, niche events where you can have real conversations, and partnerships with athlete management system providers who can pull WHOOP into their stack, have been the most valuable sources of leads. Trade show booths? Much less effective. As always, your mileage may vary, but it’s another reinforcing data point suggesting deep, niche relationships beat a larger breadth with high impressions.

5. Sell sustainable programs, not hardware deployments.

Todd’s north star for WHOOP’s next 12 months is helping customers build programs that will still be running in five years. That means bringing in WHOOP’s human performance experts and solution architects early, co-designing integration with existing data platforms, and being the vendor who asks, “What are you actually trying to achieve?” before taking the purchase order.

For more Crossing the Valley: valleycrossers.com | LinkedIn

For more on WHOOP: WHOOP.com

Follow Todd: https://www.linkedin.com/in/toddstiefler/

Follow Noah: https://www.linkedin.com/in/noahsheinbaum/

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About Byron Boots

Byron Boots is the co-founder and CEO of Overland AI. Prior to starting the company, he was an associate professor in computer science at the University of Washington, where his research focused on machine learning and robot autonomy. Byron served as principal investigator on DARPA’s Racer program, one of the most ambitious off-road ground autonomy challenges the agency has run since its landmark Grand Challenge series in 2004–2005. It was in that role — out in the field, iterating under adversarial test conditions — that the insight and technology behind Overland AI took shape.

About Overland AI

Overland AI builds autonomous ground vehicle software and systems for the U.S. military. Their flagship platform, ULTRA, is a purpose-built unmanned ground vehicle with upgraded suspension, miniaturized compute, and a suite of sensors including stereo cameras, LiDAR, thermal cameras, and Starlink — capable of GPS-denied navigation in extreme off-road terrain.

The company operates across four primary concept of operations: ISR (intelligence, surveillance, and reconnaissance), logistics and resupply, layered protection (including counter-UAS), and breaching. Their go-to-market approach has been almost entirely driven by demonstrated field performance. Initially this came through DARPA experiments, then through DIU and direct work with Army and Marine Corps units. Overland has won contracts including the DIU Ground Vehicle Autonomous Pathways program and is currently focused on scaling into formations and establishing a permanent operational presence with the services.

Key Takeaways

Five principles from Byron’s journey that apply broadly to defense tech founders:

* Field, first. One of the most counterintuitive decisions Byron made at University of Washington was to hire strong vehicle mechanics as some of his first team members. It’s a simple but counterintuitive logic. You don’t have to build the perfect software in the lab before you put it on the vehicle because if vehicles could be repaired rapidly in the field, the software team could test more aggressively, fail faster, and iterate without fear. Thus, the vehicle mechanics gave the rest of the team leverage.

* The best BD is performance (with the lights on). Overland AI’s early business development was almost entirely organic. I pressed him on DARPA’s checkered history of transitioning programs, but in this case, DARPA invited the other services to watch their field experiments. Those experiments were credible, because the company often didn’t know what was coming. It wasn’t a PowerPoints brief or a table top conversation; it was an opportunity for customers to see the tech in action. That credibility dramatically accelerated their sales path.

* Build on top of what works. Byron’s framework for capability development is deliberate: get one robot working reliably, then add a second, then build multi-vehicle coordination. Don’t architect for the end state. Prove each layer before adding the next. This mirrors successful product development in commercial software but is even more important in defense, where integration failures in the field are immediately visible and costly.

* “If it’s not seamless, it won’t survive contact with the warfighter.” Despite the old saying “good enough for government work,” the operational bar for defense products is actually quite amorphous. Byron observed that “a slow or unreliable robot simply gets abandoned.” In other words, your project might die without you even knowing. The product actually has to perform well enough that operators don’t think about it. Only then can you expand the mission set, add payloads, or introduce multi-vehicle coordination.

* It’s not about your tech. The sooner you embrace this, the faster you’ll win.

Winning a contract gets you in the door, but a contract isn’t the same thing as winning warfighter trust. Byron draws a clear distinction between them. Overland's next 12 months aren't going to be defined by new contracts as much as they are going to be defined by creating "a permanent presence" with Army and Marine Corps units. I love this point because it suggests a totally different motion. It’s not about closing the deal or renewing it. It’s not about another slide or another meeting. It’s about doing things that don’t scale, having people side by side with the mission owners, and obsessing over the question of how to make your technology invisible inside existing workflows rather than celebrated as a novelty.

For more Crossing the Valley: valleycrossers.com

For more on Overland AI: www.overland.ai

Follow Byron: https://www.linkedin.com/in/byron-boots/

Follow Noah: https://www.linkedin.com/in/noahsheinbaum/

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What happens when a Friday morning coffee turns into a term sheet by Sunday night?

In this episode, Forterra CEO Josh Araujo is joined by Ari Schuler, a returning CTV guest, to take us inside Forterra’s acquisition of goTenna.

Company Overview

About Forterra: Ground autonomy company enabling war fighters to shoot, move, and communicate more effectively. Technical stack includes autonomous driving systems, mission payload integration, and now mesh communications through the goTenna acquisition. Working with military customers across operational theaters. Founded 20+ years ago (as Robotic Research), recently closed Series C while simultaneously acquiring goTenna.

About goTenna: Mesh networking communications company providing interoperable comms, born from Hurricane Sandy in Brooklyn. Pivoted from consumer to military/public safety after discovering product-market fit with operators in Afghanistan, Iraq, and the southern border. Technology enables high node-count networks (100+ devices) sending low-bandwidth position/location data, critical for blue force tracking and preventing friendly fire.

About our Guests

About Josh Araujo: CEO of Forterra, building autonomous ground vehicle technology for military operations. Retired Marine, and Jefferies investment banker covering aerospace and defense. Joined Forterra (then Robotic Research) in 2021 as the first non-technical hire, now leading a company with 20+ years of autonomy innovation transitioning to programs of record.

About Ari Schuler: Former CEO of goTenna, now leading the communications division at Forterra. Built goTenna’s pivot from consumer to B2G, deploying mesh networking technology in conflict zones globally. Former DHS official who created Customs and Border Protection (CBP)’s innovation team, bringing government operator perspective to commercial tech development.

Key Takeaways

1. Skip the vitamin, find the medicine.

Ari’s mentor gave him a deceptively simple framework: are you selling something people want (vitamins), or something they can’t live without (medicine)? goTenna started as a consumer product, but product-market fit became unmistakable once the technology hit Afghanistan, Iraq, and the southern border. Ari explains that when you found the true medicinal use case, you go all in. Straddling consumer and government markets wastes capital and credibility that companies don’t have to spare.

2. The ability to sustain operations in the field is the real moat.

Both Forterra and goTenna had extraordinary technical pedigrees: Forterra’s co-founder holds 100+ patents, and goTenna’s mesh protocols are proprietary and deeply differentiated. But Josh was explicit: deploying at scale into combat environments is “miles apart” from having a cool demo. The muscle required to do customer success, field maintenance, and operational support in places like Afghanistan or Ukraine is not taught in any graduate program.

3. In M&A, cultural alignment is what ultimately determines deal success or failure.

The core of the conversation centers on how Josh turned a term sheet around in 72 hours, from a Friday morning coffee between Ari and Scott Sanders (another CTV alum), to an afternoon board meeting, to a signed term sheet by Sunday night. This kind of speed is not only a function of high caliber financial modeling and expertise, but of a clear strategic rationale and cultural fit. Josh talked about his view that even the best business alignment in the world can’t overcome a cultural mismatch. Culture doesn’t mean squishy values in this case. It refers to the companies’ shared mission focus, values, and tech stack (NetSuite, Arena, JIRA).

4. The defense VC funding model is creating a structural problem for which consolidation is the only solution.

Josh flagged a concern that most defense tech founders are quietly aware of: many of the best companies in this space have great technology, great teams, and genuine product-market fit, but lack venture-scale TAMs. VC math requires one in a hundred to go 100x. At the risk of sounding trite, that calculus alone will not support the entire ecosystem of mission-critical hardware businesses. As a result, if venture is the primary tool, companies that shouldn’t fail will fail because of capital structure problems. This is why Josh is shaping Forterra into a leading consolidator to create a home for these companies.

5. In a post-merger integration, the first priority is “do not break what’s working for the customer.”

Too many post-merger integration efforts try to move fast, combine everything, and extract synergies. In this deal, Josh and Forterra explicitly rejected this. The approach has been phased and deliberate: first, validate the technology combination (goTenna’s X2m module was physically integrated into Forterra’s Vector platform within 30 days, achieving 25x the range of the previous radio). Second, resource the acquired team to execute on their existing pipeline. Third, after the teams have developed organic trust, start to combine go-to-market and engineering functions. This cadence matters because defense vendors cannot afford to push artificial disruptions on their customers. As Ari explains, “We can figure out the HR systems. What we can’t do is mess up operational deployments.” The customer relationship is paramount.

For more:

* Website: Forterra | goTenna

* LinkedIn: Forterra | goTenna

* Follow Josh: https://www.linkedin.com/in/josh-araujo/

* Follow Ari: https://www.linkedin.com/in/ari-schuler-1ab93239/

* Follow Crossing the Valley: https://www.linkedin.com/company/102082197/

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.valleycrossers.com