This episode delves into the critical infrastructure, talent, and policy challenges hindering America's manufacturing renaissance, offering direct parallels for Crypto AI investors grappling with compute scarcity, AI-driven automation, and the high stakes of scaling physical infrastructure.
Introductions: Apex & Hadrian - Building the Future of Aerospace & Defense
- Ian Cinnamon (CEO, Apex): Introduces Apex, a company focused on rapidly producing satellite buses—the core platform of a satellite—to counter China's dominance in space infrastructure deployment. Ian highlights the stark contrast: China plans 13,000+ government satellites, while the US launched just over 200 last year. Apex aims to bridge this gap with scalable manufacturing, leveraging its Los Angeles base and backing from investors like Andreessen Horowitz.
- Chris Power (CEO, Hadrian): Explains Hadrian's mission to build automated factories for the aerospace and defense industry, serving major contractors ("primes") like Lockheed Martin or Boeing, neopimes like SpaceX and Anduril, and startups. Chris emphasizes the critical problem of an aging, highly skilled manufacturing workforce (average age 62) in the defense industrial base. Hadrian's solution involves using software, AI, and robotics to “give the American worker superpowers,” enabling faster, cheaper, and onshore production, essentially building “Tesla Gigafactories” for defense hardware.
The Los Angeles Nexus: Talent, Infrastructure, and Policy Hurdles
- Both founders chose Los Angeles primarily for its unique concentration of talent, merging traditional aerospace engineering, "new space" expertise (like SpaceX), software/robotics skills drawn from Silicon Valley, and a deep manufacturing base. Ian notes, “There's really only one place on the planet that has all three of those and that is Los Angeles.” Proximity to major customers like defense primes and Space Systems Command was also crucial.
- However, LA presents significant operational challenges, particularly around basic infrastructure like power. Both speakers, along with the moderator Brian, detail extreme difficulties securing adequate power from Southern California Edison (SCE), facing long delays and bureaucratic hurdles even for high-demand industrial users. Brian recounts, “I literally tried to bribe a line crew to install larger KVA transformers... unsuccessfully sadly.”
- Permitting is another major bottleneck. Ian describes waiting 10 months for permits before a 4-week build-out, highlighting systemic inefficiencies. Chris notes spending more time and documentation on securing power and permits than on raising a $100 million Series B funding round.
- Strategic Implication (Crypto AI): The intense struggle for reliable, scalable power in LA directly mirrors the energy challenges faced by large-scale AI training facilities and crypto mining operations. This underscores the critical importance of infrastructure stability and friendly regulatory environments for compute-intensive industries. Regulatory uncertainty around licensing, as mentioned by Brian regarding energetics, also parallels potential risks in deploying novel AI or crypto technologies.
American Dynamism: A Shift in Talent, Investment, and National Focus
- The conversation highlights the rapid growth and cultural shift driven by the "American Dynamism" movement, focused on investing in critical national interest sectors like defense, aerospace, and manufacturing. Chris notes the movement, catalyzed by firms like Andreessen Horowitz, has dramatically accelerated in the last 2-3 years.
- A key change is in talent perception. Previously, working for government or defense contractors faced skepticism or even protests, as Ian experienced with a prior AI company. Now, top engineering talent increasingly seeks mission-driven roles at companies like SpaceX, Anduril, or Hadrian over traditional tech giants. Chris observes, “most of what I hear from people today is like I actually don't want to go work at Google... I want to work at H[a]drian.”
- While this shift attracts crucial talent and capital, Ian cautions that the trendiness also brings "tourist" investors who may not fully grasp the complexities or customer needs in defense and hard tech. However, for dedicated founders and investors, the momentum is strong and likely still in its early stages.
- Strategic Implication (Crypto AI): This trend signifies a broader reallocation of capital and talent towards "hard problems" and physical infrastructure, potentially competing with or complementing investments in purely digital domains like crypto and AI software. Investors should track how this movement influences talent pools and venture focus.
Navigating Manufacturing Scale: Supply Chains, Software Integration, and High Stakes
- Scaling advanced manufacturing faces immense hurdles. Ian identifies the supply chain as a primary nightmare, reliant on tier 2/3 "mom and pop shops" not equipped for high-volume production needed for proliferated systems (like satellite constellations). “The hardest part about building a satellite is having the parts to go build that satellite,” Ian states.
- Software is highlighted as a critical, often underestimated component. Ian emphasizes that software failures are the leading cause of satellite anomalies, not hardware. Apex invests heavily not just in onboard software but also in a custom operating system integrating the entire company (BD, finance, supply chain, production, engineering) to manage complexity at scale.
- Chris describes manufacturing as a relentless challenge (“getting punched in the face every single day”), requiring a delicate balance between scaling physical operations (factories, equipment, workforce) and customer demand, unlike easily scalable software. Safety, quality, and workforce training add layers of complexity.
- The financial stakes are incredibly high. Hardware investments involve massive, often irreversible capital expenditures on equipment. Brian notes the stark difference from software: “you buy it for millions and it's literally worth like a few dollars” if you need to pivot. Chris adds, “we're just betting $100 million chips on capex every single time.”
- Strategic Implication (Crypto AI): The emphasis on robust software for managing complex hardware systems resonates with the need for sophisticated orchestration in large AI clusters or decentralized physical infrastructure networks (DePIN). The supply chain fragility and high capex risks mirror challenges in securing GPUs and building out specialized compute infrastructure.
Policy Recommendations: Fueling the Manufacturing Renaissance
- Chris advocates for policies that force more demand onshore, such as tariffs or requiring DoD-funded products to have fully domestic supply chains, letting market forces build capacity. He stresses viewing the manufacturing base itself as a strategic capability.
- Crucially, Chris calls for making manufacturing “incredibly sexy and cool again” to attract the next generation workforce, countering the decades-long emphasis on four-year degrees over skilled trades. He praises the Vice President's remarks at the summit for highlighting the value of roles like electricians and machinists.
- Ian adds the need to facilitate exports to allies. While onshoring is step one, ensuring US companies can easily sell to friendly nations prevents them from turning to adversaries like China. Streamlining cumbersome export licensing processes is key to maintaining US influence and industrial base health.
- Strategic Implication (Crypto AI): Policy decisions around onshoring, tariffs, workforce development (especially STEM), and export controls directly impact the environment for all advanced technology sectors, including AI hardware development and potentially aspects of the crypto ecosystem reliant on specialized hardware or facing geopolitical scrutiny.
Revitalizing US manufacturing demands overcoming critical infrastructure bottlenecks (power, permits) and mastering the complexities of scaling physical production through automation and robust software. Crypto AI investors should monitor these industrial challenges—especially energy constraints and AI's role in automation—as they directly mirror hurdles and opportunities within the compute-intensive digital economy.
