The United States must significantly reindustrialize to ensure its military security, as its current reliance on foreign supply chains for critical components like actuators is a major vulnerability.
The US military should pivot investment from traditional assets like aircraft carriers to AI-enabled drones, as AI is fundamentally changing the cost-exchange ratio and nature of warfare.
A major, disruptive increase in memory prices is imminent due to high demand from AI data centers, posing a catastrophic risk to consumer hardware, robotics, and physical AI companies.
The development of a true 'AI for hardware engineering' is severely hampered by the lack of public training data, as 3D CAD files are highly proprietary corporate assets.
She left OpenAI due to fundamental disagreements with its governance, decision-making speed, and lack of guardrails concerning its partnership with the Department of Defense.
Apple Tenure
Worked on products like the MacBook Air, learning principles of 'ruthless efficiency,' maintaining a high bar for excellence from Steve Jobs, and prioritizing core design goals by removing non-essential features.
Meta/Oculus Tenure
Focused on professionalizing the hardware development process for VR, leading a cost-reduction redesign that made the Quest 2 the highest-selling VR headset. Also worked on advanced but not-yet-mass-producible AR technology like the Orion glasses.
OpenAI Tenure
Experienced Sam Altman's leadership style of pushing teams to think at a 100x to 10,000x scale.
Departure from OpenAI
Left the company due to disagreements over the speed of decision-making, governance, and the lack of defined guardrails surrounding a deal with the Department of Defense.
Post-OpenAI Analysis
Synthesizes her career experiences to publicly advocate for US reindustrialization, warn of impending hardware supply chain crises, and analyze the AI-driven shift in military technology.
▶The Geopolitical Imperative for US ReindustrializationMay 2026
Kalinowski argues that the decades-long outsourcing of the entire manufacturing supply chain, from raw materials to actuators and assembly, has created a critical national security vulnerability for the United States. She contends that re-establishing domestic, at-scale manufacturing is not just an economic issue but a prerequisite for military readiness and independence in an increasingly unstable world.
Investors should monitor companies involved in domestic advanced manufacturing, robotics components (especially actuators), and supply chain resilience, as Kalinowski's perspective suggests a potential policy and capital shift towards onshoring these critical industries.
▶The AI-Driven Transformation of Warfare
According to Kalinowski, AI is rendering traditional military doctrine and hardware obsolete. She points to the unfavorable cost-exchange ratios the US faces in missile defense and the rapid, 3D-printed iteration of drones in Ukraine as evidence that future conflicts will be won by cheaper, smarter, and more numerous autonomous systems.
This theme indicates that defense sector investments may see a strategic shift from legacy platforms (aircraft carriers, manned fighters) towards companies specializing in AI, autonomous systems, drone technology, and rapid prototyping.
▶Hardware Development in the AI Era: Bottlenecks and BreakthroughsMay 2026
Kalinowski provides a practitioner's view of the immense challenges in creating physical products, from the limited number of possible iterations to catastrophic supply chain risks. She predicts a 'meteor' of rising memory prices will impact the entire sector and notes that the lack of proprietary CAD data is a major hurdle for training AI to assist in hardware design.
Analysts should be aware that hardware-centric AI companies face unique, non-linear risks compared to software companies; supply chain disruptions, particularly in memory and key components, can trigger 'catastrophic redesigns' that derail product timelines and budgets.
▶Lessons from Visionary Tech LeadershipMay 2026
Drawing from her experiences with Steve Jobs, Sam Altman, and Mark Zuckerberg, Kalinowski synthesizes key traits of effective tech leadership. These include maintaining an unwavering high bar for excellence (Jobs), pushing teams to think at a 100x-10,000x scale (Altman), and being deeply engaged in technical details (Zuckerberg).
When evaluating tech companies, particularly in capital-intensive hardware sectors, the leadership's ability to combine ambitious, large-scale vision with deep technical understanding is a critical indicator of potential success.