Jacob Helberg

Pax Silica’s first major product-like rollout is a 4,000-acre State Department-custodied “economic security zone” in the Philippines, roughly one-third the size of Manhattan. Phase one treats the land as diplomatic property; a two-year negotiation is intended to set taxation, investor protections, and safeguards for a multidecade private build-out. Helberg also previewed a possible June rollout of four or five additional lines of effort, including logistics with large corporates.

Helberg’s break with China’s Belt and Road Initiative is to make companies—not government-owned operators—the organizing layer of economic security. He credits Belt and Road with securing China’s inputs, but argues central planning also creates overpriced “roads to nowhere” and liabilities that can jump from X to 10X. Guo adds that Chinese workers and companies often perform the work, and that debt can convert into Chinese equity when host countries default. America’s answer: “We’re not going to do government-operated supply chains because that’s not how we shine as a country.”

The strategic bottleneck extends far beyond chips into thousands of inputs, including precision reducers, server motors, rare-earth magnets, and actuators. Helberg says China “completely” dominates the robotics supply chain, making the Philippines—with its existing manufacturing base and alliance alignment—a potential site for a robotics bet. The proposed zone is a platform that should ultimately “live outside of the government as a private service.”

Reindustrialization does not mean placing every supply-chain link inside the United States. America is 4% of the world’s population but accounts for roughly 20–30% of global consumption; with unemployment around 4%, closing part of the production gap would require highly autonomous factories and ports. Semiconductor fab production should continue as a domestic effort because talent is finite and the work is capital-intensive, while allied production follows a “hub-based approach.”

Critical-minerals policy is moving from diagnosis to coordinated supply investment and demand-side pricing deals. A February 4 State Department summit drew more than 55 countries, followed by mineral MOUs with dozens of them; Helberg said the administration is also allocating capital to projects. Because Chinese subsidies can undermine commercial viability, he was “incredibly confident” the minerals-pricing issue would be resolved before the administration ends.

Private capital’s highest-value role is evaluating execution risk and surfacing technological substitutes. Helberg wants venture investors to identify operators capable of delivering aggressive industrial projects, using their judgments as a signal for government allocations. The larger upside is a “rabbit out of a hat situation”—new materials or rare-earth-free magnets solving concentration risk through innovation rather than subsidy alone.

Durability remains the unresolved risk behind the strategy’s ambitious pace. Asked how executive-order-driven policy survives a new administration, Helberg could only say tax reform is “very sticky” and that officials are building evergreen platforms; he also cited, “from memory,” an early order targeting a quadrupling of domestic nuclear supply. For companies, the near-term agenda is market access across Japan, South Korea, and India, allied supply-chain partnerships, and rules protecting hundreds of billions invested in AI from model distillation.

Helberg frames “Trump time” and America’s “global underdog” identity as operating advantages rather than rhetoric alone. The administration’s appetite for speed and risk mirrors founders who hear “no 45 times before getting to a yes”; internationally, he argues that same private-sector temperament supports “positive-sum” partnerships. His closing claim is that American resilience comes from behaving like a challenger even when others cast the country as the established power.

🔗 Original source & video: Pax Silica: Inside the Trump Administration’s Tech Strategy with Jacob Helberg

Jacob Helberg’s core macro call is that AI, deregulation and abundant energy could shift the U.S. from a consumption-led service economy toward a high-investment industrial one. CapEx is already above 2% of GDP and could double by next year; Helberg cites analysis saying AI added a full percentage point of GDP in the last year, while the economy grew 3%.

Supply-chain security requires insulating Western producers from China’s ability to crush prices and later restore them. Helberg highlights 90% reliance on critical minerals refined in China, reliance on semiconductors manufactured in Taiwan and the $750 million DoD–MP Materials partnership. Its anchor buyer, offtake agreement and price floor are his blueprint for countering “classic monopolistic behavior” without leaving U.S. manufacturers begging Beijing for magnet licenses.

Helberg believes AI will erase much of developing economies’ labor-cost advantage by giving American workers “superpowers.” Companies could employ fewer people, but he expects competitors and what he argues are unlimited human wants to push them toward tenfold output instead. Jevons Paradox implies cheaper, more efficient production creates more demand. The upside case is Sarah Guo’s framing—“What if the economy was $45 trillion?”—rather than mass technological unemployment.

The “superintelligence century” could produce a second great divergence between early AI adopters and laggards. Helberg contrasts Europe’s fall from 65% of global GDP in the early twentieth century to roughly 15% today with a tech-forward Middle East where, he says, GDP per capita in the UAE and Israel exceeds France’s and is also higher than South Korea’s. His diagnosis is that Europe repeatedly “missed the boat,” and the EU AI Act may ensure it is not a first mover.

The next platform contest is whether the Global South imports an American stack led by NVIDIA or a bundled Chinese stack built around Huawei Ascend and DeepSeek. Elad Gil presses the open-source risk; Helberg calls Meta’s efforts important but argues DeepSeek is “not really open source,” alleging that it lied about its compute capacity, has a billion-dollar cluster and distilled ChatGPT model weights. The strategic objective is not one licensing model but making the best American models widely used.

Nuclear is Helberg’s preferred route to a potential doubling of U.S. electricity production in the 2030s, but financing time is the decisive variable. Large plants cost dozens of billions and can take seven years; Gil notes that protests and regulatory delays can turn a five- or six-year build into twelve years, while interest and legal costs compound. Helberg favors faster permitting and a clear CFIUS path for trusted foreign capital, alongside natural gas and clean coal in an “all-of-the-above approach.”

The broader investment regime is meant to reward builders across every layer—energy, minerals, components, chips, data centers, models, apps and logistics. Helberg describes administration policy as “shock therapy” through deregulation, lower taxes and foreign investment, with autonomous transportation offering a way to leapfrog old infrastructure. Defense is another major spending area: global spending reached a record $2.7 trillion, but how governments allocate it will determine whether their forces are real capabilities or “paper tigers.”

🔗 Original source & video: Reshaping America’s Economy for the Superintelligence Century with Jacob Helberg

Washington’s 90-action AI plan treats innovation, physical infrastructure and global ecosystem reach as one national-security strategy. Jacob Helberg laid out the plan’s pillars: America must out-innovate competitors, accelerate data centers, energy and domestic manufacturing, then create the AI stack for the world. The plan targets actions achievable within six to nine months because “you can’t regulate your way to winning the AI race.”

The investable bottleneck is shifting from model intelligence to power, permitting, machine tools and skilled labor. Michael Kratsios wants federal scientific data made usable, not merely open, while warning that AI will enter regulated products from drones to medical diagnostics. Jacob Helberg separately flagged more than 1,000 proposed or enacted state measures as a potential path toward “a patchwork of 50 different state regulatory regimes.”

Hadrian’s factory results support the episode’s central labor thesis: AI can create industrial capacity where qualified workers no longer exist. Chris Power reported 4x manufacturing productivity, 10x workforce productivity and 30-day training for recruits entirely from non-factory backgrounds; the company’s Arizona expansion is planned at four times the Los Angeles facility’s size with 350-plus jobs. “Hadrian’s advanced factories look and operate more like a data center.”

Gecko Robotics reframed energy as both AI’s constraint and one of its highest-return applications. Jake Loosararian’s example began with a 620-megawatt plant producing only 580; robotic inspection and AI reportedly unlocked 1% efficiency, which he extrapolated to 11.9 gigawatts across the US thermal fleet “without putting a shovel in the ground.” His call: “AI shouldn’t just consume, it should create energy.”

Palantir’s Shyam Sankar sees the strongest adoption where frontline workers author the applications and institutional leadership releases their agency. He wants workers made 50 times, not merely 50%, more productive; cited factory training falling from three years to three months; and described a four-week fellowship for mechanically intuitive, often self-taught workers. His categorical conclusion was that “the traditional college degree is dead.”

Paul Buchheit’s abundance case is that natural language expands the pool of builders, while capital intensity preserves scarcity at the model layer. With only 2%-3% of Americans able to code—and perhaps half that number capable of building a startup—“English is the new programming language” could produce 10x or 100x more startups, robotics companies and local applications. Buchheit expects the number of foundation-model providers to remain relatively stable, with open source constraining censorship and lock-in among closed vendors.

Small businesses are positioned as AI’s distribution channel, but the resulting market may be a barbell rather than a universal uplift. Kelly Loeffler said 60% of the SBA’s $21 billion lent this year went to companies with one to five employees; Keith Rabois expects those firms to gain incumbent-grade information, products and administration, then take share from the mid-market while compute leaders such as NVIDIA also benefit. The counterweights are energy and materials costs, industrial supply-chain exposure, rigorous underwriting and Power’s warning that offshore competition remains “companies versus the CCP.”

🔗 Original source & video: Winning the AI Race Part 1: Michael Kratsios, Kelly Loeffler, Shyam Sankar, Chris Power