Edward Conard

Top Ten New York Times Bestselling Author

  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Thursday, June 18, 2026

AI Summary. The authors find AI-native U.S. startups are 25% smaller than non-AI startups in the same industry and cohort, with 13% higher engineer shares, roughly 15% lower shares of entry-level workers and managers, flatter hierarchies, and comparable valuations. They argue embedding AI into products lets firms scale knowledge work without large teams.

Hyunjin Kim and Rembrand Koning Social Science Research Network
Date Posted:

“AI native” firms – firms organized around AI founded btw 2020 and 2024 – had headcounts ~25% lower than their industry peers. These firms’ share of engineers is ~13% higher, while their share of entry-level workers and managers is ~15% lower.

How do AI-native startups differ from other startups in workforce structure?

Core argument: AI-native startups are 25% smaller than non-AI startups in the same industry-cohort, yet their valuations are comparable, which the authors say suggests higher value created per employee.

Drawing on Y Combinator batches W20–F24 and U.S. venture-backed startups whose first financing closed between 2020 and 2024, we classify each firm’s AI-native status and link it to workforce microdata on team size, function, seniority, and hierarchy. Relative to non-AI startups in the same industry-cohort, AI-native firms are 25% smaller. Their share of engineers is 13% greater, and the shares of entry-level workers and managers are each roughly 15% lower. Their hierarchies are half a seniority level flatter—yet valuations are comparable, suggesting higher value created per employee. We argue these patterns reflect two channels: a process channel, in which AI changes how people work inside the firm, and a product channel, in which AI capabilities are built into what the firm sells. Using text from product descriptions and job postings, we find that embedding AI into the product, beyond layering on AI tools into existing workflows, is a primary way startups are scaling “knowledge work” without large teams of knowledge workers.

Takeaways by Macro Roundup® AI

  1. AI-native startups are 25% smaller than non-AI startups in the same industry-cohort, yet their valuations are comparable, which the authors say suggests higher value created per employee.
  2. In AI-native firms, the share of engineers is 13% greater, the shares of entry-level workers and managers are each roughly 15% lower, and hierarchies are half a seniority level flatter.
  3. Drawing on text from product descriptions and job postings for Y Combinator batches W20–F24 and U.S. venture-backed startups first financed between 2020 and 2024, the authors find embedding AI into the product is a primary way startups scale knowledge work without large teams.

Related Articles:

  • Attention (And Money) Is All You Need: Why Universities Are Struggling to Keep AI Talent — The annual compensation gap between top industry and academic artificial intelligence researchers widened from roughly $294,000 to $1.5m, coinciding with accelerating academic out-migration toward large incumbent technology firms. Researchers who move to industry cut paper production by about 63% while increasing patent filings nearly sixfold, consistent with a shift from open science toward proprietary innovation.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
  • Solopreneurs, Solow, and the SaaSpocalypse — For three decades after commercial electricity delivery began in 1882, inflation-adjusted output per worker grew just 0.5% annually, accelerating to more than double that pace only after factories were redesigned around electric motors rather than retrofitted from steam. The author argues a near-term absence of productivity acceleration from AI is not evidence none is coming.

AI Summary. Computing infrastructure's share of US nominal gross domestic product held near 0.5% from 2015 to 2022 before climbing toward about 1.6% by 2026, with the increase coming from AI compute hardware, data center construction, and networking while non-AI compute spending stayed flat. The buildout is a concentrated bet by a small number of hyperscalers, concentrating both upside and systemic risk.

Paul Kedrosky Applied Complexity
Date Posted:

The AI buildout has driven computing infrastructure’s share of GDP to ~1.6%, ~ double that of 2024. Kedrosky notes the buildout is “a narrow, concentrated bet by a small number of hyperscalers. This concentrates both the upside and the systemic risk.”

How much has AI spending raised computing's share of GDP?

Core argument: Computing infrastructure's share of nominal US GDP held near 0.5% through 2015–2022 before breaking upward around 2023, nearly tripling to approach 1.6% of GDP by 2026, according to an Epoch figure.

I have written about the sharply growing role of AI capex in US GDP growth, but it is now becoming material in GDP outright. [An Epoch figure shows] the ongoing AI infrastructure buildout has compressed a decade of capital spending into about two years. Computing infrastructure's share of nominal US GDP sat near 0.5% for most of the 2015–2022 period, with a gentle upward trend. Then it broke sharply upward around 2023, nearly tripling to approach 1.6% of GDP by 2026. This was driven almost entirely by AI-related compute hardware, data center construction, and networking layered on a non-AI compute data center base that never moved. Non-AI compute hardware (~0.66% of GDP) has barely budged. The entire increment is AI-specific. The buildout is not a broad-based tech investment but a narrow, concentrated bet by a small number of hyperscalers. This concentrates both the upside and the systemic risk.

Takeaways by Macro Roundup® AI

  1. Computing infrastructure's share of nominal US GDP held near 0.5% through 2015–2022 before breaking upward around 2023, nearly tripling to approach 1.6% of GDP by 2026, according to an Epoch figure.
  2. The entire increment in computing's GDP share is AI-specific, coming from AI compute hardware, data center construction, and networking, while non-AI compute hardware has barely budged at roughly 0.66% of GDP.
  3. The AI infrastructure buildout has compressed a decade of capital spending into about two years as a narrow bet by a small number of hyperscalers, concentrating both the upside and the systemic risk.

Related Articles:

  • The Macro Implications of the AI Capex Boom — Artificial intelligence capital spending is estimated to add roughly 1.4 percentage points to US growth in one year and about 1.5 points the next, comparable to business investment's contribution during the tech bubble. A material part of that estimate reflects profits at Nvidia and a few other chipmakers that are unlikely to be recycled back into the economy.
  • AI Set to be Largest CapEx Cycle Ever … and Soon Majority Externally Financed — Hyperscaler and data-center investment is tracking toward $1.5tn annually by 2030, which in real terms would exceed the 2005-06 housing boom, the 1990s fiber peak, and the 1882 railroad peak combined. External debt and equity are projected to fund close to 90% of the buildout, making it dependent on credit markets.
  • How Much Is Donald Trump Costing America’s Economy? — Excluding artificial-intelligence-related categories, US non-residential fixed investment has contracted at roughly a 3% annual rate over the past year, versus average growth above 5% in the prior decade, running about $130bn below trend and cutting GDP growth by roughly 0.4 percentage points. Credit remains plentiful, with tight corporate bond spreads.

AI Summary. Workers most exposed to artificial intelligence are substantially more educated than those most exposed to the China trade shock, with exposure to AI rising alongside educational attainment. The most AI-exposed group, under 1% of the workforce, is 3x more likely to hold an advanced degree than to have a high school education or less.

Adam Ozimek, Jason Harrison, and Nathan Goldschlag Agglomerations
Date Posted:

27% of the American workforce has a job where AI could impact at least 50% of their tasks; however, unlike the China Shock, jobs with high AI exposure employ people with higher educational attainment, suggesting these workers can adapt.

Are AI-exposed workers more educated than trade-shock-exposed workers?

Core argument: Workers in the most AI-exposed group, less than 1% of the workforce, are three times more likely to hold an advanced degree than to have a high school diploma or less.

The more concentrated the AI shock, the more educated those affected become. Workers in the most exposed AI shock group, representing less than 1% of the workforce, are three times more likely to have an advanced degree than to have a high school diploma or less. In short, regardless of how broad or narrow we define the AI shock, it will affect a group of workers who are substantially more educated than workers who were most exposed to the China shock. As AI exposure rises, so does educational attainment. One of the reasons for the disparity is simply that average education rates increase over time, with the China shock reflecting an early 1990s workforce. Between the early 1990s and early 2020s, the share of workers with a high school degree or less fell from about 48% to just over 30%. But even if we redo the analysis comparing shocked workers in the same period, the educational gaps persist.

Takeaways by Macro Roundup® AI

  1. Workers in the most AI-exposed group, less than 1% of the workforce, are three times more likely to hold an advanced degree than to have a high school diploma or less.
  2. Regardless of how broadly or narrowly the AI shock is defined, the affected workers are substantially more educated than those most exposed to the China shock, with educational attainment rising alongside AI exposure.
  3. The share of workers with a high school degree or less fell from about 48% in the early 1990s to just over 30% in the early 2020s, yet educational gaps persist when shocked workers are compared within the same period.

Related Articles:

  • AI Adoption Rises to 19.8% — US Census Bureau survey data show artificial intelligence adoption among US establishments rose 0.9 percentage points to 19.8%, with firms expecting 23.0% within six months, led by information, professional, education, and finance/insurance services. Equity analysts expect global semiconductor revenue to grow 50% from current levels by the end of 2026.
  • Looking for the Ladder — The article argues that the hiring downturn in occupations most exposed to generative AI reflects interest-rate sensitivity rather than AI itself, since roughly 38% of workers in the most AI-exposed quintile work in information, finance and insurance, and professional and technical services, versus under 2% in the least-exposed quintile.
  • AI and Young-adult Jobs: The Real Mystery — Employment rates have declined for young adults both with and without college degrees, with non-degree holders faring marginally worse, and employment growth for young workers of all education levels has lagged that of other workers. Artificial intelligence can replace some lower-skilled jobs, but those jobs are too few to drive youth labor market weakness.

AI Summary. Ukraine struck Moscow with nearly 200 drones in its largest-ever attack on the city, hitting the capital's largest oil refinery, with Moscow's mayor saying air defences downed at least 194 drones. The strike demonstrates Ukraine's growing capacity to hit deep behind Russian lines with largely homegrown long-range drones.

Max Seddon and Fabrice Deprez Financial Times
Date Posted:

Moscow’s mayor reported that at least 194 Ukrainian drones were shot down on the third consecutive day of attacks. The city’s largest oil refinery was damaged in the raid.

Is Ukraine expanding its ability to strike deep inside Russia?

Core argument: Ukraine struck Moscow with nearly 200 drones in its largest-ever attack on the city, hitting the capital's largest oil refinery and sending plumes of smoke over Moscow's south.

Ukraine hit Moscow with nearly 200 drones in its largest-ever attack on the city on Thursday, striking the Russian capital’s largest oil refinery and sending huge plumes of smoke billowing over the city’s south. Sergei Sobyanin, Moscow’s mayor, said anti-air defences had shot down at least 194 Ukrainian drones on Thursday morning in the third consecutive day of attacks. The apocalyptic images of flame and smoke engulfing the Russian capital were a remarkable demonstration of Ukraine’s increasing capacity to strike deep behind enemy lines with its largely homegrown long-range drones.

Takeaways by Macro Roundup® AI

  1. Ukraine struck Moscow with nearly 200 drones in its largest-ever attack on the city, hitting the capital's largest oil refinery and sending plumes of smoke over Moscow's south.
  2. Moscow mayor Sergei Sobyanin said anti-air defences shot down at least 194 Ukrainian drones on Thursday morning, the third consecutive day of attacks on the Russian capital.
  3. The attack demonstrated Ukraine's increasing capacity to strike deep behind enemy lines using its largely homegrown long-range drones.

Related Articles:

  • The U.S. Wants to Break China’s Drone Dominance. Here’s Where It Will Struggle — Fielding a drone fleet able to compete with China requires the U.S. to break China's monopoly on batteries and motors and to cut the cost of other components, where weak domestic demand is a key obstacle. Chinese producers hold 80% of the U.S. commercial drone market, and experts warn building mass-production infrastructure could take a decade or more.
  • Taiwan’s Bid To Export Drones Free Of Chinese Parts Is Taking Off — Taiwan is marketing drones built without Chinese parts to the US and allies concerned about Chinese espionage and supply-chain control, with production rising from about 10,000 units to more than 12x that level and exports climbing more than 35-fold to roughly 123,000 units. The Czech Republic and Poland were the largest buyers.
  • Ukraine Drone Strikes Hit Nuclear Bombers Deep Inside Russia — Ukraine used drones smuggled into Russia aboard trucks and released remotely from mobile wooden structures to strike strategic airfields as distant as eastern Siberia. An official in Ukraine's Security Service said more than 40 Russian aircraft, including Tu-95 and Tu-22 M3 long-range bombers and A-50 surveillance planes, were damaged, with losses assessed at at least $2bn.

Friday, June 19, 2026

AI Summary. A stock's value can be split into steady-state value from current operations and the "present value of growth opportunities" from future value-creating investments, which has averaged 35% of the S&P 500's price historically. Lower shares of price attributed to growth opportunities have been associated with higher subsequent returns, most clearly at the extremes.

Michael Mauboussin and Dan Callahan Morgan Stanley
Date Posted:
Is Database:
Database

Splitting the present value (PV) of stocks’ future cash flows into current earnings capitalized forever and the “PV of growth opportunities (PVGO),” the share driven by PVGO varies substantially over time and predicts 5-year returns with a negative sign.

Does the share of stock price from future growth predict subsequent returns?

Core argument: The present value of growth opportunities (PVGO), a term coined by financial economist Stewart Myers, has averaged 35% of the S&P 500's price from 1961 to 2025, with steady-state value accounting for the other 65%.

Think about the value of prospective cash flows in two parts. The first is the continuation of what a company is doing today - e.g. you might assume that a company earning $2 per share can sustain that level on a steady-state basis. The second part is the option to make investments in the future that create value. This part is called the “present value of growth opportunities” (PVGO), a term coined by Stewart Myers, a financial economist. When the steady state is most of the stock price, expectations about future value creation are low, [and vice versa] when the PVGO is a large % of the price. Exhibit 1 shows the annual PVGO percentage for the S&P 500 from 1961 to 2025. On average, the PVGO has been 35% of the price, and the steady-state value has been 65%. At the end of 2025, this measure was well above the average. Historically, lower PVGO percentages have been associated with higher subsequent 10-year returns. Exhibit 4 shows the five-year annualized TSRs, by quintile of PVGO percentage, for the stocks of U.S. public companies with market capitalizations of $1 billion or more in 2024 USD from 1990 to 2024. The five-year median TSR was 8.7% for the quintile with the lowest PVGO percentage and 5% for the quintile with the highest PVGO percentage. The second quintile had the highest median TSR, [which] underscores that this measure is more useful at the extremes.

Takeaways by Macro Roundup® AI

  1. The present value of growth opportunities (PVGO), a term coined by financial economist Stewart Myers, has averaged 35% of the S&P 500's price from 1961 to 2025, with steady-state value accounting for the other 65%.
  2. At the end of 2025, the S&P 500's PVGO percentage stood well above its 1961–2025 average of 35%, and historically lower PVGO percentages have been associated with higher subsequent 10-year returns.
  3. Among U.S. public companies with market capitalizations of $1 billion or more from 1990 to 2024, the lowest-PVGO quintile posted a five-year median annualized total shareholder return of 8.7%, versus 5% for the highest-PVGO quintile.

Related Articles:

  • Competitive Advantage Period: The Neglected Value Driver — Data indicate persistence in returns on invested capital has increased since 2000, with large companies the main beneficiaries; the information technology sector's aggregate return was 19% versus a 10.8% median from 1970 to 2024. Of about 13,800 U.S. public firms listing from 1976 to 2019, 18% survived.
  • One Hundred Years in the U.S. Stock Markets — Over a century, U.S. publicly traded stocks generated roughly $91tn in shareholder wealth enhancement, with returns strongly positively skewed and dominated by a relatively small number of high-performing firms. Because most possible outcomes fall below the mean in a skewed distribution, the authors argue financial planning should focus on median outcomes or the full distribution.
  • Bayes and Base Rates 2.0: How History Can Guide Our Assessment of the Future — Applying historical base rates to OpenAI's published sales forecasts, the authors find that no U.S. public company in roughly 18,900 firm-period observations from 1950 to 2024 achieved five-year sales growth as fast as the company projects. Reported forecasts imply compound annual growth rates ranging from 85% to 118%.

AI Summary. All of the S&P 500's gains over the year to date have come from the energy and artificial intelligence sectors, with the rest of the index trading below where it started.

Torsten Sløk Apollo
Date Posted:
Is Database:
Database

Since the start of the year, all of the S&P 500’s gains have come from the energy and AI sectors. Sløk notes “everything else is actually trading at less than where it started.”

Are all of the S&P 500's gains coming from AI and energy?

Core argument: All of the S&P 500's gains since the start of the year have come from the energy and AI sectors, according to Sløk.

Since January, the entire S&P 500's gains have come from just two corners of the market, AI and energy, while everything else is actually trading at less than where it started.

Takeaways by Macro Roundup® AI

  1. All of the S&P 500's gains since the start of the year have come from the energy and AI sectors, according to Sløk.
  2. Sløk notes that outside of AI and energy, the rest of the S&P 500 is trading below where it started the year.

Related Articles:

  • SpaceX and OpenAI Are Ending Wall Street’s Era of Stock Scarcity — JPMorgan projects that share sales will add roughly $1.5tn of stock to the US equity market over the next two years even after buybacks, which would be the strongest net equity issuance since at least the late 1990s. Equity has grown cheaper relative to debt as a funding source.
  • Chart of the Day: U.S. Households at Record Equity Allocation Heading into AI IPOs — U.S. households hold a record share of their assets in equities, exceeding the dot-com and Nifty Fifty eras, while price-earnings multiples sit near all-time highs and fewer than 10 stocks account for almost 40% of the S&P 500's market value. The author argues equity ownership has become structural rather than discretionary, making markets simultaneously more stable and more fragile.
  • One Hundred Years in the U.S. Stock Markets — Over a century, U.S. publicly traded stocks generated roughly $91tn in shareholder wealth enhancement, with returns strongly positively skewed and dominated by a relatively small number of high-performing firms. Because most possible outcomes fall below the mean in a skewed distribution, the authors argue financial planning should focus on median outcomes or the full distribution.

AI Summary. Trade responds to exchange-rate changes with a lag of roughly 8 to 12 quarters, and after the dollar fell from its mid-1980s peak the US trade deficit dropped from about 3% to about 1% of GDP while Japan's surplus fell from 4% to 2%. The author argues currency appreciation, not fiscal consolidation, drove that rebalancing.

Brad Setser and Shahin Vallée Council On Foreign Relations
Date Posted:

The dollar strength in the post-pandemic period is above the level associated with the tech bubble. The broad real dollar fell ~20% btw 2001 and 2005. Setser argues for Asian currency appreciation vis-a-vis the dollar to facilitate trade rebalancing.

Can currency moves, rather than fiscal consolidation, shrink trade imbalances?

Core argument: The U.S. overall trade deficit fell from around 3% of GDP to around 1% of GDP between 1987 and 1990, following the Plaza agreement and the dollar's move off its 1985 highs.

Trade adjusts to changes in exchange rates with a lag (usually thought to be 8 quarters but some work suggests that it might now be more like 12 quarters. The Plaza agreement didn’t bring the U.S. deficit down immediately, but by 1987 the real U.S. trade deficit was clearly shrinking. The overall trade deficit fell from around 3% of U.S. GDP to around 1% of U.S. GDP) between 1987 and 1990. This fall occurred even with strong demand growth in the US in 1988 and 1989, so it wasn’t just a function of underlying shifts in the global pattern of demand growth. Net exports contributed positively to U.S. growth once the dollar had clearly moved off its 1985 highs across the cycle. Japan’s surplus also fell from 4% of GDP to 2% of GDP—with a large reduction in its bilateral surplus with the U.S. This suggests that currency appreciation, not fiscal consolidation, was the primary driver of rebalancing in the 1980s.

Takeaways by Macro Roundup® AI

  1. The U.S. overall trade deficit fell from around 3% of GDP to around 1% of GDP between 1987 and 1990, following the Plaza agreement and the dollar's move off its 1985 highs.
  2. Japan's surplus fell from 4% of GDP to 2% of GDP, with a large reduction in its bilateral surplus with the U.S., suggesting currency appreciation rather than fiscal consolidation was the primary driver of 1980s rebalancing.
  3. Trade adjusts to exchange rate changes with a lag usually thought to be 8 quarters, though some work suggests it may now be closer to 12 quarters, and the U.S. deficit narrowed even amid strong U.S. demand growth in 1988 and 1989.

Related Articles:

  • The Real Problem With Global Trade — Asia's $1.5tn trade surplus is larger as a share of world output than at any point since 1945 and is the only large surplus in the global economy. Exchange rates have a meaningful impact on trade balances: China's surplus reached about 10% of its output amid renminbi depreciation, then fell below 2% after a 40% real appreciation.
  • The Dollar has Further to Fall — The author argues the dollar has considerably further to fall, noting Federal Reserve data show its real value nearly two standard deviations above its average since 1973, a level matched only twice before, each followed by depreciations of 25-30%. Financing the $1.1tn US current account deficit requires matching net capital inflows.
  • Understanding Global Imbalances — The US, China, Germany, and Japan account for roughly two-thirds of global current account imbalances, with the US deficit at 4% of GDP financed by capital inflows into dollar assets. The average duration of a surplus or deficit spell roughly doubled since the 1980s, building large net foreign asset and liability positions.

AI Summary. US officials have told Dutch chipmaking-equipment maker ASML they are concerned one of its most advanced extreme ultraviolet lithography machines may have reached China in violation of US-led export restrictions. ASML disputes this, saying all 314 operating and 26 decommissioned machines are accounted for and that the systems cannot be relocated or run without its involvement.

Mackenzie Hawkins and Jenny Leonard Bloomberg
Date Posted:

The Commerce Department has notified ASML that one of its extreme ultraviolet lithography (EUV) machines “may” be in China. The firm pushed back at the suggestion, noting the machines require constant upkeep from ASML employees.

Has an advanced chipmaking machine reached China despite export controls?

Core argument: ASML says 314 of its EUV lithography machines are in operation worldwide and 26 have been decommissioned, with none in China, rejecting Howard Lutnick's suggestion that one reached the country.

In a series of recent meetings, Howard Lutnick outlined concerns to ASML’s senior leaders that one of its top-of-the-line machines may have made its way into China, in violation of US-led export restrictions. ASML has pushed back on Lutnick’s suggestion, explaining that none of these tools — which are the size of a school bus, are manufactured in limited quantities, and require constant upkeep from ASML employees — are in China. There are 314 EUV machines in operation around the world, 26 that have been decommissioned — and none in China, according to [ASML]. ASML can automatically detect “any interruption, abnormal behavior, or loss of connectivity,” in its EUV portfolio, and that customers “cannot remove, transport and relocate EUV systems without ASML involvement due to specialized handling procedures.”

Takeaways by Macro Roundup® AI

  1. ASML says 314 of its EUV lithography machines are in operation worldwide and 26 have been decommissioned, with none in China, rejecting Howard Lutnick's suggestion that one reached the country.
  2. Howard Lutnick told ASML's senior leaders in a series of meetings that one of the company's top-of-the-line machines may have reached China in violation of US-led export restrictions.
  3. ASML says it can automatically detect any interruption, abnormal behavior, or loss of connectivity across its EUV portfolio, and that customers cannot remove, transport, or relocate EUV systems without ASML involvement.

Related Articles:

  • ASML’s China Chip Business Faces New Curbs From Netherlands — The Netherlands plans to limit ASML's ability to service and supply spare parts for its semiconductor-making equipment in China, with licenses covering its top-end deep ultraviolet lithography machines expected not to be renewed. Because the machines are sold with essential maintenance agreements, withdrawing support could render some of them inoperable.
  • The Goal for China’s Chip Giant: Cut Out the U.S. — Huawei's Mate 60 smartphone contained a system-on-chip made with SMIC technology comparable to the 7-nanometer process, despite Chinese chipmakers lacking access to ASML's most advanced lithography machines. Semiconductor engineers say the chips were likely made by exposing silicon to light multiple times, a technique that worsens yields and raises costs and becomes harder at more advanced nodes.
  • How to Fight an Economic War — China earned about $3.4bn from exporting rare-earth elements and magnets in a year, while the U.S. Geological Survey estimates a 30% disruption to U.S. supply of the rare-earth element neodymium alone would cut U.S. GDP by 2.2%, over $600bn. This asymmetry gives Chinese export controls their leverage.

AI Summary. The U.S. Air Force has agreed to deals with Anduril and General Atomics for autonomous drone jet fighters designed to help manned warplanes strike targets deep in enemy territory. The larger General Atomics FQ-42 carries missiles internally, while Anduril's FQ-44 carries munitions externally on its wings; costs are classified.

Marcus Weisgerber Wall Street Journal
Date Posted:

Anduril and General Atomics have been awarded contracts by the Air Force for two collaborative combat aircraft (CCA) or long-range autonomous drones designed to work alongside manned aircraft in highly contested environments.

Is the Air Force buying autonomous drones to support manned fighters?

Core argument: The U.S. Air Force's latest budget request includes more than $1 billion in fiscal 2027 and in excess of $9.5 billion over the next five years for these autonomous drone jet fighters.

The U.S. Air Force has agreed to deals with two companies for a new fleet of autonomous drone jet fighters designed to help manned warplanes strike targets deep in enemy territory. The Air Force had been evaluating the Anduril and General Atomics drones since 2024. The General Atomics drone, called the FQ-42, is larger than Anduril’s drone, called FQ-44. One of the differences between the two is that the FQ-42 carries missiles in an internal weapons bay while the FQ-44 carries munitions externally on its wings. Officials didn’t disclose the financial terms of the deal or how many aircraft were being bought. An Air Force spokeswoman said the cost was classified. The service’s latest budget request includes more than $1 billion for these specific drones in fiscal 2027, and in excess of $9.5 billion over the next five years.

Takeaways by Macro Roundup® AI

  1. The U.S. Air Force's latest budget request includes more than $1 billion in fiscal 2027 and in excess of $9.5 billion over the next five years for these autonomous drone jet fighters.
  2. The Air Force agreed to deals with Anduril and General Atomics for autonomous drone fighters designed to help manned warplanes strike targets deep in enemy territory, after evaluating both companies' aircraft since 2024.
  3. General Atomics' FQ-42 is larger than Anduril's FQ-44 and carries missiles in an internal weapons bay, while the FQ-44 carries munitions externally on its wings.

Related Articles:

  • Ukraine Hits Moscow With Largest-Ever Drone Attack — Ukraine struck Moscow with nearly 200 drones in its largest-ever attack on the city, hitting the capital's largest oil refinery, with Moscow's mayor saying air defences downed at least 194 drones. The strike demonstrates Ukraine's growing capacity to hit deep behind Russian lines with largely homegrown long-range drones.
  • The U.S. Wants to Break China’s Drone Dominance. Here’s Where It Will Struggle — Fielding a drone fleet able to compete with China requires the U.S. to break China's monopoly on batteries and motors and to cut the cost of other components, where weak domestic demand is a key obstacle. Chinese producers hold 80% of the U.S. commercial drone market, and experts warn building mass-production infrastructure could take a decade or more.
  • Ukraine Drone Strikes Hit Nuclear Bombers Deep Inside Russia — Ukraine used drones smuggled into Russia aboard trucks and released remotely from mobile wooden structures to strike strategic airfields as distant as eastern Siberia. An official in Ukraine's Security Service said more than 40 Russian aircraft, including Tu-95 and Tu-22 M3 long-range bombers and A-50 surveillance planes, were damaged, with losses assessed at at least $2bn.