Midterm Blood Bath, $4T AI Sell Off, Data Center Freeze, What's Next for Trump

The recent U.S. midterm elections resulted in a sweeping victory for Democrats, who claimed both chambers of Congress and at least 29 governor races. Democrats are projected to hold 54 to 56 Senate seats and at least 250, potentially 260, House seats, toppling Republicans not only in battlegrounds but also deeply red states like Texas, Kansas, Iowa, and South Carolina, which Trump had previously won by double digits. Analysis by election forecasters and podcast hosts attributes this dramatic shift to a convergence of war, inflation, affordability crises, coalition fractures among Republicans, and voter resentment towards perceived economic injustice.

War, Inflation Drive Republican Losses

A central factor in the Republican defeat is the economic fallout from the Iran war, which began in late February 2026. Gas and diesel prices surged from roughly $3 to over $4 per gallon, increasing transportation costs and filtering through the entire economy—from food to manufactured goods to fertilizers. The result was markedly higher monthly household expenses, with average families spending $200 more on gas alone and grappling with substantially more expensive groceries.

This spike in fuel prices led to inflation rising from 2.4% at the start of the year to 3.7%. Although the first year of the Trump administration saw a 3.1% increase in real household income—reversing negative trends from the Biden era—these income gains were erased as inflation outpaced wage growth, cutting into real purchasing power for most Americans. At the same time, the Federal Reserve failed to cut interest rates; instead, it hiked them, pushing mortgage rates to approximately 7.5% and making homeownership much less affordable.

Before the onset of war, prediction markets and polling data pointed to a strong Republican advantage in holding the Senate and a toss-up in the House. Poly Market and major pollsters accurately anticipated the probabilities, with a 70% projected Republican Senate win as late as January. However, the war and its economic impact abruptly reversed these dynamics by March, leading to deep GOP losses across nearly every demographic, including the traditional base of white men.

Affordability as Central Voter Concern Transcending Ideology

Affordability emerged as the single most decisive issue. Chamath Palihapitiya emphasizes that voters, centrists and otherwise, swung away from all ideology and focused on their economic reality—specifically, the cost crisis besetting wage earners. Polls showed that 74% of the electorate regarded the Iran war as a crucial or major factor in their vote, and these voters backed Democrats by wide margins, regardless of party ID or previous support for Biden or Trump.

Voter anxiety centered less on abstract economic indicators and more on perceived purchasing power and daily expenses—how far wages stretched given price increases in essentials like gas, housing, and food. As such, traditional levers of political advantage such as campaign spending and partisan gerrymandering proved largely irrelevant: huge sums funneled into right-leaning states and redistricted Republican districts failed to protect GOP incumbents, as voters consistently favored candidates they believed could deliver economic fairness and restore affordability, regardless of party.

A large and decisive centrist voting bloc, frustrated by years of economic dysfunction and seeing little distinction between the two parties’ handling of affordability or fairness, swung from Biden to Trump to the Democrats over consecutive election cycles. With asset owners benefiting in all macroeconomic environments and wage earners feeling increasingly abandoned, voters demanded policies that support labor and reverse the feeling that the economy is “broken.” The result was a wholesale repudiation of the status quo.

Loss of Key Republican Supporters Through Fracturing Coalition

A major tactical failure for Republicans was the loss of young male voters, the so-called “podcast bros,” who pivoted by 36 points against the party relative to 2024. This young male, podcast- and alternative-media-savvy bloc forms the backbone of political opinion among new voters, and they registered strong opposition to the Iran war and its costs.

Key alternative media figures such as Tucker Carlson, Joe Rogan, Theo Vaughn, Tim Allen, and Megyn Kelly distanced themselves from Trump and the GOP over foreign policy, economic grievances, and broader dissatisfaction, further damaging Republican electoral prospects. This cohort’s withdrawal from the Republican coalition fractured the party, robbing it of its primary means of message amplification outside of hostile mainstream or leg ...

A series of practical strategies could set the stage for President Trump’s political recovery and legacy, chiefly by ending the war in Iran, adopting bold economic reforms, pursuing bipartisan consensus, and drawing lessons from history’s midterm recoveries.

Ending the Iran War for Economic Recovery

David Sacks and Jason Calacanis argue that ending the war in Iran should be President Trump’s highest priority. Sacks observes that a swift conclusion could rapidly lower Brent crude oil prices from current highs near $110–117 down toward $70 per barrel, referencing historical post-election market moves. Lower energy prices would bring down the cost of gas, diesel, and food—core drivers of inflation—giving the Federal Reserve latitude to cut interest rates, which would, in turn, reduce mortgage costs.

The hosts note that, currently, strong economic metrics—robust GDP growth and positive job reports—are being overshadowed by high energy prices and inflation. If the conflict ends and energy prices normalize, public attention would return to the positive fundamentals, bolstering Trump’s approval ratings, possibly into the 40% range.

Conversely, Sacks warns that the war’s continuation risks eroding GOP popularity, drawing a parallel to how Republican fortunes dwindled after Bush’s “surge” strategy following the 2006 midterms and ultimately led to losses in 2008. Thus, decisive action on Iran is both an economic and political imperative.

Proposed Economic Reforms to Address Wage Concerns

Chamath Palihapitiya and Jason Calacanis propose sweeping economic reforms to address wage stagnation and cost of living concerns. A central proposal is the elimination of federal income taxes for incomes below $125,000–$150,000, which would significantly increase disposable income for the wage-earning class and foster a greater sense of ownership in the economy with minimal revenue loss, provided loopholes are properly closed.

Calacanis advocates for legislating a phased minimum wage increase to $15/hour over four years, affecting 5–10 million workers. He argues this would demonstrate support for economic mobility and counter narratives that Republicans ignore the bottom half of society.

A new capital gains tax bracket is also suggested: Gains over $10 million would be taxed at 50%, with credits for loans repaid or shares held, aiming for a fairer wealth contribution and generating additional revenue while answering criticisms of tax avoidance by the wealthy.

Rounding out the reforms, Calacanis calls for a plan to confront housing affordability—considered the top voter concern—by incentivizing the construction of new homes and addressing housing costs through targeted policy measures.

Strategic Moves to Isolate Opposition and Build Consensus

With ongoing legal disputes threatening to distract from policy achievements, Calacanis argues President Trump should issue blanket pardons for himself, his family, and all officials and allies immediately. This would neutralize investigations as a tool for political opposition, clearing the stage for policy debate.

Calacanis and Palihapitiya recommend reaching out to Democrats to trade Republican priorities for Democratic ones through bipartisan legislation—for example, pairing border security, ...

Election Results: Political Barriers to Data Center Expansion

The 2024 Texas gubernatorial election resulted in an unexpected victory for Gina Hinojosa over three-term incumbent Greg Abbott. Hinojosa quickly outlined her stance: while she does not oppose data center development in principle, she imposed a moratorium on new data center permits, stating no new approvals will be granted until Texas implements stronger regulatory controls. She assures that current projects may proceed through 2028, but the status of projects under construction or lacking final permits remains uncertain. Many existing projects still require additional approvals, such as air pollution permits. If the moratorium is strictly enforced before all necessary permits are granted, numerous data centers could be left stranded and unfinished.

This regulatory shift did not occur in a vacuum. Across the U.S., the 2024 elections saw both Democratic and Republican candidates run attack ads against politicians who approved data center projects, particularly targeting claims that data center expansion favors tech oligarchs and raises utility bills through increased electricity and water use. The attack ads have removed all meaningful political incentive for ambitious officials or civil servants to approve new permits, creating a climate where regulatory risk deters new investment and hinders ongoing construction.

Impact of Data Center Development Restrictions in US

The policy shift in Texas and similar signals elsewhere have already begun to slow data center construction in the U.S. As regulatory constraints deepen, compute and AI model training are migrating to international locations, notably Canada, Mexico, Malaysia, Singapore, and, if regional conflict subsides, the Middle East. This outward shift means large AI model projects will increasingly be run on foreign soil instead of within the U.S.

Economically, the U.S. transitions from being a net exporter to a net importer of AI tokens. High-paying jobs, often in the $300,000–$400,000 range, that are tied to building and operating data centers, are now lost to countries attracting this expansion. Tax revenue that would benefit state and local U.S. governments is instead collected by places like Malaysia, where Google and other tech giants are establishing massive data centers.

Global data distribution erodes the U.S. government’s leverage—data can easily and rapidly traverse international networks, negating the competitive advantage of domestic infrastructure. As domestic capacity tightens and permitting remains uncertain, the cost of compute and AI processing increases. Chamath Palihapitiya predicts the dollar cost per megawatt per month and the price per GPU hour will rise sharply, reducing the competitiveness of American companies in AI development and raising prices for U.S. consumers and enterprises.

Strategic Position of Hyperscalers in a Constrained Environment

These developments shift the balance of power toward hyperscalers—technology giants with existing global data center infrastructure, including Amazon, Meta, Microsoft, Google, SpaceX, and Apple. These companies maintain an edge because they do not depend on renting compute capacity and can absorb price increases or capacity shortages. With fewer new data centers coming online, hyperscalers can restrict compute access to competitors or use all incremental capacity internally, favoring the advancement of their AI models (e.g., Google prioritizing Gemini). As a result, companies building next-generation foundation models that rely on external compute (or “neoclouds”) face exposure to price volatility and capacity shortages, risking stalled development, decreased product performance, and lagging behind the frontier models of hyperscalers.

The game theory in this constrained environment is complex. Hyperscalers can decide how much capacity to rent out versus reserve for their own use, influencing which models advance in quality. In high-demand periods, the cost of access soars, further benefitting those with ownership of the infrastructure and putting renters a ...

The rapid progression of artificial intelligence is forcing urgent questions about government regulation, concentration of power, and the balance between innovation and state control. Commentators including David Sacks, David Friedberg, Jason Calacanis, and Chamath Palihapitiya outline likely developments and looming philosophical and structural dilemmas in the next phase of American AI policy.

Federal Government's Likely Regulatory Approach To Ai Development

David Sacks predicts that Democrats are certain to push for major AI legislation in Congress. Central to this vision would be a new federal AI department that must review and approve all "frontier" AI models before public release, effectively giving government regulators veto power over AI development. This overseeing body would be empowered to demand changes to any model and prevent release until concerns are addressed.

Sacks draws comparisons to the federal government’s actions during the COVID-19 pandemic, where social media platforms were pressured to censor what authorities deemed misinformation, disinformation, and dissident thought. He expects a similar regulatory framework for AI, where such categories would be banned from models, effectively nationalizing censorship prerogatives. Friedberg adds that the government is likely to focus regulation on compute resources—controlling the infrastructure for AI, such as data access and processing power, rather than just algorithms or software deployment. This approach allows the state to directly manage who can access or build advanced AI, reinforcing central governmental authority. Jason Calacanis points out this could lead to a situation where the best versions of AI are available only to the government, while corporations and individuals get downgraded versions, creating a quasi-nationalized system and a considerable power imbalance.

Philosophical Stakes of Ai Regulation Regarding Liberty

A major concern raised is that heavy government control of AI fundamentally contradicts America’s founding principle of checks and balances. Friedberg frames the modern challenge as analogous to the Second Amendment: where once the question was "who has the bullets and guns," now it’s "who has the technology." If the state is the sole possessor of the most powerful AI, citizens lose their practical check on government power. He emphasizes that the United States was built on the idea of individual liberty, and the concentration of AI power in the hands of a central authority flies in the face of that legacy.

Moreover, since AI models are essentially software—code that can be run on any computer—regulating AI at the model level becomes a First Amendment issue about free speech. Friedberg notes existing laws already address harmful uses of code, from theft to illegal weapons. The case for new AI-specific regulation, he argues, is more about expanding state control than addressing genuinely new threats.

Alternative Scenarios For Ai Development and Regulatory Capture

Sacks predicts the most probable outcome will be regulatory capture. Here, the government gains more direct power over AI, while dominant closed-model companies like OpenAI and Anthropic obtain government protection, building regulatory moats around their businesses and gaining a controlled duopoly. Palihapitiya expects that restrictions on data centers and AI "factories" will end up benefiting hyperscalers—tech giants like Google ...