At the Economic Club of Chicago on May 22, 2025, Palantir Technologies co-founder and CEO Alex Karp held a wide-ranging conversation with moderator Sean Connolly, the president and CEO of Conagra Brands, moving between autobiography, corporate culture, the operational use of artificial intelligence, and what Karp framed as the strategic requirements of American power in a renewed era of major-power competition.
Connolly opened by presenting Karp as an unconventional leader within the U.S. technology sector: a chief executive whose formal training is rooted in philosophy, law, and social theory rather than engineering, yet whose company has become strongly associated with defense analytics and the applied integration of large-scale data in government and industry. In biographical terms, the introduction emphasized Karp’s interdisciplinary educational path—Haverford College for undergraduate philosophy, Stanford Law School, and a doctorate completed in Frankfurt—paired with early professional experience spanning research work in Germany and subsequent activity in finance, before the Palantir founding period. Connolly also placed Palantir’s trajectory within the arc of the firm’s public-market rise following its 2020 direct listing, using the company’s share-price appreciation as a proxy for both commercial validation and Silicon Valley’s shifting attitude toward defense-adjacent technology.
Karp’s own remarks quickly anchored on management style and organizational design. He described Palantir as a “high-volatility” business whose internal rhythm is shaped by constant challenge from younger staff, conveying a deliberate culture of direct criticism and rapid iteration. He attributed much of this to a flat structure with relatively few direct reports and an institutional preference for concentrated responsibility over layered titles. In his telling, this arrangement supports blunt internal feedback, accelerates problem-solving, and aligns with a broader commitment to meritocratic evaluation: people are expected to demonstrate capability continuously, with credentials and pedigree treated as weak predictors of performance over time.
From there, Karp framed Palantir’s identity as inseparable from controversy, particularly in the company’s long-standing willingness to build for U.S. defense, intelligence, and counterterrorism missions when such work was widely stigmatized in parts of the technology industry. He argued that Palantir was founded around the premise that liberal-democratic societies require a practical synthesis of security and legal restraint: counterterrorism tools should enable the identification of threats while preserving civil liberties through auditable, controlled access to sensitive data. Within this account, Palantir’s early “core product” aimed at reconciling fragmented databases so analysts could detect operational patterns without dissolving constitutional constraints into an unchecked surveillance practice.
Karp then connected Palantir’s defense posture to what he presented as a broader civilizational commitment. He spoke explicitly in terms of Western institutional superiority—invoking meritocracy, market coordination, constitutional rights, and legal oversight as elements of a coherent political form worth protecting. He also portrayed the past decade as a period in which that stance shifted from reputational liability to strategic advantage, partly because geopolitical shocks and battlefield realities increased demand for software that can fuse intelligence, guide operations, and reduce decision latency under pressure.
On capabilities, Karp described Palantir’s work in two domains that share a common technical logic: government operations and enterprise applications. He emphasized that the firm’s primary defense contribution, as he framed it, consists in enabling “dominance on the battlefield” through faster targeting cycles, improved intelligence fusion, and operational decision support; he asserted that the company’s platforms have helped disrupt terrorist plots and support allied operations. In the commercial sphere, he portrayed Palantir’s growth thesis as “operational AI”: systems that measurably raise revenue, lower costs, and shift organizations from fragmented decision-making toward integrated, model-assisted execution. Central to this is what he called an “ontology,” described as a structured layer that organizes enterprise data and operational objects so that machine learning and large language models can be deployed safely and usefully inside real workflows, rather than remaining conversational demonstrations that fail to generate durable business value.
Karp’s description of customer engagement emphasized a distinctive commercial stance: Palantir, he claimed, absorbs a meaningful portion of the risk of value creation by binding its work to performance outcomes and operational adoption, rather than merely delivering tooling and transferring execution risk back to the customer. He illustrated the company’s typical enterprise use cases in terms of volatility management—supply chains under disruption, real-estate acquisition at scale, underwriting, construction planning, and cost transparency across complex input networks—arguing that these are the environments in which model-driven decision systems can most visibly convert uncertainty into measurable advantage.
A significant portion of the discussion centered on defense procurement and institutional inertia. Karp recounted how Palantir’s initial traction came through special operations communities whose procurement culture, he said, is pragmatically outcome-oriented: if a product works in theater, it is adopted with comparatively little concern for the vendor’s aesthetics or conformity. He contrasted that with the broader Department of Defense acquisition environment, which he portrayed as structurally inclined toward lengthy documentation, slow cycles, and entrenched vendors—conditions he argued are ill-suited to software, where capability is demonstrated in iterative deployment rather than in static specifications.
Within that narrative, Karp described a period in which Palantir pursued litigation against the U.S. government to challenge procurement outcomes, despite strong informal pressure that suing would lead to exclusion from future work. He presented those legal confrontations as a forcing mechanism intended to make “merit” operational within acquisition: to create conditions where demonstrated effectiveness compels adoption. In his telling, the downstream impact was broader than Palantir’s own contracts, because it contributed to an ecosystem in which newer defense-technology firms could compete on performance rather than on procedural endurance. He also suggested that, over time, defense budgets will reallocate toward software-centric and AI-enabled capabilities, while acknowledging the continuing importance of legacy primes for scale-intensive platforms.
On internal culture, Karp described Palantir’s founding group—Peter Thiel, Joe Lonsdale, Stephen Cohen, Nathan Gettings, and himself—as unusually intellectual and highly argumentative, and he implied that this early environment hardened into an institutional style: deep conceptual rigor combined with constant adversarial testing of assumptions. He highlighted the “Five Whys” method—iteratively pushing beyond first explanations to identify root causes—as an internal discipline used to expose dysfunction, self-deception, and superficial fixes. Recruitment, in his account, follows an aggressively networked logic: hiring a small number of exceptional people, then systematically pulling in the strongest peers from their personal networks, with the expectation that excellence compounds socially as well as technically. He further characterized Palantir as “anti-experience” in the sense that lateral hires from conventional corporate backgrounds often struggled to adapt to the company’s norms, though he noted that recent high-profile additions in government-facing roles appeared to be integrating more effectively.
The conversation then turned to education, where Karp offered a position that combined respect for elite institutions with sharp frustration at their recent performance. He presented himself as broadly progressive while arguing that leading universities have become intellectually captured, with negative consequences for free inquiry, administrative competence, and the production of capable graduates. In response, he described Palantir initiatives designed to attract high-aptitude candidates directly from high school, treating the firm itself as a site of apprenticeship and practical formation. He argued that the emerging economy, shaped by AI, requires new forms of testing and selection because classical signals—grades, admissions pedigrees, conventional standardized metrics—do not reliably identify the combination of creativity, judgment, and operational intelligence needed for complex institutional work. He extended this into a larger claim: societies will need revised systems for “slotting” talent quickly into roles where it can compound, supported by vocational training and AI literacy, with institutional flexibility treated as a competitive advantage.
Karp’s AI analysis was presented less as a productivity story than as a geopolitical one. He argued that American history contains a recurring pattern in which battlefield-driven technologies later diffuse into civilian life, generating both economic growth and a form of social cohesion. In his view, the consumer-internet era disrupted that pattern by channeling engineering talent into primarily commercial, often trivial applications; AI, he contended, is pulling the system back toward strategic competition, with state capacity and industrial mobilization returning as decisive factors. He characterized the global environment as an arms race for operational AI adoption, with U.S. adversaries and allies pursuing comparable capabilities at speed, and he implied that senior decision-makers already treat this as a defining contest for the international order.
Alongside strategic urgency, Karp emphasized distributional and political risk. He argued that AI is likely to raise aggregate output while also amplifying inequality, because advanced systems disproportionately benefit those already positioned to capture productivity gains. He stressed the political salience of relative deprivation: even in a growing economy, social stability can degrade if gains are asymmetrically concentrated. He also suggested that different political forms will face different adaptation constraints: centralized systems can redirect labor and capital more rapidly, while democracies must manage slower transitions, job displacement, and the political economy of programs designed partly to sustain employment. Europe, in his view, faces particular friction where defense spending is intertwined with local jobs and regional patronage, making the case for software substitution more difficult even when effectiveness gains are clear.
In addressing criticism, Karp portrayed controversy as both inevitable and, in some contexts, strategically clarifying. He said he listens closely to objections and practices systematic “steel-manning,” attempting to reconstruct stronger versions of critics’ arguments before deciding what to accept or reject. Yet he also argued that business operations provide a hard test of reality: outcomes, adoption, and measurable capability function as a form of “productized truth,” whereas parts of academia, in his depiction, reward status conflict and rhetorical performance over impact. This was presented as a diagnosis of institutional decay: when major institutions fail to deliver competence, legitimacy migrates toward systems that still produce enforceable results.
The closing segment returned to deterrence and grand strategy. Karp argued that deterrence rises and falls with the perceived gap between U.S. technological capability and that of competitors. He invoked the mid-20th-century period—organized scientific mobilization, decisive military superiority, and subsequent economic dominance—as an illustration of how credibility can support both security and an attractive cultural model abroad. He suggested that America’s values exert influence when they are backed by the credible capacity to enforce order and deter aggression, and that erosion of that credibility encourages adversaries to test limits. In that frame, he presented AI-enabled, software-defined systems as central to restoring and sustaining a durable technological advantage.
Asked for advice to young people, Karp emphasized aptitude identification and life-structuring: finding what one is uniquely good at, organizing effort around that capability, and accepting the trade-offs required for exceptional performance. He warned against confusing status signals with substantive compatibility in personal choices, and he advised minimizing behaviors that predictably derail long-run capacity. The overall message, consistent with his broader argument, treated success as the compounding outcome of focused skill, institutional flexibility, and the disciplined alignment of individual life choices with the realities of a competitive, fast-shifting technological era.
Karp’s remarks, taken as a whole, presented Palantir as both a technology company and a political actor in a broad sense: a firm that sees operational AI as an instrument of institutional power, regards procurement reform and talent formation as strategic levers, and treats U.S. military and economic primacy as the stabilizing condition under which liberal order and rule-governed life remain credible. In that conception, debates about platforms, models, and enterprise transformation are inseparable from questions of state capacity, social cohesion, and the ability of democratic societies to adapt quickly enough to remain strategically decisive.
Simon Gros 
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