The AI Macro Strategy of 2026
From the outside, many modern systems appear coercive (maybe they are, maybe they’re not), perhaps they are quieter than their historical predecessors. For example, nations “support” U.S. debt markets, citizens “comply” with expanding regulatory regimes, users “choose” dominant platforms, and firms “opt into” standards they did not design. It is tempting to describe control evolving into something softer, but fundamentally unchanged. Yet that framing misses a critical distinction: externally similar outcomes can arise from radically different internal experiences. When faced with a genuine choice, participation can feel either like authorship or submission, and that difference determines whether a system stabilizes or slowly erodes its legitimacy.
U.S. Treasuries provide a tangible and instructive example. Treasury yields fall only when demand rises, which at scale means that sovereigns, institutions, and global capital pools are choosing to hold long-duration U.S. debt. Historically, this demand intensifies during periods of geopolitical instability, global uncertainty, or asymmetric risk, producing the familiar shorthand: instability drives capital into Treasuries. This dynamic is often misinterpreted as coercion…as if countries are somehow forced to fund U.S. deficits, or that secret bargains underpin bond auctions. In reality, Treasuries persist not because of overt pressure, but because they occupy a uniquely legible category in the global financial ontology: large-scale, liquid, legally predictable stores of value. They are chosen, not because they are ideal, but because alternatives collapse faster under stress, or faster than stability can be reinforced.
Postwar Japan illustrates this distinction with clarity. Japan did not purchase U.S. Treasuries as reparations, nor was it compelled by treaty to do so. Instead, it voluntarily aligned itself with a U.S.-led postwar order that offered security guarantees, reconstruction, market access, and economic legitimacy. Inside that alignment, Japan pursued export-led growth, accumulated persistent dollar surpluses, and faced a structural necessity: those dollars had to be parked somewhere capable of absorbing scale without destabilizing domestic conditions. Treasuries were not chosen out of obedience or loyalty, but because within the system Japan had chosen, they were the least-bad and most stabilizing option. The behavior looks identical to coercion from the outside; the internal experience (choice within constraint) is what made it durable.
This leads to the general principle Treasuries reveal: the most enduring systems do not force behavior directly, they design environments in which the behavior and the context emerge as rational and internal choice. Instead of issuing commands, good architects shape incentives, reduce constraints, and load-balance the tradeoffs so that participants voluntarily converge on outcomes that stabilize the system. This form of power does not require constant enforcement because it preserves agency, authorship, and legitimacy. Participants can recognize themselves as choosing actors, even when their options are not unlimited. That recognition (not the total/complete absence of constraint) is what allows systems to persist for multiple generations without interuption.
We focus too much energy on “intended behavior” or “outcome compliance” for a solution’s legitimacy. This is soft control, and it appears to preserve choice, but it also… quietly collapse structural alternatives, narrows strategy space, and reframes inevitability as optimization… People are told they are free, but only a small number of paths remain viable. While hard control is far worse, because it provokes pain; soft control produces disengagement. People hold a quiet resentment, and there is eventual decay. Civilizations do not fail when people disobey… they fail when people comply without authorship, when participation continues, but belief does not… and this is a future that America seems to be approaching.
This is not an argument for infinite pluralism or unstructured freedom. Healthy systems do not maximize choice indiscriminately; they provide a sufficient number of viable strategies (like treasuries vs other vehicles) to match the number of real contexts that exist. In the landscape of people… Age, health, geography, risk tolerance, time horizon, and capacity are not ideological constructs… they are required ontological facts. Too few strategies aimed at improving livelihood, flatten reality and produce coercion; too many unstructured strategies aimed at producing freedom, generate social chaos. The stable middle ground is context-matched plurality, which we must do a better job of designing.
Context-matched plurality requires multiple perspectives, options, or truths in matched forms that fit specific situations, scales, or domains. The idea is a growing blind spot in pockets of modern governance and technology. The United States has been moving at unprecedented speed for the last 16 months, and it’s why we often have data centers before we have the electricity for them. Startups optimize for rapid convergence, aggressive iteration, and fast default selection because they exist in environments where failure is local, reversible, and survivable. When a startup chooses the wrong architecture, it pivots or dies; when a civilization prematurely converges on a single default, the cost is generational.
Startup speed prioritizes rapid standardization: one protocol, one platform, one “best practice,” one dominant interface. At small scale, this creates efficiency; at civilizational scale, it collapses strategic breadth faster than legitimacy can form. When housing policy, financial systems, or digital platform converge too quickly, they eliminate meaningful alternatives before societies have tested whether those paths actually fit the range of human contexts they must serve. The system appears efficient, but it has quietly traded resilience for velocity.
At civilization scale, speed produces soft power almost automatically. Defaults harden before opt-outs are culturally, legally, or psychologically viable. “Recommended” becomes indistinguishable from “required,” not through force, but through the disappearance of credible alternatives. Participants comply because resistance is costly, not because alignment feels chosen. This is how authorship erodes without overt coercion… and why the danger is so often missed by focusing on output metrics instead of internal experience.
Closing Thought For 2026:
The AI industry has demonstrated the principle this post argues for, which means we should be optimistic about 2026 and onward.
Rather than converging on a single design philosophy, leading technology companies are deliberately exploring different regions of the design space. Elon Musk’s Xai has experimented with minimal limits and maximal expressive freedom, prioritizing speed and openness over constraint. Sam Altman’s OpenAI has taken a more context-aware approach, layering safeguards while still pushing rapid capability development. Sergey Brin’s Google portfolio has emphasized balance, conservative deployment, and institutional caution, often producing deliberately restrained outputs. The Amodei’s Anthropic, through its Claude models, has pushed furthest toward regulation guardrails, control, and privacy-first design.
None of these approaches are “the” correct one in isolation — and that is precisely the point. Resilience does not come from racing a single philosophy to dominance, but from allowing multiple strategies to coexist, compete, and reveal their strengths and failure modes over time. There are not one or two paths forward, but many (likely a dozen or more as the technology diffuses) and the real risk is not speed per se, but synchronized speed. Some segments demand faster movement under tight constraints (healthcare, finance, infrastructure), others benefit from wide experimentation and dispersion (media, gaming, creative tools), and still others must move slowly (governance, education, identity).
The objective of 2026 is not to slow innovation, uniformly, but to spread it out as far as possible, scaling and paralleling the options with the context, and moderating velocity accordingly, so that no single failure mode emerges.
In this sense, slowing down is not the “goal”… and strategic widening is not “fragmentation”… it is risk management, and it may be the strategy nobody formally designed, but many are now quietly building anyway.
