Paul Virilio was a French cultural theorist well known for his theory of dromology. Dromology explores the logics and impacts of speed in the modern era. At its core, it theorizes how the velocity of action or decision-making enables actors to accrue wealth and power over others. Virilio often approached this concept through the lens of martial power, contemplating how new means of movement — the horse, the automobile, telemetric control — created new capacities to overcome the frictions of time and space, and to overcome adversaries through heightened sensing and accelerated decision-making.
We exist in an era of digital intensification. Cybernetic systems are now core to many people’s daily realities, including systems over which they have little meaningful influence or control. Earlier digital modernity was often described as an “attention economy.” Today, we may be entering what I’ll call a “velocity economy,” which is increasingly grappling with the implications of a faster-moving world.
Escape Velocities
Om Malik has written recently on velocity and how it may now precede attention as a structuring condition:
What matters now is how fast something moves through the network: how quickly it is clicked, shared, quoted, replied to, remixed, and replaced. In a system tuned for speed, authority is ornamental. The network rewards motion first and judgment later, if ever. Perhaps that’s why you feel you can’t discern between truths, half-truths, and lies.
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Algorithms on YouTube, Facebook, TikTok, Instagram, and Twitter do not optimize for truth or depth. They optimize for motion. A piece that moves fast is considered “good.” A piece that hesitates disappears. There are almost no second chances online because the stream does not look back. People are not failing the platforms. People are behaving exactly as the platforms reward. We might think we are better, but we have the same rat-reward brain.
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When velocity becomes the scarcest resource, everything orients around it. This is why it’s wrong to think of “the algorithm” as some quirky technical layer that can be toggled on and off or worked around. The algorithm is the culture. It decides what gets amplified, who gets to make a living, and what counts as “success.”
Once velocity is the prize, quality becomes risky. Thoughtfulness takes time. Reporting takes time. Living with a product or an idea takes time. Yet the window for relevance keeps shrinking, and the penalty for lateness is erasure. We get a culture optimized for first takes, not best takes. The network doesn’t ask if something is correct or durable, only if it moves. If it moves, the system will find a way to monetize it.
The creation and publication of content — and the efforts to manipulate engagement metrics to juice algorithms — have long been partially automated. Bot and content farms are not new. What may be new is the scale and ease of synthesis. As the cost of producing text, images, summaries, and responses to each declines through the widespread adoption of LLMs and agentic systems, the volume of generated material increases dramatically.
That increase in volume does not just mean “more noise.” It alters competitive dynamics and means that velocity — which then accrues attention — becomes key in an algorithmically intermediated world. In this environment what is increasingly put under pressure are decisional latencies — the time between sensing, synthesizing, and acting. And humans are making decisions on what to focus on based on automations and algorithms designed to cull out what they “should” be paying attention to.
Earlier digital acceleration primarily affected distribution: messages moved faster, and telemetrics enabled the expression of power at heightened distances, as examples. Now we may be witnessing the acceleration of what looks like cognition. LLMs have no theory of mind insofar as they do not “understand” in any human sense. Yet they can synthesize, summarize, categorize, and prioritize at speeds that mimic cognitive activity. And when those synthesized outputs are connected to agentic systems capable of taking action — filing forms, executing transactions, triggering workflows — we move beyond accelerated messaging into accelerated execution. Decisional latencies can become compressed in order to produce outputs that move sufficiently fast, and with sufficient purchase, to be registered by algorithms as worthy of amplification and, ultimately, human attention.
Put differently: as velocity becomes a mode of capturing attention there is pressure to move more quickly in the face of other, similarly fast-moving outputs, and in ways that potentially exploit or game algorithms in an effort to obtain human attention.
New Velocity, New Harms
For Virilio, every accelerant technology carried with it a corresponding accident. The invention of the ship implied the shipwreck. The car led to the car crash. Radio and telecommunications enabled new forms of propaganda and coordinated deception. And so on.
LLMs and agentic systems may carry their own accident structures. They enable mass automated persuasion at scale. A flaw in a widely deployed foundation model could result in class-breaking errors replicated across applications dependent on that model.
Agentic systems introduce further risks: cascading autonomous mis-executions, rapid propagation of flawed decisions, and compounding feedback loops that create significant problems before humans detect them.
AI accidents have the potential to be more distributed and more simultaneous than prior automation failures. While automated systems have long-posed risks the generalized and cross-sector nature of foundation models could expand the blast radius of automated harms. When many systems rely on shared models or shared training data, correlated failures become more plausible.
Velocity, in this sense, does not merely amplify error; it compresses the window in which errors can be identified and corrected. It risks creating brittle systems and generating what Charles Perrow has called “normal accidents.”
Velocity and Organizational Impacts
If decisional latency becomes the friction to be minimized in a velocity economy, organizations may feel pressure to shorten analytic cycles and accelerate workflow tempos. In domains where speed confers agenda-setting power, organizations may need to move faster or risk marginalization.
At the same time, we might see a divide emerge. Some institutions may further prioritize velocity and first-mover visibility as a way to shape agendas. Others may deliberately preserve slower processes to protect legitimacy and safety. Friction — often treated as inefficiency — may be read as functioning as a source of institutional credibility. It may, also, be used by some organizations to justify their resistance to innovation and with the effect of falling behind other actors.
As information volume expands, organizations and individuals may increasingly depend on third-party systems to track, assess, and prioritize what is “meaningful.” LLMs and agentic systems may be paired with other automated triage systems designed to impose order on informational abundance.
Yet such sense-making is inherently lossy. The world is dense with detail, contingency, contradiction, and edge cases. When LLMs normalize information statistically, much of that raw specificity can be abstracted away. The effect can be that important context is never surfaced for human review; reliance on abstracted assessment systems to navigate a digitally intermediated world may entail a further loss of representational fidelity.
This abstraction is not unprecedented — humans have always distilled complexity — but the scale and automation of the distillation may be new. And as (or if) human review recedes the capacity to interrogate what has been smoothed over may diminish.
Organizations must also determine when they will introduce human review as well as when they will deliberately refrain from doing so. Prioritizing human assessment of all outputs could introduce friction that other organizations or jurisdictions may not demand. A majority-human-review organization may operate outside the dominant tempo of a velocity economy, with the end of potentially gaining legitimacy and safety while simultaneously sacrificing influence or timeliness.
Organizational Consequences of LLM and Agentic Velocity
If LLM- and agentic-enabled systems increase the rate at which information is generated and decisions are executed, several consequences may follow.
- The distribution of power may become linked to access to compute, to foundational models, to reliable data, and to the capacity to act digitally or physically. Countries that dominate the production — or regulation — of foundational models may accrue disproportionate influence. Where production and regulation of AI models or systems diverge between nation-states or geopolitical regions, conflicts over norms and authority may intensify.
- Organizations may need fast initial outputs to secure attention in a velocity-based information environment. However, rapid outputs need not be final outputs. Deeper analysis may continue in parallel, informing subsequent action and ensuring that longer-term activities based on such analysis remain well grounded in facts and aligned with strategic priorities. Organizations that excel at this two-track approach to knowledge production may gain strategic benefits in being able to set agendas as well as subsequently navigate them with complexity, depth, and institutional integrity.
- Where agentic systems are entrusted to make certain classes of judgments, institutions must determine under what conditions (and to what extent) they will add the friction of human oversight. The more friction introduced, the greater the potential divergence from competitors operating at full automation speed. At the same time, human-informed decision-making may confer benefits of perceived legitimacy and safety.
- Institutions must carefully consider how they can, and cannot, adopt LLMs and agentic systems so they are responsive to changes in the lived reality of the world while at the same time working to carefully protect social trust that they possess. There may be increased pressures on institutions to align their decisional horizons with machine-accelerated and innovation-driven time horizons, perhaps requiring shifts in decisions from slow and fixed in time, to more fast moving and subject to routine revisions. For bureaucratic organizations or institutions this could require major changes in decisional structures and processes.
Future Looking Velocity-Imposed Pressures
If we are to take Virilio’s insights seriously, along with changes in technological activity per Malik’s thoughts, then there are at least three tensions worth watching:
- Organizations with access to contemporary models may be able to move more quickly and accurately, with the effect of reducing the time delta in summarizing or producing information while compressing decisional cycles. At risk, however, is whether this elides the specificity that is reflective of the actual world and has the effect of delegitimizing actual decisions as a result of minimal (or insufficient) human oversight or governance. To what extent might LLM- and agentic-forward organizations make bad decisions more quickly and undermine their legitimacy? How much will access to contemporary models differentiate between organizations’ abilities to undertake rapid-pace sense-making and decision making?
- Epistemic pressures may worsen as synthetic media is produced at scale and automated intermediaries filter what humans encounter. What happens when your digital assistant, or one your organization relies on, has been sorting content for months, only for you to discover it has been amplifying propaganda because of model poisoning or bias you did not anticipate? What to do when the decisions you’ve been making have unknowingly been badly torqued to the advantage of other parties?
- Class-breaks that result in cascading failures become more plausible in monocultural model ecosystems. To what extent does widespread reliance on common foundation models create systemic points of failure that are difficult to detect, diagnose, or correct? Will this encourage the development of more ‘small models’ in an effort to stem or mitigate these kinds of security impacts?
Virilio suggested that speed restructures power. Malik suggests that velocity now structures visibility and attention. If LLMs and agentic systems compress not only communication but also enable synthetic cognition and decisional executions, then the next few years may test whether institutions can preserve legitimacy, trust, and factually-driven actions and decisions in a world increasingly oriented around motion.
It will be interesting to assess whether friction comes to be seen increasingly as an obstacle to wealth or power, or whether organizations that maintain appropriate degrees of friction preserve (or expand) their legitimacy relative to those that move quickly and break things.