Behind the Outbreak of Intelligent Agents

Author: Jordi Visser

Over the past three years, since the release of ChatGPT, my life has undergone a revolutionary transformation that far exceeds all my original expectations for the future. I still remember the day someone suggested I take a Python course to better harness ChatGPT; and then, within just three hours of a YouTube tutorial, my self-doubt was completely shattered—I had once lacked confidence, unsure if I could do anything meaningful with computers. But despite all these advances, nothing compares to the massive upheaval in my daily life since I set up my first OpenClaw. A thought flashed through my mind: just send a message to my assistant on my phone to build this idea, review it after a busy day at home, or run an overnight task and evaluate the results the next morning—this is an absolutely game-changing experience. Tasks that used to take weeks now only take minutes. At first, I thought it was just replacing work that previously required hiring people. But the more I used it, the more I realized this is just the beginning. What truly matters is the broad activity these systems will trigger across the entire internet. OpenClaw is the gateway to the intelligent agent consumer economy.

In the past few years, most people have understood AI through the lens of the chatbot era: it can provide better answers for humans. This cognitive framework is now outdated. We are now entering a larger, more disruptive domain: the rise of autonomous intelligent agents. They are no longer just responding to humans but are acting on behalf of humans, trading with other agents, and coordinating in both digital and physical worlds. OpenClaw is important because it signals that this shift is no longer just theoretical. It marks the official beginning of the agent layer, where AI is no longer just a conversational tool but becomes the infrastructure for action.

From billions of humans to trillions of agents

This shift could create one of the most significant transformations in the structure of economic demand in modern history: a leap from billions of human consumers to trillions of agent consumers. For centuries, technology has changed production, labor, and distribution, but the ultimate buyers have always been humans. Industrialization replaced workers, but humans still bought goods. The internet eliminated brick-and-mortar stores, but humans still clicked to buy. In the next phase, this assumption will be broken. Increasingly, the direct buyers, schedulers, negotiators, and executors will no longer be humans but agents.

Human consumers are limited by physiology, attention, time, biases, emotions, and transaction frictions. They need sleep. They hesitate. They can only compare a few options and make imperfect decisions. Agents, on the other hand, can instantly compare thousands of variables, make dynamic adjustments, and continuously optimize until the transaction is complete. The vision of trillions of agent consumers is not an exaggeration of the future. It is an inevitable outcome of embedding intelligence into software, devices, platforms, vehicles, robots, and ultimately humanoid robots. One person might control dozens of agents, while a company could deploy millions. An intelligent factory will operate as a dense network of agents responsible for ordering parts, procuring power, allocating computing resources, managing robot workflows, and settling transactions between suppliers and logistics networks. Even if the human population remains unchanged, the number of economic participants will expand exponentially.

Labor: a disruptive wave sweeping both supply and demand

This profoundly impacts the labor market. Historically, technological disruption has mostly replaced supply-side jobs, with humans remaining central on the demand side. But the agent economy is fundamentally different because this wave of disruption affects both sides simultaneously. Humans are not only under pressure as workers; as transaction participants, they are increasingly marginalized. An increasing proportion of economic activity is now conducted through “agent-to-agent” transactions that require no human intervention.

This does not mean humans will disappear entirely. The labor market will shift toward oversight, orchestration, exception handling, trust mechanism design, and high-dimensional decision-making. However, the traditional assumption that “creating jobs will feed back into human-centered demand systems” is becoming increasingly unreliable. In this new cycle, a growing share of demand may come from non-human participants operating on machine logic rather than household psychology.

Time compression and the velocity of money circulation

Modern economic analysis is largely built around human time scales. Growth, productivity, and GDP are measured within frameworks shaped by working hours, payroll cycles, settlement delays, and household consumption behaviors. The agent economy compresses time. It significantly accelerates the execution of tasks, decision-making, and transaction completion. Time has always been an implicit constraint on economic growth, but intelligent agents are breaking this constraint.

This is where the velocity of money circulation comes into play. By automating negotiations and settlements of trillions of microtransactions, agents greatly increase the speed at which capital flows through the system. The surge in nominal economic activity is not just because more things are happening, but because things are happening faster. On a macro scale, this time compression begins to manifest as accelerated growth.

The inevitability of embracing programmable money amid fiat friction

But this acceleration encounters a stumbling block. An almost infinitely fast operating layer of agents cannot seamlessly interface with traditional financial infrastructure built around ACH, SWIFT, business hours, reconciliation delays, and manual reviews. The faster the agent economy grows, the more glaring this friction becomes. Traditional financial rails are designed for a world where humans are the primary participants. They are fundamentally incapable of supporting trillions of autonomous, cross-border, cross-platform value settlements.

A world with trillions of agent consumers cannot operate on trust systems designed for slow human oversight. Without programmable safeguards, risks become unmanageable: uncontrolled spending, recursive feedback loops, automated fraud, and large-scale lightning-fast systemic failures that traditional finance cannot handle. The future calls for native monetary and asset systems in a world of autonomous, non-human participants.

This is the opportunity for cryptocurrencies to shift from speculative side assets to strategic infrastructure. Stablecoins enable real-time settlement. Smart contracts allow conditional execution. Wallets become operational accounts for agents. On-chain systems enable clear identification of ownership, permissions, and collateral. Machine commerce requires more than speed; it demands programmable constraints—rules embedded directly into the transaction layer. In the machine economy, compliance, authorization, risk limits, and settlement logic cannot be slow, manual add-ons outside the system—they must be integral parts of the protocol.

Bitcoin, tokenization, and the expanding digital economy

In this future landscape, Bitcoin’s role differs from that of programmable currencies. It acts as a store of value layer. As I have pointed out, it possesses an advantage that fiat-backed digital investments lack: a moat as the preferred digital economic store of value. As the digital economy expands through trillions of transactions driven by agents, the digital asset ecosystem also flourishes. Bitcoin benefits not because it handles machine-to-machine transactions but because it anchors value in this increasingly digital world. The larger the digital economy becomes, the more indispensable a scarce, rule-based, globally recognized digital reserve asset is. Bitcoin’s value proposition grows stronger as the economy it underpins expands.

Tokenization extends this logic further. Today, vast pools of wealth—real estate, private equity, infrastructure, private credit—exist in a relatively dormant state. If trillions of agents need to transact in real-time and continuously mobilize liquidity collateral, these assets cannot remain static. Tokenization converts these assets into granular digital units that can be identified, divided, pledged, and mobilized, transforming dormant wealth into active collateral capable of flowing freely within the machine economy’s financial architecture.

The emergence of humanoid robots makes this grand vision even more expansive. Once agents have physical form, they will become direct participants in physical commerce: ordering parts, purchasing power, contracting logistics, leasing warehouses. The machine economy will extend from cloud infrastructure into the physical world. The most forward-looking consumers in this disruptive wave will no longer be just humans with smartphones—they might be machines holding wallets.

The true significance

For investors, this is precisely the moment of real significance. The narrative of AI is not just about smarter models or cheaper labor. It’s about the birth of a new class of economic participants. OpenClaw is crucial because it announces that the agent layer has arrived now, not in some distant future. Once this layer is fully deployed, the number of active economic participants will leap from billions to trillions. The gears of the economy will accelerate, money will circulate faster, the labor market will be forced to reshape, and traditional financial infrastructure will begin to show its cracks.

This is why programmable money and digital assets are destined to benefit—they are no longer just speculative assets but foundational infrastructure for machine-native commerce. The next great economic transformation may no longer be defined solely by smarter software. Its watershed moment might be the historic instant when consumers themselves cease to be human.