Contrary to the view that AI token intensity will drop after the initial coding boom, the move from simple queries to autonomous 'agentic' workflows will cause an order-of-magnitude (10x) increase in token usage per task. This applies across all knowledge-based jobs, ensuring sustained and explosive demand for compute.

Features like Codex's '/goal' create a new paradigm of persistent, autonomous agents that can work on a task for days. This shift from active human prompting to unattended 24/7 AI work is expected to cause an exponential increase in token consumption and compute demand, reinforcing the infrastructure boom.

Individuals will soon manage hundreds or thousands of personal AI agents running concurrently. This shift from owning 3-4 physical devices to countless virtual agents will cause a tenfold explosion in an individual's demand for underlying compute, memory, and power resources, reshaping infrastructure needs.

For an AI agent to perform meaningful work, it needs more than just a model; it requires its own dedicated computing environment. Services like Orgo provide a 'computer in the cloud' where the agent can live, store files, and execute tasks, enabling true autonomy beyond simple API calls.

The concept of a massive "agentic workforce" is not a distant future scenario but a current reality. Companies are already deploying systems with up to 70,000 AI agents running simultaneously. This rapid, large-scale adoption indicates the transition is happening much faster than commonly perceived, creating urgent infrastructure needs.

The shift from simple query-based AI to agentic AI, where AI calls itself recursively to solve complex tasks, increases compute demand by orders of magnitude. Most people, especially non-coders, fail to grasp this exponential shift, leading them to consistently underestimate the scale and duration of the AI infrastructure build-out.

The next wave of AI adoption involves 'agentic' workflows, where AI performs complex tasks autonomously. This shift from simple queries to agentic use is expected to increase token consumption by approximately 10x per task. This will drive a massive explosion in compute demand across all knowledge-work industries, not just coding.

The largest driver of future energy consumption for AI won't be human-initiated queries on chatbots. Instead, it will be the massive, continuous "machine-to-machine" traffic generated by autonomous AI agents performing tasks, which will ultimately swamp human-AI interaction and create a runaway demand for compute power.

The transition from chatbots to autonomous 'agentic' AI represents a fundamental step-change. These agents, which execute complex tasks independently, have already increased the demand for computational power by 1000x, creating a massive, ongoing need for new infrastructure and hardware.