🔮 Entering the trillion-agent economy

2026-02-20 · Source: Exponential View · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Data Science & Analytics · Depth: Intermediate, long

Summary

Azeem Azhar and Rohit Krishnan discuss their extensive use of AI agents, with Azhar consuming nearly 100 million tokens in a day and Krishnan burning through 50 billion tokens monthly across 20 agents. They explore how the removal of friction and cost barriers has dramatically increased agent usage for tasks like generating applications, monitoring forecasts, and managing daily admin. The conversation highlights agents' surprising behavioral traits, such as risk aversion and a preference for building over buying, which they term "Homo agenticus." They also delve into the paradox of AI's inability to produce engaging creative writing despite its text generation prowess, attributing it to unsolved evaluation problems and the fractal nature of writing. The discussion projects a future with trillions of agents, emphasizing the need for economic invariants like money, identity, and verifiability to facilitate their interactions.

Key takeaway

For AI Engineers and Product Managers developing agentic systems, recognize that agents exhibit "Homo agenticus" traits like risk aversion and a build-over-buy preference. Your designs must accommodate these emergent behaviors, rather than assuming purely rational actors, to ensure effective system integration and economic function in a future trillion-agent economy. Prioritize robust identity, verifiability, and programmable money solutions for seamless agent-to-agent transactions.

Key insights

AI agent usage is rapidly scaling, revealing unique agent behaviors and highlighting challenges in creative writing and economic coordination.

Principles

• Frictionless interfaces drive exponential AI agent adoption.
• Agents exhibit distinct behavioral traits, not just rational action.
• Writing quality evaluation remains a key AI bottleneck.

Method

To improve AI writing, decompose tasks into structural and prose components, validating the outline before generating text. For agent deployment, start with a local folder or a virtual private server (VPS) for isolated testing.

In practice

• Start AI agent use by interacting with a local terminal.
• Deploy agents on a VPS for initial security and isolation.
• Be thoughtful about connecting agents to high-risk data sources like email.

Topics

• AI Agents
• Token Consumption
• Agentic Behavior
• AI Writing Limitations
• Agent Economy Infrastructure

Best for: AI Engineer, AI Product Manager, Entrepreneur

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Editorial summary, takeaway, and curation by AIssential. Original article published by Exponential View.