To be honest, this is getting terrifying. Word is going viral: a 23-year-old developer ran 300 Claude Code instances at once. But the real story isn't the scale—it's that he assigned a cheaper "supervisor" AI to catch the worker AIs the second they hallucinate. On his dashboard: 300 AIs cross-check data from 100 companies three times, verifying every line against source text within 0.1 seconds before saving it to a knowledge base. A task that takes an analyst team weeks was done in a single run. Managing an agent fleet myself, I feel the exact same way: AI output volume doesn't matter; controlling hallucinations does. This shifts the game across three dimensions: Technology: We are moving from simple generation to Multi-Agent Governance. The true bottleneck is no longer context size, but real-time, low-latency validation loops. Brand: Trust is currency. Brands using unmonitored AIs risk reputational suicide, while those leveraging "AI-governed AI" can scale 100x faster without sacrificing accuracy. Risk: Mass automation brings new vulnerabilities. If the verifier shares logical flaws with the worker, you risk scalable confirmation bias—amplifying subtle errors thousands of times before a human intervenes.