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AI Economics

54 summarised stories about AI Economics, each linking back to the original source. Browse all topics →

Wednesday, 15 July 2026

You Just Hired a Million Bad Employees

TLDR 1 day ago

Companies are deploying AI agents without proper management frameworks, creating wasteful "loops" where poorly-trained employees use AI inefficiently to compensate for unclear processes. The vast majority of token spend produces no value, mirroring how 80% of traditional employees often perform no meaningful business function. The key to unlocking AI value lies in building rigorous evaluation systems and AI transformation services that encode each firm's specific processes into measurable outputs, similar to how coding became the only breakout AI use case because code either runs or fails.

The Great Flattening

TLDR 1 day ago

As AI inference costs decline, companies can process larger volumes of requests without hitting capacity constraints, shifting the focus from resource scarcity to deliberate prioritization of what to build. Organizations using this approach operate with smaller engineering teams while increasing API token consumption, enabling faster feature deployment. This allows product teams to respond directly to customer feedback with merged code changes rather than being bottlenecked by engineering capacity.