Show notes
Most AI agents today run on the same pattern: give the model a goal, dump in a giant system prompt, let it loop through tool calls until it decides it's done. It's flexible. It's also burning enterprise budgets for no good reason.
In this episode, we break down why the generalized agent loop, the default architecture behind most agentic AI, is quietly a tax on an enterprise's margin. Anthropic's own research shows agents can burn 4x the tokens of a normal chat, multi-agent systems up to 15x, and paying a frontier model to rediscover business rules on every single turn adds up fast.
We dig…
