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Building Cost-Resilient AI Agents
AI agents sound cheap until they fail. A single fifty-turn session costs ninety cents—but when agents loop or restart from scratch after a mid-workflow failure, that cost multiplies fast. An eighty-five percent reliable step sounds solid until you compound it across ten steps: you're down to twenty percent success. This episode digs into the engineering that prevents wasted money when agents break: checkpointing patterns that let you resume without restarting, retry strategies that distinguish between recoverable and permanent failures, caching that memoizes expensive LLM calls, and the…
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