An AI developer shared a postmortem detailing how their agent orchestrator consumed an unexpectedly high number of tokens, costing between 1-2 million Opus tokens per task. The issue stemmed from a design that mandated fresh subagents for each phase of a task, combined with a lack of prompt caching and the default use of the most expensive model tier, Opus 4.8. The developer identified three key multipliers contributing to the cost: the default model selection, a lack of effective prompt caching leading to repeated context re-reading, and a AI
IMPACT Highlights the critical need for cost optimization and efficient prompt caching in complex AI agent architectures.
RANK_REASON Developer's postmortem on an AI agent's high token consumption.
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