AI Agent Cost Is a Runtime Signal | Focused Labs

Short summary

AI agent costs should be managed as runtime signals through harness policies and observability traces, not as monthly bills. Cost per outcome is more valuable than cost per token, and effective controls must integrate budget windows with trace data, evals, and operational policies. Budget windows should warn early, attribute expensive traces, throttle wasteful loops, and preserve detail for the harness to recognize patterns.

• •Agent costs are driven by runtime behavior—model selection, retry loops, context size, and harness policies—not fixed service tiers
• •Monthly bills hide the actual cost path; tie budget controls to observable traces and outcomes for effective management
• •Spend ownership belongs in the harness layer, not a thin proxy; budget windows must alert, attribute, throttle, and learn

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