How I cut coding agent costs with model and harness routing

Coding-agent costs are shaped not only by model token prices but also by harness behavior, including context management, retries, tool calls, subagents, and review processes, making cost per accepted outcome a more useful metric than raw cost per request. Drawing on experiments at Arize, the author describes reducing a daily bug-finding bot’s estimated cost from about $100 using Opus 5 end to end to $15–$20 by having Kimi K3 Max manage the workflow, cheaper models handle routine tasks, and Opus 5 act as an advisor, although equivalent quality was not rigorously established. Two main routing approaches are presented: using a frontier model to orchestrate lower-cost subagents, or allowing a cheaper model to run the process while consulting a frontier advisor at key decision points. A similar multi-agent security scan reportedly identified more than 20 potential high-severity issues for about $100, versus an estimated $1,000–$2,000 with a frontier model alone, but all findings required human validation. Effective evaluation requires fixed task sets, predefined acceptance criteria, repeated trials, full tracing of token and tool usage, and inclusion of human review and failed attempts. The author also emphasizes reducing unnecessary context from command output and repeated searches, using deterministic tools for verification, and reserving costly frontier-model capacity for planning, ambiguity, escalations, and final review while assigning exploration, summarization, and routine implementation to less expensive models.

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