StudioChecksum cut agent task completion from 19 minutes to 2 by giving agents an interpreter instead of tools
Original title: Don't give your agent tools. Give it an interpreter. Production agent task completion went from 19 minutes to 2, same model!
A Checksum engineer argues that instead of giving agents tools to call one by one, you should give them a code interpreter and turn every task into a coding task. Switching to a code-mode based agent cut test generation from 19 minutes to 2 and cost per test from $1.67 to $0.25 with the same model. The post distinguishes loop-level code mode (calling tools as Python functions via a stateful interpreter, e.g. Monty by Pydantic AI) from task-level code mode (making the whole task a coding exercise, e.g. browser-use's browser harness where code traverses the full HTML), and describes caching by design: after an agent completes a task, it writes a script that reruns it without AI, with an agent invoked only when the script errors.
The author backs the code-mode approach with production numbers from Checksum and offers a layered implementation path plus caching, transferable to agent architecture design.
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