Why AI Features Need a Single Runtime Budget Across All Dependencies

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Individual timeouts on AI model calls, tools, and retries do not prevent a workflow from running too long or costing too much overall. A single runtime budget tracks wall-clock time, token usage, model calls, tool invocations, retries, and estimated cost as one shared envelope across an entire execution. These dimensions interact — a retry consumes extra time and tokens, while a tool call can expand the next model prompt — making isolated limits insufficient on their own. A well-designed budget enforces immutable configured limits while a live ledger tracks consumption per execution, dynamically adjusting per-attempt timeouts based on remaining time and a completion headroom reserve. The approach treats a late or overpriced result as a failed execution, deliberately stopping work that exceeds acceptable bounds rather than allowing runaway costs or delays.

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