In my experience the biggest multiplier isn't any single variable it's the interaction between them. Fanout × retries × context growth compounds in ways that linear cost models completely miss.

The fix that worked for us: treat budget as a hard constraint, not a target. When you're approaching limit, degrade gracefully (shorter context, fewer tool calls, fallback to smaller model) rather than letting costs explode and cleaning up later.

Also worth tracking: the 90th percentile request often costs 10x the median. A handful of pathological queries can dominate your bill. Capping max tokens per request is crude but effective.