How can you optimize Claude Sonnet 5's effort setting across a fleet of subagents?

Set a lower default effort, such as low or medium, on individual subagent calls specifically, reserving higher effort for the top-level orchestrating call that's actually making the higher-stakes planning and coordination decisions, since subagent-level work is often narrower in scope and less likely to need the deepest reasoning available.

Measure whether raising a specific subagent's effort actually changes its output quality on the type of narrow task it's typically assigned, rather than uniformly raising effort across the whole fleet preemptively, since thinking-token overhead compounds multiplicatively across many parallel or sequential subagent calls in a way that a single top-level call's effort setting doesn't.

Consider whether some subagent roles are well suited to having thinking disabled entirely, particularly for narrow, mechanical subtasks like formatting, simple lookups, or routing decisions where reasoning is unlikely to change the outcome, since this removes an entire category of token spend across every instance of that subagent role rather than just reducing it via a lower effort level.

Periodically re-audit this configuration against actual production outcomes as the fleet's task distribution evolves, since a subagent role that started out narrow and mechanical can drift toward handling more complex cases over time, at which point an effort setting that was originally well-tuned may need to be raised again for that specific role.

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