Never add agents to sequential tasks — only distribute…

Never add agents to sequential reasoning tasks—distribute additional agents only to genuinely parallel workstreams where coordination overhead is measurably less than throughput gain.

When This Fires

When considering adding people, tools, or parallel processes to a task that's too slow
When a project is behind schedule and "more resources" is proposed as the solution
When designing multi-agent cognitive systems and deciding agent count
When Brooks's Law is being violated in practice ("let's add more people to speed this up")

Common Failure Mode

Adding agents to bottlenecked sequential work: "The analysis is taking too long — let's have two analysts." If the analysis requires understanding the full dataset and building conclusions iteratively, splitting it between two people adds context-sharing overhead without enabling parallelism. The serial nature of the reasoning is the constraint; more agents can't parallelize it.

The Protocol

(1) Before adding agents/resources to any task, classify: is this task sequential (each step depends on the previous) or parallelizable (independent subtasks can run concurrently)? (2) If sequential → do not add agents. Instead, optimize the serial process itself (Only optimize the constraint — verify that improving… — identify the constraint within the serial chain). (3) If parallelizable → estimate coordination cost: handoff time, synchronization time, communication overhead, duplicate work. Also estimate throughput gain from parallel execution. (4) Add agents only if throughput gain > coordination cost with margin. If the math is marginal → don't add. Coordination costs are always underestimated. (5) After adding, verify (Review new agents 7-14 days after deployment — remove…): did actual coordination cost match the estimate?