Adding a 7th subagent pushed my orchestrator latency from 22s to 31s — the opposite of what I expected.
I'd been running a fanout pattern in my ad-creative analysis SaaS: spawn N subagents in parallel, collect results, merge into one verdict. The parallel part worked fine. Individual subagents finished in 9–12 seconds regardless of how many I spawned. The problem was everything after that.
With 8 subagents, each returning ~800 tokens of analysis, the orchestrator was assembling a 6,400-token context before it could even call the LLM once. On Cloudflare Workers, serializing 8 JSON blobs into a single prompt string was taking 4+ seconds of pure CPU time before the first API call fired. The log entry that made it obvious:
[worker:orchestrator] WARN
aggregate_context_size=52480 bytes
