Q6 of 60 — CCA Practice Exam

Multi-Agent Research System

Your multi-agent research system is investigating a complex policy topic using a lead agent and six research subagents. After deployment, you observe that the lead agent rarely reassigns work and frequently stalls waiting for one or two subagents that have been running for 45+ minutes without producing output. Meanwhile, other subagents finish their tasks in under 5 minutes and sit idle. What is the most likely root cause and the most effective architectural fix?

A. The lead agent lacks sufficient context about the research topic. Expanding the system prompt with more background will help it anticipate slow subagents and proactively redistribute work before stalls occur.

B. The subagents' tasks are sized too large. Without self-contained deliverables and natural check-in points, the lead cannot detect stalls or reassign work. Tasks should be decomposed into smaller, clearly scoped units each producing a concrete deliverable.

C. The system is under-resourced. Spawning additional subagents to run redundant copies of the long-running tasks in parallel will reduce the probability that all copies stall simultaneously and restore throughput.

D. The lead agent's coordination loop is too slow. Increasing the lead's max_tokens budget will allow it to monitor more subagents per cycle, process status signals faster, and detect stalls earlier in the pipeline.