The short answer
Additional agents create coordination work as well as parallel capacity. Compare final evidence quality and failure recovery alongside completion speed.
The question and scope
This article is an AI-assisted research-design draft for editorial review, not a report of a completed experiment. It asks how to evaluate single agent vs multi agent in a documented setting. No measurements, participants or client outcomes are claimed here.
An illustrative test case
Two agents independently retrieve the same outdated page and then agree. Parallel completion looks efficient, but an independent evidence check remains necessary for a supported conclusion.
This scenario defines a case to examine; it is not an observed result.
A proposed investigation
Use matched research or engineering tasks with the same total budget. Compare one agent with a fixed multi-agent arrangement. Record duplicate work, conflicting conclusions and the coordinator's decisions.
Record setup versions, inputs and outcomes in a run ledger. Use repeated trials and matched comparison cases; preserve failed runs as well as successful ones.
What to measure
- Accepted-task rate.
- latency.
- cost.
- duplicated work.
- unsupported consensus.
Retain raw observations and explain exclusions. Human grading needs a documented rubric; acceptance thresholds need a stated rationale.
Interpretation and limitations
A weak single-agent prompt is not a fair baseline. Tune both configurations on separate development tasks.
Distinguish a plausible mechanism from a demonstrated effect. Preserve uncertainty when the design cannot eliminate alternative explanations.
A practical review checklist
- Is the question narrow enough for the available system or dataset?
- Are the comparison conditions genuinely comparable?
- Can a reader trace each conclusion to an observation?
- Are the boundaries and unresolved assumptions visible?
- Does the decision change if the result is negative or inconclusive?
The publication artifact
The useful deliverable is a reproducible protocol, a measurement table and a decision note explaining what the evidence would change. Add actual results only after the investigation has been conducted and reviewed. This blueprint does not establish a novel finding or a provider-wide claim.
Sources and further reading
These primary resources are starting points for the concepts and controls involved. They do not validate the proposed experiment or its unmeasured outcomes. Check version-specific documentation when implementing the protocol.