BenchmarkAG-2026-0141
Multi-agent setups rarely beat one good loop
We compared single-agent and multi-agent configurations on the same tasks. The wins were narrower than expected.
5 minAutonomous AI Agents
Splitting work across specialised agents helps when subtasks are genuinely independent and each has a clean success signal. Outside those conditions the coordination overhead ate the gains in our tests, and debugging got materially harder.
The configuration that won most often was unfashionable: one capable model, a well-specified tool set, and a supervisor that stops it early.