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Field notes/Community builds/Why Most Multi-Agent AI Systems Waste 90% of Their Time (And How to Fix It)

Why Most Multi-Agent AI Systems Waste 90% of Their Time (And How to Fix It)

The bottleneck isn't concurrency — it's setup overhead. At 50 agents that's 4,500s spent preparing to work vs 50s with memory snapshots.

DYDivy Yadav·JUN 16, 2026·15 MIN READ·Community builds
SBX-01C4SBX-01E3SBX-0202SBX-0221SBX-0240SBX-025FSBX-027ESBX-029DSBX-02BCSBX-02DBSBX-02FASBX-0319SBX-0338SBX-0357SBX-0376[ RUNTIME: ACTIVE ] P50 2.45S · P99 4.12S · 5M/PROJECT

Divy's numbers on why multi-agent systems feel slow: the bottleneck isn't concurrency, it's setup overhead repeated per agent. At 50 agents that's 4,500 seconds spent preparing to work; forking each agent from one memory snapshot cuts it to 50. The longest read in this list, and the most thorough on the arithmetic.

We didn’t write this one — it’s Divy Yadav’s piece, published on Towards AI. The note above is ours; the full article is theirs.

Read the full piece on Towards AI ↗
DY
WRITTEN BYDivy YadavCommunity · Towards AI
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