7 Ways AI Systems Fail at Scale: 100 Users Fine, 100,000 Broken
goyalshaliniuk · x · 2026-10-03
Shalini Goyal kicked off a thread listing 7 ways AI systems that work perfectly at 100 users break down at 100,000 — arguing scaling is not just adding servers.
The thread walks through engineering failure modes that emerge with growth. Points 6-7 in this batch: monitoring can't keep up (you need automated detection of quality drops, latency spikes, cost increases, tool failures, hallucinations) and security risks multiply (larger attack surface of data, APIs, tools, agents, permissions). Her core advice: build observability, evaluation and least-privilege security in from day one.
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