Benchmark reveals macOS Gatekeeper slows parallel AI agent workflows, not daily use

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A developer running AI coding tool Codex with parallel agents on a MacBook Air noticed significant slowdowns and built a small benchmark to identify the cause. The culprit was not Gatekeeper itself but the repeated launching of executables from many new file paths, which forced macOS to assess each one fresh. In tests, launching copies of a binary from 50 new locations jumped completion time from near-instant to roughly 11 seconds, while repeatedly launching an already-trusted binary remained fast. Attempted system-level workarounds like lowering syspolicyd process priority and restarting the daemon provided no meaningful relief. The author concluded the practical fix is to avoid unnecessary executable path churn and pre-warm new tools before deploying them across parallel agents, rather than disabling Gatekeeper entirely.

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