The Yield Problem in Long-Horizon Agents
xiaosun86 · x · 2026-07-14
This post discusses a critical issue facing AI agents: whether a model can continuously execute a complete task for over 100 hours without drifting off course.
The author argues that this is fundamentally a yield problem: if the success rate of each step is merely average, failures will quickly accumulate over a long-chain task. However, if each step achieves a 99.9999% success rate, the system can sustain task progression for much longer.
Related event: Grok 4.5 Touted as More Enterprise-Ready for Long Agents(2 posts)→
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