Cutting agent latency from 30s to 8s without model swap
SapotaCorp successfully reduced the latency of an AI chat product from 31 seconds to 8 seconds without changing the underlying model. This improvement was achieved by optimizing the agent's structure rather than switching to a faster model. As a result, the user abandonment rate dropped by 70%.
- ▪The original AI chat product had a p95 response latency of 31 seconds, with the model contributing only 11 seconds to that total.
- ▪By parallelizing tool calls, eliminating unnecessary intermediate steps, and implementing response streaming, latency was significantly reduced.
- ▪The changes made did not involve altering the AI model, demonstrating that structural optimizations can yield substantial performance improvements.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3948393) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } SapotaCorp Posted on May 24 • Originally published at sapotacorp.vn on May 24 Cutting agent latency from 30s to 8s without model swap #aiagents A founder pinged us with a UX problem disguised as an engineering question. His team had launched an AI chat product. Users were abandoning the conversation before the agent finished responding. The team had measured p95 response latency at 31 seconds. Their assumption was that they needed to switch to a faster model.
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