Engineering·September 8, 2026·9 min read
From Prototype to Production Agent
Lessons learned from running 500,000+ customer conversations across website widgets, WhatsApp Business, and Slack. Latency optimization and prompt drift mitigation.
By AgentFlow EngineeringVerified for AgentFlow v1.4
Moving an agent from a demo notebook to 24/7 production traffic reveals edge cases you rarely encounter during initial testing. Here are three critical engineering lessons:
1. Latency is User Experience Customers expect conversational responses within 1.5 seconds. To achieve this: - Stream tokens incrementally using Server-Sent Events (SSE). - Perform vector retrieval in parallel while evaluating guardrail filters. - Keep tool payloads lightweight and cached where appropriate.
2. Guard Against Prompt Drift As base models receive updates, subtle changes in instruction following can affect tool parameter extraction. Version your system prompts alongside your knowledge indexes so you can roll back instantly if behavior shifts.
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