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AI Features

Context, Cost, and Latency

Explore how context size, token usage, and latency interplay to affect performance and cost in LLM-based chat and retrieval systems. Understand common truncation methods, token-driven cost and delay factors, and strategies for balancing long histories with responsiveness. This lesson guides you to design efficient prompt management and ensure budgets for input tokens, calls, and latency are met for reliable production systems.

A chat feature needs to return a helpful first answer in under 1s1\text{s} at p95p95 stands for the 95th percentile. It is a latency metric used to measure performance across requests., keep the per-interaction spend under a small fixed ceiling, and still handle users who paste long documents and arrive with weeks of conversation history. The ...