Section 047 · Chapter 7, Release Readiness for AI Systems
Cost, Latency, and Quality Tradeoffs
A model can be smarter, slower, safer, riskier, cheaper, and more expensive all at the same time. Quality decisions need the whole picture.
latencyescalationcost latency quality tradeoffs
What to do
- Use cheaper, faster paths for low-risk work and stronger paths for high-risk or ambiguous work.
- Define runnable checks that exercise latency, escalation, and cost latency quality tradeoffs.
- Set acceptable outcomes and blocker failures for latency, escalation, and cost latency quality tradeoffs before running the evaluation.
Evidence to preserve
- Preserve the inputs, versions, configurations, raw outcomes, and results for latency, escalation, cost latency quality tradeoffs needed to reproduce work on Cost, Latency, and Quality Tradeoffs.
- Report results for latency, escalation, cost latency quality tradeoffs by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.
Expert note
Expert teams build Pareto views: quality, safety, latency, cost, and escalation rate. A release candidate is not automatically best because it wins one metric; it is best when it sits on the right frontier for the product's risk and economics.
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Cite this page
Jason Arbon. "Cost, Latency, and Quality Tradeoffs." Testing AI Knowledge Edition, section 47.
https://jarbon.ai/testing-ai/knowledge/ch047-cost-latency-quality-tradeoffs.html