SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives cover art

SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives

SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives

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 Executives often demand reliability from AI but lack a shared language to measure it. In this 20-minute monologue Mirko opens with a concise vignette where unseen model latency and stale features caused revenue slippage, then delivers a compact, decision-first playbook for Service-Level Objectives (SLOs) tailored to models and data. Listeners learn how to define business-aligned SLOs (accuracy bands, latency windows, freshness, fairness thresholds), set error budgets, choose a minimal monitoring signal set that executives can read, and map SLO breaches to concrete decision gates and funding actions. Practical artifacts include a board-ready SLO template, example alert thresholds, and a prioritized 30–90 day pilot plan to embed SLOs into governance. The episode keeps trade-offs explicit and non-technical so leaders can commission measurable reliability commitments. CTA: download the Executive SLO Template and 30–90 Day Playbook at datascience.show/slo. That’s the difference between models and value.

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