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Playbooks

How we do it, written down.

Practical guides from our enterprise work on Google Cloud. Free to download: tell us where to send them.

  1. Playbook 1 · PDFComing soon

    Agents in production

    How we take an AI agent from prototype to production on Google Cloud, and keep it reliable afterwards.

    • Evaluation sets and release gates
    • Guardrails and human review
    • Deployment, monitoring and SLOs
    • Runbooks and on-call
  2. Playbook 2 · PDFComing soon

    Borderless lakehouse implementation

    Planning and running a move to open Apache Iceberg tables with one runtime catalog, so every engine works on one copy of your data.

    • Assessing your current data estate
    • Iceberg table and catalog design
    • Governance across engines
    • Migration in phases
  3. Playbook 3 · PDFComing soon

    AI cost control

    Keeping agent costs predictable at enterprise scale, from prompt design to reporting cost per task.

    • Prompt caching
    • Model routing
    • Cost-per-task reporting in BigQuery
    • Budgets and alerts

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Playbooks