Data readiness
Inventory data sources, purpose, permissions, freshness, quality, lineage and retention before model or retrieval design.
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Design for the full system: source permissions, model and retrieval behavior, tool interfaces, approval boundaries, observability, cost and operating responsibility. No model or framework alone establishes production readiness.
A GCC is a long-term operating capability. Choices about responsibilities, people, workplace, technology and governance should reinforce each other from the beginning.
AI, data, product, security and business-process owners
Production AI combines probabilistic outputs with enterprise data and tools. Reliability depends on data permissions, retrieval quality, versioned prompts and models, evaluations, observability, escalation and change control—not model selection alone.
Inventory data sources, purpose, permissions, freshness, quality, lineage and retention before model or retrieval design.
Select hosted or self-managed models, RAG or fine-tuning only after defining task needs, latency, cost, data boundary and fallback.
Use narrow tool schemas, least-privilege identities, policy checks, bounded actions, rate limits and human approval for high-impact steps.
Version test sets and configurations; trace retrieval, model calls and tool actions; monitor quality, safety, cost and drift.
Define representative tasks, accepted outcomes and human-review costs.
Test prompt injection, data disclosure, unsafe tool use, untrusted output and resource exhaustion.
Use approved data and tools, stage exposure, log decisions and keep a human fallback.
Gate model and prompt changes, investigate failures, review access and retain a rapid disable path.
A hypothetical agent classifies a purchase request, retrieves approved policy and drafts a recommendation. It cannot select suppliers or approve spend. It records cited policy passages, requests missing fields and routes ambiguous or above-threshold cases to a named reviewer.
Measures depend on the workflow, starting baseline and client-approved service expectations.
Design for the full system: source permissions, model and retrieval behavior, tool interfaces, approval boundaries, observability, cost and operating responsibility. No model or framework alone establishes production readiness. A useful next step is to document the decision owners, assumptions and information needed to validate the option. A use-case assessment tied to a real workflow
Design for the full system: source permissions, model and retrieval behavior, tool interfaces, approval boundaries, observability, cost and operating responsibility. No model or framework alone establishes production readiness. A useful next step is to document the decision owners, assumptions and information needed to validate the option. A use-case assessment tied to a real workflow
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