Decide With Run State In Mind
When you shortlist platforms, evaluate more than demos. Can your team diagnose failures, upgrade dependencies, and extend integrations without waiting on vendors?
Run lightweight operability drills during pilots: deploy to staging, rotate secrets, simulate a partial outage. Document what broke and who owned the fix.
- Score each option on observability, automation hooks, and documentation depth.
- Ask vendors how customer teams typically staff operations after launch.
- Weight TCO by ongoing effort, not just license cost.
Invest In Skills Before Go-Live
Identify the critical skills to keep the stack healthy—data modeling, prompt engineering, SRE, access governance. Align each to named owners and budget for training or hiring early.
Shadow partners or internal champions as they implement the first lanes. Turn those learnings into playbooks and internal workshops so the knowledge sticks.
- Budget 10-15% of implementation effort for enablement and knowledge transfer.
- Set measurable competency goals (e.g., two engineers certified on Azure OpenAI, one analyst trained on pgvector maintenance).
- Create office hours where the build team pairs with future owners weekly.
Design For Shared Ownership
Split responsibilities explicitly: data platform, integration layer, AI experience, governance. Each gets a backlog, on-call expectations, and metrics reported to leadership.
Embed operational artifacts—runbooks, dashboards, guardrails—directly into the product. Copilots should cite those artifacts so frontline teams can support themselves.
- Stand up a monthly operations review covering incidents, capacity, and roadmap impact.
- Instrument telemetry that alerts both engineering and business owners when SLAs drift.
- Feed operational insights back into procurement so future platform decisions consider support load.