# Community Facilitator Guide

## Session title

GenAIOps for Cloud Solution Architects: From Prompt to Production

## Audience

New CSA starters, early-career cloud architects, community learners, and technical consultants.

## Duration options

| Format | Duration | Shape |
|---|---:|---|
| Lightning talk | 15 minutes | Lifecycle overview and three lessons learned. |
| Lunch and learn | 45 minutes | Lifecycle, reference architecture, use cases, Q&A. |
| Workshop | 90 minutes | Lifecycle, group exercise, evaluation checklist, operating model. |

## Learning outcomes

By the end, attendees should be able to:

1. Explain GenAIOps in plain language.
2. Describe the Build, Evaluate, Deploy, Monitor, Govern, Optimise lifecycle.
3. Identify why evaluation and monitoring are different for GenAI.
4. Explain where an AI gateway helps.
5. Ask better customer discovery questions.

## Suggested agenda: 45 minutes

| Time | Activity |
|---:|---|
| 0-5 | Why GenAI demos are not the same as production services. |
| 5-15 | GenAIOps lifecycle walkthrough. |
| 15-25 | Reference architecture: app, gateway, agent, retrieval, model, safety, telemetry. |
| 25-35 | Use case exercise: choose a pilot and define controls. |
| 35-42 | Common questions and objections. |
| 42-45 | Takeaways and next steps. |

## Group exercise

Ask attendees to pick one use case and answer:

- Who is the user?
- What task are they trying to complete?
- Which data sources are trusted?
- What could go wrong?
- How would you evaluate quality before release?
- What would you monitor after release?
- Who owns the solution in production?

## Safe public framing

Avoid customer-specific examples. Use generic examples such as support knowledge assistants, service desk triage, contact centre summarisation, policy assistants, and engineering runbook assistants.