The lifecycle
Build
Prompts, agents, retrieval, orchestration and tools.
Evaluate
Groundedness, relevance, coherence, safety and task success.
Deploy
Managed endpoints, CI/CD, gateway and release controls.
Monitor
System health, answer health, token use, safety events and feedback.
Govern
Identity, RBAC, audit, responsible AI and project isolation.
Optimise
Cost, model choice, context design, caching and continuous improvement.
What you will learn
Architecture thinking
How to frame a production GenAI pattern with app, gateway, orchestrator, retrieval, model, safety and telemetry.
Customer conversations
How to ask better discovery questions about value, data, quality, risk, ownership and cost.
Evaluation and monitoring
Why production AI needs quality gates and observability for both system behaviour and answer behaviour.
Governance and FinOps
How identity, access, audit, quotas and model selection help teams scale safely.
Downloads
Video concept
Working title: GenAIOps for Cloud Solution Architects: From Prompt to Production
Format: 8-10 minute public explainer using generated diagrams, public-safe examples and an AI-generated version of your own voice.
Disclosure: Narration uses an AI-generated version of my own voice, created with my consent.