A practical guide to applying prompt engineering discipline when building production apps with Google Gemini. Covers writing prompt specs before coding, using typed template variables, enforcing JSON schema outputs, building eval sets (30–50 examples), prompt chaining for multi-step workflows, tracing prompt versions in production, handling prompt injection, and releasing prompt changes with the same rigor as code deployments. Includes before/after prompt revision examples and a pre-ship checklist.
Table of contents
Start with the app behavior, not the modelUse Google AI Studio to prototype the prompt shapeTurn the prompt into a template with typed variablesUse structured outputs for app integrationsImprove prompts with before and after revisionsBuild evals before you shipConnect prompt engineering to context engineeringUse prompt chaining for multi-step app workflowsTrace prompt versions and model responses in productionChoose model settings with the app in mindHandle prompt injection and unsafe user inputRelease prompts like application changesCommon mistakes when applying Google prompt engineering to appsA practical implementation checklist640 Impressions