AB-410 practice test

Designing solutions with AI-enabled tooling: analysing requirements into components, evaluating the built-in agents worth including, recommending extensibility and environment types, and applying a solution and lifecycle strategy. Then data models: creating and editing tables in the data workspace, standard and custom tables, table properties, columns, relationships, prompt columns and row summaries, public views, main forms and the security around them.

Model-driven apps: forms, views, generative pages described in natural language, composing the app, access to forms, views and the app itself, and charts and dashboards. Canvas apps: building from data, designing for accessibility, performance, responsiveness and usability, automating processes from the app, reusable components with named formulas, user-defined functions and component libraries, variables and collections, error handling, testing with Monitor, and creating a Copilot Studio agent from an app.

Cloud flows: recommending triggers and connectors, approvals, actions, control flow with conditions and loops, and testing and troubleshooting what runs. Prompts and models in the AI hub: building from a template or from blank, consuming a prompt in apps and in flows, adding knowledge, customising settings including the model, adding inputs, and consuming prebuilt models from both surfaces. Then business and process logic: business rules, business process flows, calculated, rollup and formula columns, and judging which of them a requirement actually calls for.