Wappler documentation
AI Manager
Start with Wappler's project-wide AI agent for orchestrating full-stack work across pages, data, backend logic, validation, and agentic execution.
Start here when the task spans project setup, pages, App Connect, Server Connect, Database Manager, migrations, Problems panel fixes, or any cross-file outcome. The AI Manager is Wappler's project-wide AI agent: it is not bound to the HTML Editor, it can reason across the whole project, load the knowledge and context it needs on demand, work with the right files, follow project rules, make plans, track progress, coordinate validation, and execute broader agentic workflows from one central surface.
Start here
AI Manager OverviewPractical AI Manager orientation to its task surface, history flow, toolbars, model/account controls, and prompt entry workflow.Connect an AI ProviderWappler Options setup for AI providers, GitHub Copilot as the preferred default, and request-based versus token-based usage in AI Manager.Choosing Models in AI ManagerBest-practice AI Manager model choice for design, coding, and orchestration, with preferred Claude and GPT defaults.From Prompt to First Full-Stack FeatureBuild a concrete first feature with the AI Manager: a public feedback page, backend save flow, and review checkpoints across the stack.Agentic Generation, Context, and VerificationAdvanced AI Manager workflows for larger tasks with bounded prompts, on-demand knowledge, context control, recovery, and verification.
Build across Wappler
AI for Pages, Design, and UIUse the AI Manager to shape real pages and UI in Wappler with concrete prompts, reusable structure, and editor-based review.AI for Data, Backend, and Business LogicUse the AI Manager for real data contracts, Server Connect flows, validation, and form behavior instead of backend theory alone.WorkflowsA guided starting point for Workflows: Server Connect Actions (server-side) and App Connect Flows (client-side).
Prompt and guide the agent
Prompting, Rules, and ExecutionLearn how to brief the AI Manager well: stronger prompts, design requests, reusable rules, standards, plans, and execution discipline.Best Prompt GuidelinesPractical AI Manager prompt patterns: write stronger prompts, add the right context, break work into reviewable slices, and guide follow-up passes clearly.Design Prompts for Better UIPractical design-prompt patterns for the AI Manager: brief real UI goals, describe hierarchy and states, and review the outcome in Wappler.Rules, Standards, and GuardrailsPractical ways to write reusable AI Manager rules, show them in project files, and turn them into concrete execution constraints.Plans, Task Execution, and VerificationPlan larger AI Manager tasks with concrete slices, checkpoints, validation, and recovery steps instead of one opaque execution jump.