Wappler documentation
Advanced AI Workflows
Advanced Wappler AI workflows for agentic generation, context discipline, validation, and cross-stack iteration.
This route is for users who want Wappler AI to handle bigger cross-stack tasks without becoming a black box. Focus on bounded prompts, on-demand knowledge, token discipline, validation, and recovery.
Control larger tasks
Agentic Generation, Context, and VerificationAdvanced AI Manager workflows for larger tasks with bounded prompts, on-demand knowledge, context control, recovery, and verification.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.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.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.
Position the tool correctly
Bring an AI-assisted code project into WapplerAssess an existing code project, choose what to reuse and verify one working feature before expanding the migration.Prompting, Rules, and ExecutionLearn how to brief the AI Manager well: stronger prompts, design requests, reusable rules, standards, plans, and execution discipline.