The practice of crafting effective natural language descriptions to get better output from AI systems. In GenMB, good prompts specify the app type, key features, data structure, and user flow. More specific prompts produce better applications. Plan Mode and Knowledge Files complement prompt engineering.
The process of using large language models (LLMs) to produce source code from natural language prompts. Modern AI code generators like GenMB produce complete, multi-file applications rather than just snippets, using pipeline stages for validation, generation, error healing, and enhancement.
Persistent project context documents that carry across chat sessions in GenMB. Users upload design specifications, API references, product requirements, or coding conventions. The AI references these files during every generation, ensuring consistent output that respects project-specific constraints.
A GenMB feature where the AI creates a structured breakdown of what it will build before generating code. Plan Mode produces higher quality output for complex, multi-feature applications by thinking through components, data models, UI layout, and technical trade-offs first.
Put these concepts into practice. Describe your app idea and let GenMB generate the code.
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