> ## Documentation Index
> Fetch the complete documentation index at: https://docs.michelangelo.land/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompt Engineering

> Learn how to write effective prompts for Michelangelo

The quality of your prompt directly affects the quality of the generated app. A good prompt gives the AI enough context to produce something useful while leaving room for iteration.

## Anatomy of a Good Prompt

A strong prompt usually includes:

* **Goal** — what the app should do.
* **Screens** — what pages or views the app needs.
* **Data** — what information the app shows or collects.
* **Behavior** — how the app should respond to user actions.
* **Style** — any visual direction, such as colors or layout preferences.

## Examples

**Weak:**

> "Make a fitness app."

**Strong:**

> "Create a workout logging app with two tabs: a list of past workouts and a form to add a new workout. Each workout should have a name, duration, and date. Use a dark theme with cards for each workout."

## Tips for Better Results

* **Be concrete** — use specific names, labels, and values.
* **Limit scope** — focus on one or two screens per prompt.
* **Mention data flow** — explain where data comes from and where it goes.
* **Reference existing apps** — "like Strava but for books" can help set expectations.
* **Attach images** — screenshots, sketches, or wireframes guide the layout.

## Iterating with Follow-Up Prompts

You do not need to get everything right in the first prompt. Use follow-ups to refine:

* "Add a settings screen with a toggle for dark mode."
* "Make the list items larger and add an icon."
* "Fetch the weather from the Open-Meteo API instead of using mock data."
* "Fix the error that appears when I tap the submit button."

<Info>
  Michelangelo applies follow-up prompts as edits rather than starting from scratch, so you can build incrementally.
</Info>

## Handling Errors

If the sandbox shows a runtime error, you can:

1. Read the error message in the sandbox.
2. Send a follow-up prompt like: `Fix this error: {error message}`.
3. Let Michelangelo auto-fix when available.

## Common Mistakes

* **Too vague** — the AI makes assumptions you may not like.
* **Too large** — asking for 10 features at once often leads to partial results.
* **Ignoring the sandbox** — always test the generated app before the next prompt.

## Next Steps

<CardGroup cols="2">
  <Card title="Vibe Coding Basics" icon="pen-nib" color="#7c7c7c" href="/v2/how-to-build/vibe-coding-basics">
    Learn the fundamentals of Vibe Coding.
  </Card>

  <Card title="Project Lifecycle" icon="arrows-rotate" color="#7c7c7c" href="/v2/how-to-build/project-lifecycle">
    Understand the project lifecycle.
  </Card>
</CardGroup>