Writing better prompts

Anatomy of a good prompt

A Myndlab prompt is not a Google search query — it's a brief product specification. The AI on the other end is capable of building complex, multi-file applications, but it needs the same information a good developer brief would contain: what the app does, who uses it, what data it manages, and any constraints on technology.

You don't need to write a ten-page spec. Four or five sentences that cover the key dimensions consistently outperform either a single vague sentence or an overly detailed implementation plan. The sweet spot is a prompt that describes outcomes, not mechanics.

What to always include

Four dimensions cover the vast majority of what Myndlab needs to make good decisions. When any one of these is missing, the AI has to guess — and its guess may not match your intent.

Weak vs strong examples

The difference between a weak and strong prompt is usually specificity, not length. Here is a side-by-side comparison for the same app idea:

# Weak prompt — vague, forces guessing
Build me a task manager app.

# Strong prompt — concrete, covers all four dimensions
Build a team task manager for small marketing agencies.

Users: two roles — Agency Admin and Team Member.
- Admins can create projects, assign tasks, and view all activity.
- Team Members can view their assigned tasks, update status, and
  leave comments.

Data: Projects contain Tasks. Tasks have a title, description,
due date, priority (low/medium/high), status (todo/in-progress/done),
and an assignee (Team Member).

Stack: React frontend, FastAPI backend, PostgreSQL database.

The main view is a Kanban board grouped by status. Include email
notifications when a task is assigned or overdue.

The strong prompt is still only ten lines. But it eliminates every major ambiguity: roles, permissions, data model, stack, primary UI paradigm, and key features. Myndlab will generate a more accurate spec, spend fewer credits on corrections, and produce code that needs fewer follow-up edits.

Iteration prompts

Once your app exists, you'll spend most of your time sending iteration prompts — requests to change, add, or remove something specific. Iteration prompts should be even more precise than initial prompts, because Myndlab needs to identify exactly which part of the existing codebase to touch.

# Good iteration prompt
On the Task detail page, add a Comments section below the task
description.

- Users can type a comment (up to 500 characters) and submit it.
- Comments display the author's name, avatar, and a relative
  timestamp ("2 hours ago").
- Comments load on page load; no infinite scroll needed yet.
- Only the comment author or an Admin can delete a comment.

What NOT to include

Over-specifying implementation details is the most common mistake experienced developers make when switching to AI-assisted building. When you tell Myndlab how to implement something rather than what to achieve, you constrain the AI's judgment without necessarily improving the outcome — and often worsen it.

Using voice to brainstorm first

Voice mode (⌘ ⇧ P) is one of the fastest ways to arrive at a high-quality written prompt. Speak naturally for 60–90 seconds about what you want to build — what problem it solves, who uses it, what the most important feature is. Myndlab transcribes and structures your speech into a draft prompt, which you can then review and tighten before hitting Build.

Voice brainstorming is particularly useful at the start of a project, when you have a clear mental picture but haven't yet translated it into structured text. Speaking forces you to say things out loud that you might skip when typing, and Myndlab's voice-to-prompt pipeline is tuned to capture those details.