Writing Effective Prompts

The quality of your project description directly determines the quality of everything VibeMap generates. A well-crafted prompt produces focused personas, relevant features, and realistic technical specifications. A vague prompt leads to generic output that needs heavy editing.

What Makes a Good Prompt

Be Specific About Target Users

Tell the AI who will use the product. The more specific you are, the more relevant the personas and user stories become.

• Vague: "People who want to manage tasks"
• Specific: "Freelance designers managing client projects, deliverables, and invoicing"

Describe the Features You Want

List the key things users should be able to do. You don't need to describe every screen or interaction -- focus on capabilities and outcomes.

• Vague: "Users can track their progress"
• Specific: "Users can set weekly goals, log completed tasks against those goals, and view a dashboard showing progress trends over the past 30 days"

Mention Your Tech Stack (Optional)

If you have preferences for technology, include them. This improves the schema, file structure, and component suggestions.

• "Built with Next.js and Supabase"
• "React Native mobile app with a Node.js backend"
• "WordPress plugin with a custom admin panel"

Define the Scope

Help the AI understand what's in and out of scope for this version of the product.

• "MVP focused on core task management -- no team features in v1"
• "Full-featured platform including admin dashboard, reporting, and integrations"

Include Business Context

A sentence or two about the market or business model helps the AI make better decisions.

• "Competing with Notion and Linear for small development teams"
• "Subscription-based SaaS targeting agencies with 5-20 employees"

The Anatomy of a Great Prompt

A strong prompt typically includes these elements in 2-4 paragraphs:

1. What it is -- One sentence describing the product
2. Who it's for -- The target users and their context
3. Core features -- 3-8 key capabilities
4. Technical context -- Stack, platform, or constraints
5. Scope boundaries -- What's included and excluded

Example Prompts

Good Prompt

A recipe sharing platform for home cooks who want to discover, save, and share recipes with their friends and family. Users can create detailed recipe pages with ingredients, step-by-step instructions, photos, and cooking times. They can follow other cooks, save recipes to personal collections, and leave reviews with star ratings.

The app should include a search system with filters for dietary restrictions (vegan, gluten-free, etc.), cuisine type, cooking time, and difficulty level. Users get a personalized feed based on who they follow and what cuisines they've shown interest in.

Built with Next.js and PostgreSQL. MVP scope -- no meal planning, grocery lists, or video content in v1.

Why it works: Specific users, clear features, defined tech stack, and explicit scope boundaries.

Bad Prompt

A cooking app where people can share recipes and find new ones to try.

Why it fails: No detail about users, features, tech, or scope. The AI has to guess at everything, producing generic results.

Good Prompt

An internal tool for a property management company (50-200 units) to track maintenance requests from tenants. Tenants submit requests through a simple form describing the issue and attaching photos. Property managers see a dashboard of all open requests, can assign them to maintenance staff, set priority levels, and track resolution.

Maintenance staff get a mobile-friendly view of their assigned tasks with directions to the property. Managers get weekly reports on response times, resolution rates, and recurring issues by property.

React frontend with a Node.js API. PostgreSQL database. Must integrate with Twilio for SMS notifications to tenants when their request status changes.

Why it works: Clear user roles (tenant, manager, staff), specific workflows, defined integrations, and business context.

Bad Prompt

Build a maintenance tracker for property managers with notifications and reporting.

Why it fails: No detail about user types, workflows, or what "notifications" and "reporting" actually mean.

Common Mistakes to Avoid

• Too short -- One-sentence prompts force the AI to make too many assumptions
• Too abstract -- Describing goals without concrete features ("improve user engagement")
• Feature soup -- Listing 30 features without context or prioritization
• Copied marketing copy -- Promotional language doesn't help the AI understand what to build
• Assuming context -- The AI doesn't know your industry jargon -- spell things out

Iterating on Your Prompt

You don't have to get it perfect on the first try:

• Review the summary -- If the AI misunderstood your intent, your prompt likely needs more detail in that area
• Create a new project -- If the overall direction is wrong, write a revised prompt and start fresh
• Use the agent -- Ask the conversational agent to help you refine specific aspects after initial generation
• Add detail incrementally -- Start with a solid base prompt, then use the agent to add features or personas you didn't initially include

Prompt Length Guidelines

The sweet spot is 2-4 focused paragraphs that cover what the product does, who it's for, its key features, and any technical constraints.