Tutorials

Plan Mode: How to Get Better AI-Generated Code in GenMB

Toggle Plan Mode to have the AI think through your request before generating code. Get structured breakdowns and higher quality output.

Ambuj Agrawal

Ambuj Agrawal

Founder & CEO

5 min read

What Is Plan Mode?

Plan Mode is a toggle in GenMB that changes how the AI approaches code generation. Instead of jumping straight into writing code, the AI first creates a structured plan — a step-by-step breakdown of what it will build, how the components connect, and what technical decisions it will make. You review the plan, optionally edit it, and then the AI executes it with full awareness of the big picture.

Think of it as the difference between a builder who starts laying bricks immediately versus one who reviews the blueprints first. Both get the job done, but the one with a plan produces more coherent, well-structured results — especially for complex projects.

How Plan Mode Works

When you enable Plan Mode and submit a prompt, the generation process adds an extra stage:

Step 1: Analysis

The AI reads your prompt and analyzes the scope of work. It identifies the major components, features, data flow, and technical requirements.

Step 2: Plan Generation

Instead of generating code, the AI produces a structured plan. This plan includes:

  • Feature breakdown: Each feature listed with its components
  • File structure: Which files will be created and what each one does
  • Data flow: How state moves between components
  • Technical decisions: Framework patterns, library choices, state management approach
  • Build order: The sequence in which features will be implemented

Step 3: Review and Edit

The plan appears in the chat panel for your review. You can:

  • Approve it as-is and proceed to code generation
  • Request changes ("Move the auth flow to happen before dashboard loading")
  • Add missing requirements ("Also include a settings page")
  • Remove features ("Skip the analytics section for now")

Step 4: Execution

Once you approve the plan, the AI generates code following the exact blueprint it laid out. Because it has a clear roadmap, the resulting code tends to have better structure, more consistent patterns, and fewer integration issues between components.

When to Use Plan Mode

Plan Mode adds time to the generation process because of the planning stage. Here is when that tradeoff pays off:

Complex Multi-Feature Apps

If your prompt includes more than three distinct features, Plan Mode helps the AI organize them coherently. Without a plan, complex apps sometimes have duplicated state, inconsistent patterns, or features that do not integrate well.

Apps with Data Dependencies

When features depend on each other — a dashboard that reads from the same data a form writes to, or a shopping cart that needs to sync with inventory — Plan Mode maps out these dependencies before code is written.

Projects Where Architecture Matters

If you care about code organization, separation of concerns, or specific component patterns, Plan Mode lets you review and influence the architecture before any code is generated.

When You Are Unsure About Scope

If your idea is broad and you want to see how the AI interprets it before committing to code generation, Plan Mode gives you a preview of the approach. You can refine the direction without waiting for a full generation cycle.

Plan Mode vs Direct Generation

Here is a practical comparison:

Direct Generation (Plan Mode Off)

  • AI generates code immediately from your prompt
  • Faster total time for simple apps
  • Best for single-feature apps, quick prototypes, and straightforward requests
  • The AI still plans internally but you do not see or influence it

Plan Mode (On)

  • AI shows its plan before generating code
  • You can review, edit, and approve the approach
  • Better results for multi-feature, architecturally complex apps
  • Slightly longer total time due to the planning stage

A good rule of thumb: if your prompt is under 3 sentences and describes a single feature, direct generation is fine. If your prompt is a paragraph or more with multiple features, turn on Plan Mode.

Reviewing and Editing Plans

The plan appears as a structured message in the chat panel. Here is an example of what a plan looks like:

`

Plan for: Project Management Dashboard

  1. Layout & Navigation
  • Sidebar with navigation links (Dashboard, Projects, Tasks, Team)
  • Top bar with search and user profile
  • Responsive: sidebar collapses to hamburger on mobile
  1. Dashboard View
  • KPI cards: total projects, active tasks, team members, completion rate
  • Recent activity feed
  • Upcoming deadlines chart (Chart.js bar chart)
  1. Projects List
  • Table view with columns: name, status, progress, due date
  • Create project modal with form
  • Filter by status (active, completed, on hold)
  1. Task Board
  • Kanban columns: To Do, In Progress, Review, Done
  • Drag and drop between columns
  • Task cards with assignee avatar, priority badge, due date
  1. State Management
  • React useState for local component state
  • Shared context for projects and tasks data
  • localStorage for persistence

Files: index.html, styles.css, app.jsx, components/Sidebar.jsx,

components/Dashboard.jsx, components/ProjectList.jsx,

components/TaskBoard.jsx, components/KPICard.jsx

`

You can respond with edits like:

"Add a team members page to section 4 and use a chart for the KPI cards instead of simple numbers"

The AI updates the plan and shows it again for your approval.

Examples of Plan Mode Output

Simple App (Plan Mode Optional)

Prompt: "Create a tip calculator"

Plan Mode would show a brief plan with a single component and basic state. For prompts this simple, direct generation works just as well.

Complex App (Plan Mode Recommended)

Prompt: "Create an employee directory with department filtering, org chart view, profile pages, and a search that works across name, title, and department"

Plan Mode maps out the data model, four distinct views, shared search state, and the component hierarchy — catching potential issues like where the org chart data comes from and how filtering interacts with the tree view.

Best Practices

Be Detailed in Your Initial Prompt

The more detail you provide, the better the plan. Include feature lists, data relationships, and UI preferences so the AI has enough context to create a comprehensive blueprint.

Read the Plan Before Approving

Do not skip the review step. The plan reveals the AI's interpretation of your request. If it misunderstood something, catching it at the plan stage saves a full regeneration cycle.

Use Plan Mode for Refinements Too

Plan Mode is not just for initial generation. When you are making significant changes to an existing app — adding a new page, restructuring navigation, or introducing a new data flow — enable Plan Mode to see how the AI plans to integrate the changes.

Summary

Plan Mode gives you visibility and control over the AI's approach before code is written. By reviewing a structured breakdown of features, file structure, data flow, and build order, you can catch misunderstandings early, influence architecture decisions, and get higher quality output for complex applications. Toggle it on for multi-feature apps, review the plan carefully, and use the edit step to steer the AI toward exactly what you need.

Frequently Asked Questions

Does Plan Mode make code generation slower?
Plan Mode adds a planning stage before code generation, so the total time is slightly longer. However, the resulting code is typically higher quality with fewer integration issues, which saves time on refinements.
Can I edit the plan before the AI generates code?
Yes. After the AI shows its plan, you can request changes, add missing features, remove sections, or restructure the approach. The AI updates the plan and waits for your approval before generating code.
When should I use Plan Mode vs direct generation?
Use direct generation for simple, single-feature apps and quick prototypes. Use Plan Mode for multi-feature applications, projects with data dependencies, and any prompt longer than a few sentences where architecture decisions matter.
Ambuj Agrawal

Ambuj Agrawal

Founder & CEO

Award-winning AI author and speaker. Building the future of app development at GenMB.

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