Planor

Overview

Planor transforms a single sentence idea into a structured, versioned development roadmap optimized for AI coding assistants. Instead of building feature by feature, it understands your full project, defines features automatically, and breaks work into scoped versions from scaffolding to MVP launch. Each task includes acceptance criteria, dependencies, and step-by-step guidance that integrates with Cursor, Copilot, Windsurf, and other AI editors.

Key Features

Version-Based Planning: Automatically generates version outlines from v0.1 Project Scaffolding to v1.0 MVP Polish & Launch, each scoped and focused on specific milestones.
Self-Contained Tasks: Creates tasks with title, priority, dependencies, acceptance criteria, and step-by-step guidance for end-to-end implementation.
Aftermath Reporting: Tracks files changed, verification steps, and deviations after each task to update future work with awareness of your actual codebase.
GitHub Integration: Creates repos from production-ready templates with pre-configured analytics and monetization, so you start ready to scale.
AI Editor Compatibility: Generates clean rulebooks and scoped prompts that work directly with Cursor, Copilot, Antigravity, and Windsurf.
Adaptive Planning: Uses aftermath reports to refine upcoming tasks based on what was actually built, not just the original plan.
Production-Ready Templates: Starts projects from configured templates instead of blank files, reducing setup time.
One-Sentence Input: Accepts simple ideas like "mental health app for Gen Z" without requiring detailed specs or PRDs.

Pros

Streamlines AI Development: Provides structured planning that AI assistants can follow, reducing back-and-forth clarification.
Version-Based Approach: Breaking projects into v0.1, v0.2, v1.0 makes progress measurable and development more manageable.
Codebase Awareness: Aftermath reporting keeps plans aligned with actual implementation, preventing drift between plan and reality.
Production Templates: Starting from configured templates saves hours of setup and includes best practices from the start.
Works With Your Tools: Integrates with popular AI editors instead of forcing you to switch workflows.

Cons

Pricing Unknown: No public pricing information available, making it hard to evaluate cost-effectiveness.
AI Editor Dependency: Requires using compatible AI code assistants like Cursor or Copilot to get full value.
Learning Curve: The aftermath reporting workflow adds process overhead that may slow down experienced developers.

Use Cases

Solo Developer MVP Building: A developer wants to build a todo app for elderly users. Planor asks key questions, defines scope, and splits the project into versions and tasks automatically, allowing the developer to execute with their AI assistant without constant replanning.
Authentication System Setup: Building a mental health app requires secure user accounts. Planor creates tasks for setting up NextAuth.js v5 with PostgreSQL, including signup UI, API endpoints, input validation, and error handling across multiple versions.
Startup Prototyping: A founder has an idea for "a mental health app for Gen Z with daily mood tracking and AI-based emotion analysis" but no technical spec. Planor generates the full version outline from project scaffolding to launch-ready MVP with structured tasks.
Project Recovery: An AI-assisted project has drifted from the original plan. Planor uses aftermath reports to understand what was actually built, then refines future tasks to align with the real codebase state.
GitHub Project Initialization: Starting a new SaaS project that needs analytics and monetization wired up. Planor creates the repo from production templates with configuration already in place, saving days of boilerplate setup.
Team Alignment: Multiple developers using AI assistants need consistent context. Planor generates shared rulebooks and scoped prompts that ensure everyone works from the same structured plan.

Frequently Asked Questions

What AI code editors does Planor work with?

Planor works with Cursor, Copilot, Antigravity, and Windsurf. It generates clean rulebooks and scoped prompts that plug directly into these AI coding environments without requiring you to change your workflow.

How does the aftermath reporting system work?

After completing each task, your AI code editor creates an aftermath.md file that logs files changed, verification steps, and any deviations from the plan. Planor uses these reports to update future tasks with awareness of your actual codebase, keeping plans aligned with reality.

Do I need to write a detailed project specification?

No. Planor accepts simple one‑sentence ideas and then asks targeted questions to define scope, automatically splitting the project into versions and tasks without requiring a full PRD.

What does the version outline include?

Planor generates versions from v0.1 (Project Scaffolding) through v1.0 (MVP Polish & Launch). Each version is scoped, named, and focused on specific milestones. You get self-contained tasks for each version with priorities, dependencies, acceptance criteria, and implementation guidance.

How does GitHub integration work?

Planor creates repositories from production-grade templates, sets up configuration, and wires up analytics and monetization. Instead of starting from a blank project, you begin with a configured codebase ready to scale.

Can Planor handle changes during development?

Yes. The aftermath reporting system tracks what was actually built versus what was planned. Planor refines upcoming tasks based on these reports, adapting to deviations and keeping the plan relevant to your evolving codebase.

Is Planor a replacement for AI code editors?

No. Planor is built to fit your existing workflow, not replace it. It generates structured plans and prompts that make AI code editors more effective, but you still use your preferred AI assistant to write the actual code.

What kind of projects is Planor best for?

Planor works well for building MVPs, SaaS applications, and projects where you want structured planning without writing detailed specifications. It's particularly useful for solo developers and small teams using AI assistants to build production apps.