GitHub has launched GitHub SpecKit, an open-source toolkit that helps developers write code with AI while keeping it aligned with project requirements.
GitHub SpecKit uses spec-driven development, which means developers define detailed project specifications before generating code. This approach reduces errors and misaligned AI outputs.
How does GitHub SpecKit work?
GitHub SpecKit organizes work into four phases:
- Specify – Write down what the project needs to do. For example, if you are building a Pokedex team builder, you would list features like filtering Pokémon by type, optimizing team combinations, and handling user preferences.
- Plan – Decide on the technical tools, architecture, and technology stack needed to meet the specifications.
- Tasks – Break the plan into smaller steps. For the Pokedex, this could include designing the user interface, implementing the filtering algorithm, and testing each function.
- Implement – Use AI coding tools like GitHub Copilot, Claude Code, or Gemini CLI to write code, then refine it to match the specifications.
Following these steps gives developers a clear path from idea to finished code. It also makes it easier to check if AI outputs meet the project’s goals.
Managing projects and AI workflows with GitHub SpecKit
GitHub SpecKit includes a command-line interface (CLI) and comes with pre-made templates and prompts to keep documentation consistent.
Developers can generate project specs, track tasks, and integrate AI tools—all from the terminal. This setup reduces errors and keeps the workflow organized, making AI-assisted coding less unpredictable.
Building real projects step by step
Take the Pokedex team builder example:
- Specify: Define every feature the tool should have.
- Plan: Lay out the tech stack and how the system will operate.
- Tasks: Assign coding, UI design, and testing duties.
- Implement: AI generates code, and developers tweak it to match the plan.
By following these steps, developers can produce working, documented applications faster and with fewer mistakes.
Standing out from other tools
Tools like Amazon’s Kira also use spec-driven development, but GitHub SpecKit supports more AI coding agents and offers more templates and workflow tools. Developers can integrate it with the AI tools they already use without being forced into a single ecosystem.
GitHub SpecKit is open-source and free for all skill levels. By combining clear specifications, structured steps, and AI coding, it turns AI from a gamble into a reliable assistant. Developers get code that works, documentation that’s consistent, and a workflow that’s easier to manage.
