GitHub Spec Kit: Can It FINALLY Fix “Vibe Coding”?

Key Concepts

• Specs-driven development: A methodology focusing on detailed specifications before coding.
• Coding agents: AI tools like Cursor, Codec, Claude, Gemini, Copilot used for code generation.
• Product Requirements Document (PRD): A comprehensive document detailing the features, functionality, and purpose of a product.
• Custom Commands: Specific instructions or actions that can be executed within a coding environment.
• Test-Driven Development (TDD): A software development process where tests are written before the code.
• Specification Kit: A framework provided by GitHub for implementing specs-driven development.

1. The Problem: Lack of Specifications in AI Coding

• The main problem with AI-assisted coding is the lack of detailed specifications, not the coding agents' capabilities.
• Coding agents make too many assumptions based on simple text prompts, leading to errors.
• Solution: Provide clear feature descriptions, detailed technical plans (including tech stack), and a product requirements document (PRD).

2. Specs-Driven Development and GitHub's Spec Kit

• Specs-driven development involves creating detailed specifications before coding.
• Examples: Kirro from AWS (expensive), GitHub's Spec Kit (integrates with existing coding agents).
• The video focuses on GitHub's Spec Kit, its setup, capabilities, and limitations.

3. Four-Step Process Using the Specification Kit

• Step 1: Specify: Describe what to build (what and why), focusing on functional and non-functional requirements.
• Step 2: Plan: Define technical details, architecture, and tech stack. The agent assists in refining the plan. Use /plan command.
• Step 3: Task: Create manageable and actionable tasks for the agent to perform sequentially or in parallel. Use /task command.
• Step 4: Test: Implement using test-driven development.

4. Setting Up and Using the Spec Kit

• No installation is required.
• Copy and run a command in the IDE or coding agent to download the template.
• Example command: npx degit github/github/specs-kit#main image-nano-banana (project name is customizable).
• The command creates a project folder with:
  • .cloud folder: Contains plan, specify, and tasks custom commands.
  • memory: Used for context management.
  • scripts: Scripts run by the agent at each step.
  • templates: Templates for planning, specification, and task creation.
• The /specify command is used to define the feature to be implemented.

5. Example Project: Image Generation with Nano Banana

• The presenter describes an example project: "Using nano banana to create images of a person in different styles based on an uploaded image."
• A detailed product requirement document (PRD) was created using GPT-5.
• The functional and non-functional requirements from the PRD are used in the specification stage.
• The agent updates files (e.g., specs file) based on the initial request.
• The agent may ask for clarifications, tagged as "needs clarification."

6. Planning and Task Creation

• The planning stage uses technical details from the PRD, including API implementation.
• The agent uses web search to collect information for implementation.
• The agent creates a design and updates markdown files to document the process.
• The agent generates individual tasks (e.g., 45 tasks in one example).
• The /task command is used to execute the tasks sequentially or in parallel.

7. Test-Driven Development and Task Execution

• The agent focuses on test-driven development.
• Tasks are numbered sequentially (001, 002, etc.).
• Task complexity varies, affecting execution time (e.g., one set of tasks took 1 hour 18 minutes).
• In one example, the process resulted in 59 tasks, including setup, testing, and integration testing.

8. Strengths and Weaknesses

• Strengths:
  • Thoroughness: The agent is very detailed in its design and implementation.
  • Learning opportunity: Reading the agent's design, specs, and implementation tasks can be educational.
  • Documentation: The agent updates cloud.md like a human programmer.
  • Support for multiple coding agents (Claude Code, Gemini CLI, GitHub Copilot).
• Weaknesses:
  • Not fully polished (first iteration).
  • Adds implementation time, especially for simple projects.
  • Can be slow (e.g., over 2 hours for one project).
  • The presenter hasn't figured out an easy way to implement a feature in an existing codebase.

9. Conclusion

• GitHub's Spec Kit is worth checking out for those using coding agents.
• It adds overhead but can be helpful for complex projects.
• The agent's thoroughness and documentation are valuable.
• The tool is still in its early stages and has limitations.
• The presenter encourages viewers to try the tool and share their experiences.