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Project Setup

Setting up a development project effectively using AI tools and techniques ensures smooth collaboration, high productivity, and adherence to best practices. Below is a detailed guide for initializing your project:

This guide outlines how to set up a development project using AI tools and techniques. A proper setup ensures: - smooth collaboration - high productivity - adherence to best practices

Initial Setup

  1. Choose Project Platform

    • select hosting platform (Azure DevOps, GitHub, GitLab, Bitbucket)
    • agree on Git branching strategy
    • document collaboration guidelines

  2. Configure Repository

    • create GitHub repository manually
    • set branch protection rules

Development Environment

  1. Configure AI IDE

    • Cursor
      • Install Cursor from cursor.sh
      • Add required VS Code extensions (Cursor is built on VS Code)
      • Configure workspace settings and preferences
    • Kiro
      • Install Kiro AI IDE
      • Add required VS Code extensions (Kiro is also built on VS Code)
      • Configure workspace settings and preferences
    • GitHub Copilot
      • Install GitHub Copilot plugin to VS Code / JetBrains IDE
      • Requires GitHub Copilot subscription

  2. Configure Privacy Settings - IMPORTANT

    • In ChatGPT -> Settings -> Data Controls -> "Improve the model for everyone" -> toggle off / disable
    • In Cursor -> Settings -> General -> Privacy Mode -> enabled
    • In Kiro -> Configure privacy settings according to your organization's policy
    • In GitHub Copilot -> Settings -> Data retention -> Configure according to your organization's policy

IMPORTANT: Privacy settings must be enabled. This ensures that data is not persisted on providers servers and it is not used for training models.

  1. Add Required Configurations

    For Cursor: - Copy language-specific rules from programming language rules - Copy framework-specific rules from framework rules - Customize IDE rules for team requirements - Update system prompt for LLM base understanding

    For Kiro: - Set up steering guidelines in .kiro/steering/ directory - Configure project-specific steering rules for consistent AI behavior - Add team standards and coding conventions to steering files - Refer to .kiro/steering documentation for detailed configuration options

Using Repository Documentation

Create directory within the repository to store documentation, such as:

  • product requirements
  • architecture documentation
    • development rules and guidelines (reference IDE rules)

Ensure all documentation is:

  • version controlled
  • accessible to the IDE
  • formatted in markdown

(Optinal) Initialize Memory Bank with Tools

Set up the Memory Bank system to enable effective AI assistance throughout the project lifecycle:

  1. Create Memory Bank Structure
  2. install Memory Bank MCP server

  3. initialize core memory bank files using prompt: Initialize memory bank with tools

  4. Configure Memory Bank Files

  5. projectbrief.md - foundation document defining project scope and goals
  6. productContext.md - user experience goals and problem definition
  7. activeContext.md - current work focus and recent changes
  8. systemPatterns.md - architecture and technical decisions
  9. techContext.md - technologies and development setup

  10. progress.md - current status and evolution tracking

  11. Integrate with Development Workflow

  12. ensure memory bank files are version controlled
  13. establish update patterns for maintaining current context
  14. configure AI tools to reference memory bank for project understanding

The Memory Bank serves as the AI assistant's primary reference for understanding project context, enabling more effective and contextually-aware assistance throughout development.

(Optional) Configure VibeSpecs MCP Server for Spec-Driven Development

Set up the VibeSpecs MCP Server to enable structured, spec-driven development workflow in Cursor:

  1. Install VibeSpecs MCP Server
  2. follow installation instructions from VibeSpecs MCP Server

  3. configure the server in your Cursor MCP settings

  4. Initialize Spec-Driven Workflow

  5. use the workflow commands to guide feature development from requirements to implementation

  6. leverage structured phases: goal definition → requirements → design → tasks → execution

  7. Integrate with Project Structure

  8. align spec outputs with your repository documentation structure
  9. ensure generated specifications are version controlled
  10. reference spec-driven development documentation for best practices

The VibeSpecs MCP Server provides a systematic approach to feature development, ensuring thorough planning and consistent implementation across your project.

Next Steps

Once your project setup is complete, proceed to the feature development lifecycle:

Functional Requirements - Start by defining what your system should do from a user's perspective, including expected behaviors, UI elements, and testable features.