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Agentic AI & Git Learning Plan

A rapid, hands-on curriculum for mastering Git, AI-assisted development, and modern workflows with an expert AI mentor agent. Designed for fast progress, with deep-dive references for further exploration.

New! See the Guide: Getting Access to Agentic AI in Cursor & VS Code (June 2025) for up-to-date advice on free tiers, cost models, and maximizing productivity with agentic AI tools.

Module 1: Crafting a Frictionless Terminal Environment with Zsh & Oh-My-Zsh

  • Why Your Terminal Matters
  • A smooth, powerful terminal setup saves time, reduces frustration, and makes development more enjoyable.
  • Modern shells like Zsh, enhanced with Oh-My-Zsh and plugins, provide features like autosuggestions, syntax highlighting, and especially a powerful, informative prompt.

  • Example prompt: "Why do developers prefer Zsh and Oh-My-Zsh over Bash?"

  • Making Your Zsh Environment Portable

  • Want your 10x shell setup everywhere (local, remote, new machines)? See the Portable Shell & Dotfiles Guide for best practices, example configs, and a bootstrap script.

  • Setting Up Zsh and Oh-My-Zsh

  • Step 1: Check Your Shell

    • Zsh is the default shell on macOS since Catalina (10.15). To check your current shell, run:

    sh echo $SHELL

    • If your shell is not Zsh, you can install it and set it as default.
    • Step 2: Install Zsh (if needed)
    • On most systems, you can install Zsh with your package manager (e.g., brew install zsh on macOS, sudo apt install zsh on Ubuntu).
    • To make Zsh your default shell, run:

    sh chsh -s $(which zsh)

  • Step 3: Open the Terminal in Cursor IDE

    • Use the menu (View > Terminal) or the shortcut (usually Ctrl+or Cmd+ on Mac) to open a terminal inside Cursor IDE.

  • Step 4: Install Oh-My-Zsh

    • In your Cursor IDE terminal, run:

    sh sh -c "$(curl -fsSL https://raw.githubusercontent.com/ohmyzsh/ohmyzsh/master/tools/install.sh)"

    • Oh-My-Zsh makes it easy to manage plugins, themes, and your Zsh configuration.
    • Example prompt: "Guide me through installing Zsh and Oh-My-Zsh on my system."
    • Example prompt: "How do I make Zsh my default shell?"

  • Must-Have Plugins for Productivity

  • Task: Add plugins like zsh-autosuggestions and zsh-syntax-highlighting for a buttery smooth experience.
  • Example prompt: "Install and configure zsh-autosuggestions and zsh-syntax-highlighting."

  • Why: These plugins boost speed, reduce errors, and make your terminal a joy to use.

  • A Prompt That Works for You: Git Integration and Context

  • Task: Customize your Zsh prompt to show useful information, especially Git branch/status, Python environment, and more.
  • Example prompt: "Help me set up my Zsh prompt to show the current Git branch and status."
  • Why: A good prompt gives you instant feedback about your repo state (e.g., branch, dirty/clean, staged changes), reducing mistakes and context switching. It can also show Python virtualenv, time, and more—making you more productive and less likely to make Git errors.

  • Example prompt: "Explain what each part of my Zsh prompt means and how to customize it for my workflow."

  • Letting the Agent Help

  • Task: Use the agent to explain, install, and troubleshoot your shell environment, plugins, and prompt customization.
  • Example prompt: "Explain what each Oh-My-Zsh plugin does and recommend the best ones for developers."
  • Example prompt: "If my Zsh config is slow or buggy, help me debug and optimize it."

  • Example prompt: "Suggest a Zsh prompt theme or config that works well for Git workflows."

  • Going Deeper: Resources & Videos

  • Oh My Zsh Official Site
  • Awesome Zsh Plugins
  • Zsh Autosuggestions
  • Zsh Syntax Highlighting
  • Video: How to Set Up a Beautiful Zsh Terminal (YouTube)
  • Video: Oh My Zsh! Productivity Tips (YouTube)
  • Oh My Zsh Git Plugin
  • Customizing Your Zsh Prompt (Oh My Zsh Docs)

Module 2: Kickstart – Your AI Mentor & Git in Action

  • Meet Your AI Mentor
  • Learn how the AI agent can guide, review, and unblock you throughout your workflow.
  • Example prompt: "What can you help me with in this project?"
  • Instant Git Setup
  • Task: Initialize a new Git repository, make your first commit, and push to GitHub.
  • Use the AI to walk you through each step, explain commands, and troubleshoot errors.
  • Example prompt: "Help me set up a new Git repository and push it to GitHub. Explain each step."
  • Integrate Cursor IDE with GitHub
  • Task: Connect Cursor IDE to your GitHub account and verify integration.
  • Use the AI to guide you through the integration process and check your setup.
  • Example prompt: "Guide me through connecting Cursor IDE to my GitHub account."
  • Test Your Integration with the AI Mentor
  • Task: Make a test commit and push to verify everything works.
  • Example prompt: "Check if my Cursor IDE is properly connected to GitHub. Try making a test commit and push it to my repository. If there are any issues, help me fix them."
  • Go Deeper:
  • Pro Git Book
  • GitHub Docs: Getting Started
  • Cursor IDE Docs: GitHub Integration

Module 3: Branching, Iterating, and Rolling Back – Fast

  • Branching with AI
  • Task: Create, switch, and merge branches for new features or experiments.
  • Use the AI to suggest branch names, explain branching strategies, and automate branch creation.
  • Example prompt: "Create a new branch for a feature called 'user-auth'. Explain why and how to use branches."
  • Iterate Rapidly
  • Task: Make changes, commit, and use the AI to review and improve your code.
  • Example prompt: "Review my latest commit and suggest improvements."
  • Rollback Mistakes
  • Task: Use Git commands to reset, revert, or checkout previous states if something goes wrong.
  • Use the AI to explain the difference between these commands and guide you through rollbacks.
  • Example prompt: "I made a mistake in my last commit. Should I use reset, revert, or checkout? Help me fix it."
  • Go Deeper:
  • Atlassian Git Branching Guide
  • Git Reset, Revert, and Checkout
  • Oh Shit, Git!?!

Module 4: AI + Cursor IDE + GitHub Integration

  • Connect Everything
  • Task: Ensure your GitHub repo is linked in Cursor IDE and you can see Git status, commit, push, and pull.
  • Example prompt: "Show me how to use Git features in Cursor IDE."
  • AI-Driven Code Reviews & PRs
  • Task: Use the AI to review your code, suggest improvements, and help you create pull requests.
  • Example prompt: "Review my code and help me create a pull request for my latest feature."
  • Collaborate with the AI
  • Task: Use the agent to explain diffs, resolve merge conflicts, and document your changes.
  • Example prompt: "Explain the differences between these two branches and help me resolve any conflicts."
  • Go Deeper:
  • Cursor IDE Docs
  • GitHub Pull Requests

Module 5: Supercharge with Model Context Protocols (MCP)

  • What is MCP?
  • Learn how MCP tools expand your AI's context and capabilities for smarter assistance.
  • Example prompt: "What are Model Context Protocols and how can they help me in Cursor?"
  • Hands-On: Install & Use the Official Everything MCP Server
  • Task: Set up the official Everything MCP Server (@modelcontextprotocol/server-everything) to experiment with a variety of MCP tools.

  • Quick Start:

    1. Make sure you have Node.js installed.
    2. Run the server with:

    sh npx @modelcontextprotocol/server-everything

    1. (Optional) Integrate with VS Code by adding to .vscode/mcp.json:

    json { "servers": { "everything": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-everything"] } } }

    1. Explore the available tools (e.g., add, echo, sampleLLM, printEnv) and try calling them from your AI agent or IDE.
    2. Use the AI to guide installation, configuration, and first use.
    3. Example prompt: "Walk me through installing and using the Everything MCP Server with Cursor."
    4. Enhance Your Workflow
    5. Task: Use MCP to search code, share context, and automate tasks with the AI.
    6. Example prompt: "Use MCP to search for all functions related to authentication in my codebase."
    7. Go Deeper:
    8. Everything MCP Server on npm
    9. MCP Tools Documentation
    10. MCP Example Servers

Module 6: Real-World Project – Rapid Co-Development

  • Build Something Real, Fast
  • Task: Define a small project (e.g., CLI tool, web app) with the AI's help.
  • Example prompt: "Help me brainstorm and outline a simple CLI tool project."
  • Plan, Build, and Iterate with AI
  • Task: Use the AI to break down the project into tasks, create branches, and implement features step by step.
  • Example prompt: "Create a task list for this project and help me start the first feature branch."
  • Practice Branching, Merging, and Rollbacks
  • Task: Use the AI to guide you through branching, merging, and rolling back changes as you develop.
  • Example prompt: "Guide me through merging my feature branch and resolving any conflicts."
  • Use MCP Tools to Enhance Workflow
  • Task: Leverage MCP for advanced code search, context sharing, and automation.
  • Example prompt: "Show me how to use MCP to document and share project context with collaborators."
  • Go Deeper:
  • Open Source Guides
  • Effective Pair Programming

Module 7: Laying the Foundation for a Modern Python Project

  • Project Structure & Initialization
  • Task: Create a clean project directory and initialize it in Cursor IDE.

  • Example prompt: "Set up a new Python project structure in this directory, including a src/ folder and a README.md."

  • Dependency Management with uv and requirements.txt

  • Task: Use uv (a fast, modern Python package manager) to manage dependencies.
  • Example prompt: "Install uv and use it to add requests and pytest to my project. Generate a requirements.txt file."

  • Why: uv is faster and more reliable than pip, and requirements.txt ensures reproducibility for collaborators and CI.

  • Development Environment: Should You Use a devcontainer?

  • Task: Decide whether to use a devcontainer for consistent, reproducible development environments.
  • Example prompt: "Should I use a devcontainer for this project? If so, generate a .devcontainer/devcontainer.json for a Python 3.11 environment with uv and ruff pre-installed."

  • Why: Devcontainers make onboarding, CI, and cross-platform development easier and more reliable.

  • Code Quality: Setting Up Ruff

  • Task: Add ruff for fast linting and code formatting.
  • Example prompt: "Install ruff and configure it for this project. Add a pyproject.toml with recommended settings."

  • Why: Ruff enforces code style and catches errors early, improving code quality and consistency.

  • Automated Checks: Pre-commit Hooks

  • Task: Set up pre-commit to run ruff and other checks before every commit.
  • Example prompt: "Set up pre-commit to run ruff and black on every commit. Add a .pre-commit-config.yaml and install the hooks."

  • Why: Pre-commit ensures code quality checks are run automatically, preventing bad code from entering your repo.

  • Letting the AI Agent Do the Heavy Lifting

  • Task: Use the agent to automate setup, explain configuration files, and troubleshoot issues.
  • Example prompt: "Automate the setup of uv, ruff, and pre-commit for this project. Explain what each tool does and how to use it."

  • Example prompt: "If I get a pre-commit error, help me understand and fix it."

  • Go Deeper:

  • uv: Fast Python Package Manager
  • Ruff: Python Linter & Formatter
  • pre-commit: Framework for Managing Git Hooks
  • Dev Containers

Module 8: Automating CI and Testing with Your AI Agent

  • Setting Up a CI Pipeline with GitHub Actions
  • Task: Automate continuous integration (CI) for your project using GitHub Actions.
  • Example prompt: "Set up a GitHub Actions workflow to run my Python tests and linting on every push and pull request."
  • Why: CI ensures your code is automatically tested and checked for quality before merging, reducing bugs and improving reliability.

  • Example prompt: "Explain what each step in the generated GitHub Actions workflow does."

  • Letting the Agent Do the Heavy Lifting

  • Task: Use the agent to generate, configure, and troubleshoot your CI pipeline.

  • Example prompt: "If my GitHub Actions workflow fails, help me debug and fix the issue."

  • Writing and Maintaining Tests with the Agent

  • Task: Ask the agent to generate unit, integration, or end-to-end tests for your codebase.
  • Example prompt: "Write unit tests for my main.py file using pytest."
  • Example prompt: "Review my test coverage and suggest areas that need more tests."

  • Why: Automated tests catch bugs early, document expected behavior, and make refactoring safer. With an AI agent, writing and maintaining tests becomes much easier and less time-consuming.

  • Why Adopt CI and Automated Testing Now?

  • With your AI agent handling much of the setup and maintenance, there's little reason not to automate quality checks and testing. This leads to more robust, maintainable, and collaborative projects.

  • Go Deeper:

  • GitHub Actions Documentation
  • pytest Documentation
  • Guide: Automated Testing Best Practices

Best Practices for Prompting Cursor-Style Agents

  • Be Specific and Contextual: Clearly state your goal, provide relevant code or file references, and specify the language or framework if needed.
  • Use Step-by-Step (Chain-of-Thought) Prompts: For complex tasks, break your request into steps or ask the agent to explain its reasoning as it works.
  • Give Examples (Few-Shot Prompting): If you want a certain style or format, provide a short example in your prompt.
  • Iterate and Refine: Don't expect perfection on the first try—ask follow-up questions, request clarifications, and refine your prompt as needed.
  • Ask for Explanations: If you don't understand a suggestion, ask the agent to explain its reasoning or the code it generated.
  • Leverage Cursor Rules: Use .cursorrules to set project-specific guidelines for the agent, such as coding style, error handling, or naming conventions.
  • Review and Test AI-Generated Code: Always review, test, and validate code before merging or deploying.
  • Be Polite and Clear: While not required, a friendly and clear tone can improve results and make collaboration smoother.

References & Further Reading

References & Further Learning

  • Git, GitHub, Cursor IDE, and MCP documentation
  • Example repositories and exercises
  • Community and support channels

Next Steps

  • Keep building with AI and Git
  • Explore advanced MCP integrations
  • Contribute to open source with your new skills

Common Scenarios and Solutions

Here are some common scenarios you might encounter and how to handle them using Git with AI assistance:

Working with Branches

When starting new work:

  1. Create a new branch from main
  2. Make your changes
  3. Commit regularly with clear messages
  4. Push to remote and create PR when ready

AI can help with:

  • Generating meaningful commit messages
  • Reviewing changes for potential issues
  • Suggesting improvements to code quality