Course Description

Build Better Apps with Cursor by Adding Automated AI Code Reviews

Cursor’s AI agent can generate features incredibly fast — but speed comes with risk. Auto-generated code often ships with security flaws, broken integrations, and hidden bugs that compound over time if they’re not caught early.

In this lesson, you’ll learn how to pair Cursor with CodeRabbit to create a powerful feedback loop where every implementation phase is reviewed, refined, and hardened before moving forward. This workflow dramatically improves code quality, security, and stability, without slowing you down.

Instead of blindly prompting the agent again and again, you’ll introduce structured review cycles that catch problems immediately and feed actionable fixes straight back into the AI.

What You’ll Learn

• Why AI coding agents frequently introduce hidden vulnerabilities

• How to review AI-generated code after every implementation step

• How to catch security issues before they reach production

• How to combine Cursor + CodeRabbit into a single tight workflow

• How to build large projects phase-by-phase with integrated reviews

Core Concepts Covered

Why AI Code Needs Continuous Review

• Cursor generates large amounts of code automatically

• Errors, leaks, and poor practices are unavoidable at scale

• Early detection prevents fragile architectures later

Introducing CodeRabbit

• Originally built for GitHub PR and commit reviews

• Now available as an extension for:

  • Cursor

  • VS Code

  • Windsurf

• Reviews commits for:

  • Security vulnerabilities

  • Refactoring opportunities

  • Integration flaws

  • Code quality issues

Cursor + CodeRabbit Review Loop

• Generate code with Cursor

• Commit changes locally using Git

• Trigger CodeRabbit review automatically

• Receive detailed suggestions and warnings

• Feed fixes back into Cursor’s AI agent

• Repeat for every phase

Git-Based Workflow Setup

• Initialize Git in your project

• Commit changes after each implementation chunk

• Let CodeRabbit review each commit

• Use branches correctly to avoid known issues

• Maintain clean version history throughout development

Handling Review Feedback Efficiently

• Inspect review comments per file

• Use “Fix with AI” to generate structured instructions

• Paste instructions directly into Cursor

• Let the agent apply fixes accurately

• Recommendation: use Gemini 2.5 Pro for handling multiple fixes at once

Structured Implementation Plan

• Define project specs and tech stack upfront

• Generate a multi-phase implementation plan

• Lock the agent to the plan using Cursor rules

• Execute phase by phase:

  • Implement

  • Commit

  • Review

  • Fix

  • Continue

• Maintain momentum without chaos

Real-World Results

• Fewer runtime errors

• Stronger security (especially around auth & passwords)

• Cleaner component logic

• Faster stabilization of complex projects

• Reduced back-and-forth prompting

Who This Lesson Is For

• Cursor users building real applications

• Developers worried about AI-generated security flaws

• Teams wanting predictable AI workflows

• Anyone scaling beyond “toy projects”