How to Automate Code Reviews Using AI in Under 2 Hours

Automating code reviews can feel like a daunting task, especially when you’re juggling multiple projects as a solo founder or indie hacker. The good news? With the right AI tools, you can streamline this process and enhance your coding quality in under two hours. In 2026, there are more options than ever, so let’s dive into how you can implement automation effectively.

Prerequisites: Tools You’ll Need

Before we get started, here are the essential tools you’ll need:

1. GitHub or GitLab Account - Most AI tools integrate seamlessly with these platforms.
2. Node.js or Python Installed - Some tools may require you to run scripts.
3. Basic Understanding of Git Commands - You'll need to push and pull code changes.

Step-by-Step Guide to Automating Code Reviews

Step 1: Choose Your AI Tool

Select an AI code review tool from the list below. Each has its strengths, pricing, and limitations, so pick one that suits your needs best.

Step 2: Set Up the Tool

Most tools can be integrated with your GitHub or GitLab account in under 30 minutes. Follow the specific setup instructions provided by the tool’s documentation.

Step 3: Configure Review Settings

Spend about 20-30 minutes configuring the review settings. This includes defining coding standards, setting up rules for code complexity, and integrating with CI/CD pipelines if necessary.

Step 4: Run Your First Review

After setup, push a code change to your repository. The AI tool will automatically generate a review report. This can take anywhere from a few seconds to a few minutes, depending on the complexity of your code.

Step 5: Analyze Feedback

Take time to go through the AI-generated feedback. This is crucial, as it helps you understand areas for improvement and ensures you’re not just relying blindly on the AI.

Troubleshooting: What Could Go Wrong

• Integration Issues: If the tool doesn’t connect with GitHub, double-check your permissions and API keys.
• Feedback Quality: Sometimes the AI may not catch everything. Always do a manual review before merging.

Tool Comparison: AI Code Review Tools

Here’s a quick comparison of the top AI tools you can use for code reviews in 2026:

| Tool Name | Pricing | Best For | Limitations | Our Take | |-------------------|----------------------------|-------------------------------------|------------------------------------------------|-----------------------------------| | CodeGuru | $0 for 1 user, $19/mo/user | Java, Python code reviews | Limited to AWS ecosystem | We use this for Java projects. | | DeepCode | Free tier + $15/mo pro | JavaScript, Python, TypeScript | Doesn’t support C/C++ | We don’t use it for C projects. | | SonarQube | Free tier + $150/mo | Comprehensive code quality analysis | Can be resource-intensive on large codebases | We prefer lighter options. | | ReviewBot | $29/mo, no free tier | GitHub integration | Limited customization options | We use this for quick reviews. | | Codacy | Free tier + $15/mo | Multiple languages | Some features locked behind higher tiers | Good for teams, but pricey. | | PullRequest | $19/mo/user | GitHub pull requests | Slower feedback on large PRs | Great for focused reviews. | | CodeScene | $25/mo | Visualizing code changes | Steep learning curve | Useful for understanding codebases.| | Snyk | Free tier + $49/mo | Security-focused code reviews | Focuses more on security than code quality | We don’t use it for general reviews.| | CodeClimate | $12/mo/user | Metrics-driven reviews | Lacks deep AI insights | Good for teams wanting metrics. | | LGTM | Free tier + $10/mo | Security and quality checks | Limited to specific languages | We use it for additional checks. |

What We Actually Use

In our experience, we primarily use CodeGuru for Java projects due to its seamless integration with AWS, and ReviewBot for quick pull request reviews on GitHub. For projects involving multiple languages, we lean towards Codacy for its broad language support and ease of use.

Conclusion: Start Here

To automate your code reviews, start by choosing a tool that fits your coding style and project needs. Invest a couple of hours to set it up correctly, and soon you'll find that your code quality improves significantly with less manual effort.

If you're unsure where to begin, I recommend starting with CodeGuru for Java or ReviewBot for GitHub integrations. Both can be set up quickly, and you'll see immediate benefits.