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Automate Apex Code Reviews in Salesforce with AI using GPTfy

· 6 min read
GPTfy Team
GPTfy Team
GPTfy Product Team

Table of Contents​

TL;DR​

GPTfy enables Salesforce technical teams to automate code reviews by connecting AI with Salesforce metadata. Create a custom Apex retriever class, configure your organization’s coding standards as prompts, and implement automated quality checks that integrate with your development workflow to save time and ensure consistent code quality.

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What?​

A step-by-step guide on automating Salesforce Apex code reviews using AI through GPTfy to enforce coding standards and best practices without manual intervention.

Who?​

Salesforce admins, developers, architects, and COE leaders who want to maintain quality and consistency across their org’s codebase.

Why?​

To streamline quality assurance, enforce organizational coding standards, and free up developer time from repetitive code reviews.

→ Transform manual code reviews into automated quality gates with AI.

What can you do with it?​

  • Automated Code Analysis: Instantly check Apex classes against organizational standards
  • Standardized Quality Gates: Ensure consistent enforcement of coding policies
  • Developer Guidance: Provide specific feedback with examples for improvement
  • Technical Debt Management: Track code quality evolution over time

The Challenge for Tech Teams​

One of the big challenges for technology teams supporting Salesforce is how to apply AI beyond sales and service use cases – essentially, how to “scratch their own itch.” As a Salesforce admin, developer, architect, or Center of Excellence leader, ensuring consistent application of standards and policies can be a significant burden.

The traditional approach to code reviews requires manual inspection, which is time-consuming, inconsistent, and often creates bottlenecks in development workflows. What if you could automate this process using the same AI capabilities that power other areas of your Salesforce org?

This challenge becomes particularly acute in large organizations or when working with multiple consultants and partners. Without automated checks, maintaining consistent code quality becomes nearly impossible at scale.

How It Works: Under the Hood​

GPTfy offers a streamlined solution for AI-powered Apex code reviews through its API Data Source capabilities. Here’s a look at the core components:

Custom Objects Structure​

The solution leverages two custom objects to track code artifacts and their reviews:

  • DevArtifact__c: Parent object that represents an Apex class
  • DevArtifactReview__c: Child object that contains individual review results

This parent-child relationship provides a complete historical record of code quality over time. Each time a class is updated, a new review record is created, preserving the entire lifecycle of the code’s evolution.

API Data Source Integration​

The magic happens through GPTfy’s API Data Source feature, which connects to a custom Apex class that retrieves code for analysis. This class uses the Tooling API to pull the latest version of any Apex class in your org.

When you run the analysis, GPTfy:

  • Calls your custom Apex retriever class
  • Passes the name of the class to analyze
  • Gets back the code content
  • Processes the response and stores it in your custom object

Analysis with AI​

The AI analysis applies your organization’s specific coding standards to the Apex class, identifying issues in areas like:

  • Error handling
  • Input validation
  • Code structure
  • Performance considerations
  • Security vulnerabilities

The analysis results are automatically formatted as a readable report and stored in the DevArtifactReview__c object, where they can be accessed, shared, and tracked over time.

Implementation Steps​

1. Create a Custom Apex Retriever Class​

Develop an Apex class that implements GPTfy’s API Data Source interface. This class will retrieve the code to be analyzed using the Tooling API.

2. Configure Custom Objects​

Create the DevArtifact__c and DevArtifactReview__c objects to store your analysis results.

3. Set Up Your AI Prompt​

Configure a prompt in GPTfy that incorporates your organization’s specific coding standards and best practices. Use structured HTML output with formatted issue boxes, code blocks, and required review sections.

4. Configure API Data Source in GPTfy​

  • Navigate to the GPTfy Cockpit
  • Select “API Data Sources”
  • Create a new data source
  • Name: ApexCodeRetriever
  • Apex Class: ApexCodeRetriever
  • Test Parameters: {"className": "AccountTriggerHandler"}
  • Save and test the connection
  • Open your code review prompt
  • Select “Data Sources” tab
  • Add “ApexCodeRetriever” as a data source
  • Configure merge field: Replace [CODE] with {!ApexCodeRetriever.Body}
  • Save the prompt

6. Automate Reviews with Flow​

  • Build a trigger on DevArtifactReview__c after update
  • Use GPTfy invocable actions to run the prompt
  • Create/update DevArtifact and DevArtifactReview records
  • Optionally, add notification actions based on results

Use Cases of AI Automated Apex Code Review in Salesforce​

Center of Excellence Support​

Enforce organizational standards across all development work. Ensure consistency across multiple teams and business units while reducing governance overhead.

Consultant and Partner Management​

Automatically validate code delivered by partners and consultants before acceptance, ensuring quality standards are met.

Developer Training and Onboarding​

Provide junior developers with detailed, actionable feedback to accelerate their learning and ensure adherence to best practices.

Technical Debt Management​

Track code quality trends over time and create dashboards to visualize improvements and identify problem areas.

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Conclusion​

GPTfy enables Salesforce technical teams to “scratch their own itch” by automating code reviews against organizational standards. By combining a custom Apex retriever with AI analysis, you can implement consistent quality checks that integrate seamlessly with your development workflow.

The beauty of this approach lies in its flexibility and ease of implementation. You can set it up in hours, using the same GPTfy platform that powers your sales and service AI initiatives, but now applied to your own technical processes.

This creates a unified approach to AI across your entire Salesforce ecosystem, where developers, admins, architects, and business users all benefit from the same powerful AI capabilities.