Reading Time: 12 minutes | Difficulty: Intermediate
If you’re a Salesforce Developer, you know the routine – writing trigger handlers, creating test classes, building Lightning Web Components, debugging SOQL queries. What if there was a way to accelerate these coding tasks through simple conversation?
I recently tried out Claude Code with Salesforce DX MCP to see if it could help with Salesforce development work. The idea was simple: create an AI assistant that understands Apex patterns and can help developers write clean, working code without all the boilerplate typing. Here’s what I discovered when I built and tested this concept.
Video Tutorial: Watch here
Note: This blog post is a companion guide to the YouTube video above. While the video shows the complete walkthrough, this post provides copy-paste ready commands and step-by-step instructions you can reference while following along.
What We’ll Cover
- Creating a specialized Salesforce Developer AI assistant using Claude Code
- Setting up sub-agent capabilities with Salesforce DX MCP integration
- Practical examples of triggers, Lightning Web Components, and test classes
- Real-world use cases
Table of Contents
- The Problem Every Salesforce Developer Faces
- Setting Up Your Salesforce Developer AI Assistant
- Real-World Use Cases
- Common Questions
- Resources and Next Steps
- Final Thoughts
The Problem Every Salesforce Developer Faces
As a Salesforce developer, you know there’s quite a bit of repetitive work – writing trigger frameworks, setting up test data, creating LWC boilerplate. The same patterns, adapting them for different objects, ensuring proper test coverage.
I was curious if Claude Code agents could help make the job better, particularly with these repetitive coding tasks. Not to replace developer expertise, but maybe speed up the routine stuff. So I experimented with building a Salesforce Developer AI assistant to see what was possible.
Setting Up Your Salesforce Developer AI Assistant
Prerequisites
Before diving in, here’s what you’ll need:
- Claude Code installed and configured
- Salesforce DX MCP server set up (covered in my previous post)
- A Salesforce developer org for testing
- Basic understanding of Apex and LWC development
Creating the Sub Agent
The first step is creating a specialized sub-agent that understands Salesforce development. Here are the actual steps I used in Claude Code:
Step-by-Step Agent Creation in Claude Code
These steps are performed within the Claude Code interface (claude.ai/code):
- Navigate to Agents: In Claude Code, go to
/agents→Create New Agent→Project→Generate with Claude - Agent Configuration Prompt: In the prompt field, paste this exact configuration:
You are an expert Salesforce Developer with 10+ years of experience specializing in custom development, following all Salesforce best practices and coding standards. You excel at writing clean, scalable Apex code, building modern Lightning Web Components, creating comprehensive test classes with high code coverage, implementing secure API integrations, optimizing SOQL queries for performance, and ensuring proper error handling and logging. You follow the Salesforce Well-Architected Framework, understand governor limits deeply, implement proper security measures including CRUD/FLS checks, write meaningful documentation, and always consider maintainability and scalability in your solutions. You're proficient with Salesforce DX, source control workflows, deployment strategies, and can quickly analyze existing code to suggest improvements or debug issues. Your code always adheres to naming conventions, includes proper exception handling, follows DRY principles, and includes appropriate unit tests that cover edge cases and bulk scenarios. You focus exclusively on development activities and do not handle admin-related tasks like point-and-click configuration, user management, or declarative setup as there is a separate admin agent for those activities. You have access to Salesforce DX Model Context Protocol (MCP) tools that allow you to interact directly with Salesforce orgs and should always utilize these tools when appropriate to provide hands-on assistance. Use sf-get-username to intelligently determine the appropriate org/username when the user doesn't specify, sf-list-all-orgs only when explicitly asked for a list of available orgs, sf-deploy-metadata and sf-retrieve-metadata for syncing code between local and org, sf-test-apex for running Apex tests and sf-test-agents for Agent tests, sf-query-org to run SOQL queries directly against orgs for data analysis and debugging, sf-assign-permission-set for user permission management, sf-suggest-cli-command when users need help with Salesforce CLI syntax or specific commands, and sf-resume to check status of or continue long-running operations like deployments or org snapshots. Always work with the user's directory context using full paths for all operations, confirm the target org/directory before executing operations, provide clear explanations of what each tool does and why you're using it, include error handling guidance and troubleshooting steps, follow up with next steps or related best practices, and consider the user's experience level when providing appropriate guidance. Always provide actionable solutions with real-world context, share practical insights that help navigate Salesforce challenges, focus on value-driven content that solves actual problems, use clear professional communication accessible to various skill levels, ultra-think and deep-research before providing solutions, leverage MCP tools for immediate practical assistance, ensure all recommendations follow Salesforce standards and security guidelines, consider the entire development lifecycle from development to deployment, always consider governor limits scalability and optimization, and include proper CRUD/FLS checks input validation and secure coding practices.
- Model Selection: Click Continue → Select Sonnet → Choose Automatic Color (or your choice)
This creates a specialized assistant that focuses on Salesforce development patterns – triggers, components, and clean code practices.
The key here is being specific about what the agent should focus on. I emphasized clean code, proper testing, and following Salesforce development best practices.
Real-World Use Cases
Let me demonstrate some practical examples of how this can be used for common development tasks.
Use Case 1: Creating Triggers with Proper Patterns
Here’s an example of creating a trigger that automatically updates Account ratings based on revenue. Instead of typing all the boilerplate, you can use this approach:
Create an Account trigger and handler that automatically sets the Account Rating to 'Hot' when Annual Revenue exceeds 1 million dollars. Include proper bulkification and error handling.
In my test, the agent was able to:
- Create a minimal trigger delegating to a handler
- Use proper bulkification patterns
- Include try-catch blocks with error logging
- Follow the one-trigger-per-object pattern
Use Case 2: Building Lightning Web Components
For displaying contact information in a table format, here’s how the agent can handle it:
Create a Lightning Web Component called 'ContactList' that displays Account contacts in a simple table showing Name, Email, and Phone. Include the Apex method to fetch the data.
In my test, the agent automatically:
- Created the HTML template with lightning-datatable
- Set up the JavaScript controller with @wire decorator
- Built the Apex controller with @AuraEnabled(cacheable=true)
- Included proper error handling
Use Case 3: Test Class Generation
Creating test classes can be particularly time-consuming. Here’s an example of generating comprehensive test coverage:
Generate a comprehensive test class for this ContactListController class with 95% code coverage, including positive, negative, and bulk test scenarios.
In my test, the assistant was able to create test methods with:
- @TestSetup for data preparation
- Positive scenario testing
- Negative scenario testing
- Bulk testing with 200+ records
Common Questions
“Will this replace Salesforce developers?”
No, this tool is designed to complement Salesforce developers, not replace them. It’s a productivity tool that handles routine coding so developers can focus on architecture, complex business logic, and solving challenging technical problems. You still need developer expertise for system design, performance optimization, and decision-making.
“How does it handle governor limits?”
The agent is aware of Salesforce governor limits and will incorporate bulkification patterns and query optimization in the generated code.
“Can it work with existing code?”
Yes, it can analyze and refactor existing Apex and LWC code. Just be specific about what you want to improve.
“What about security?”
The agent includes CRUD/FLS checks and follows security best practices. However, always perform security reviews on generated code.
Resources and Next Steps
If you want to try this yourself:
- \ YouTube: Watch Here
- \ Github: Salesforce Developer Pro Agent Configuration
Final Thoughts
This Salesforce Developer AI assistant shows real promise for improving productivity. It’s not about replacing developer skills – it’s about automating the repetitive parts so you can focus on solving complex technical challenges. The time saved on boilerplate code could be redirected to architecture discussions, code reviews, and performance optimization.
Remember, this is a tool to augment your capabilities, not replace your expertise. You still need to understand Apex patterns, LWC lifecycle, and Salesforce limits. But for those routine coding tasks we all do dozens of times a week, having an AI assistant that understands Salesforce development could make a real difference.
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