Overview
This article explores the evolution of software development practices, specifically focusing on how Salesforce development teams can leverage agentic coding to accelerate delivery. We trace the journey from traditional manual coding through the emergence of LLM assistance, IDE-embedded AI copilots, and finally to the cutting-edge realm of autonomous agentic coding. Each stage represents a significant leap in developer productivity, with agentic coding offering the potential for 3-5x speed improvements. This document outlines the characteristics, benefits, and business case for adopting agentic coding tools like Claude Code, Cursor, and Windsurf in Salesforce development workflows, demonstrating how these technologies can transform how we build, test, and deploy Salesforce solutions.
The Evolution of Development
Accelerating Salesforce Delivery with Agentic Coding
From Manual Coding to Autonomous Development
For Salesforce Delivery Team
Stage 1: Manual Coding
Traditional Development (Pre-2020)
Characteristics
- • Developers write every line of code manually
- • Heavy reliance on documentation and Stack Overflow
- • Time-consuming debugging and troubleshooting
- • Repetitive boilerplate code creation
Salesforce Impact: Slow apex class development, manual test class creation, repetitive trigger patterns
Stage 2: LLM Assistance
ChatGPT Era (2023)
Characteristics
- • Copy-paste between IDE and chat interface
- • LLM generates code snippets on request
- • Manual context switching and integration
- • Helpful for learning and troubleshooting
Salesforce Impact: Faster SOQL query creation, quick formula field logic, API integration examples
Stage 3: Copilot Integration
IDE-Embedded AI (2023-2024)
Characteristics
- • Inline code suggestions as you type
- • Context-aware autocomplete
- • Tab to accept, reduced copy-paste friction
- • Developer stays in flow state
Salesforce Impact: Rapid component development, intelligent trigger completion, test coverage acceleration
Stage 4: Agentic Coding
Autonomous Development (2024-2025)
Characteristics
- • AI autonomously edits multiple files
- • Executes terminal commands and tests
- • Self-corrects based on errors and feedback
- • Handles entire features end-to-end
Salesforce Tools: Claude Code (terminal), Cursor (IDE), Windsurf, Google Antigravity
Use Cases: Full LWC component creation, bulk trigger refactoring, test suite generation, metadata deployment
Why Agentic Coding for Salesforce?
The Business Case
Speed
Complete user stories in hours instead of days
Quality
Better test coverage, consistent patterns, fewer bugs
Scalability
Handle technical debt and refactoring at scale
Developer Experience
Focus on architecture and business logic, not boilerplate
Next Steps
Start pilot with Claude Code or Cursor on non-critical features
Measure velocity improvements and iterate