Description:

This 3-day intensive training prepares participants to build and extend the Salesforce platform using Apex, SOQL, and Lightning Web Components. Students will work hands-on with the Salesforce Developer Console and Visual Studio Code to design custom data models, write business logic with Apex classes and triggers, query and manipulate data programmatically, and build modern Lightning user interfaces. The course concludes with Apex testing, debugging, and deployment strategies — giving students everything they need to pass the Platform Developer I exam and immediately contribute to real-world Salesforce development projects.

Duration: 

1 Day

Course Code: BDT626

Learning Objectives:

After this course, you will be able to:

1. Explain the Salesforce platform architecture, developer tooling, and multi-tenant execution model.
2. Design custom data models using standard and custom objects, field types, and object relationships.
3. Write Apex classes, methods, and triggers to implement and automate business logic.
4. Query and manipulate Salesforce data using SOQL and SOSL within governor limit constraints.
5. Build Lightning Web Components to deliver custom user interface experiences.
6. Apply Apex testing best practices to achieve the required code coverage for deployment.
7. Deploy Salesforce metadata across environments using Change Sets and Salesforce CLI.
8.  

This course is designed for individuals looking to build and extend the Salesforce platform programmatically and prepare for the Salesforce Platform Developer I certification.

1. Junior Salesforce developers building their first platform solutions.
2. Salesforce Administrators transitioning into a development role.
3. Professionals preparing for the Salesforce Platform Developer I (PD1) certification exam.

1. Familiarity with Salesforce administration basics (objects, fields, profiles, and permissions).
2. Basic understanding of programming concepts such as variables, loops, and conditional logic.
3. Completion of the Salesforce Fundamentals course or equivalent hands-on Salesforce experience.

Course Outline:

Introduction to Cursor

1. What are AI coding assistants and AI-native IDEs?
2. Overview of underlying AI models in Cursor (GPT, Claude, Gemini)
3. What is Cursor?
4. Key capabilities of Cursor
5. Cursor vs traditional coding assistants and extensions

Key Concepts

1. AI-native development environments
2. AI-assisted development workflows
3. Codebase indexing and understanding

Demonstration

1. Exploring Claude Code in the terminal

Installing and Configuring Cursor

1. System requirements and migration from VS Code
2. Installing Cursor
3. Authentication, account setup, and model selection
4. Opening project and managing codebase indexing
5. Configuring settings, keyboard shortcuts, and preferences

Hands-On Lab

1. Install Cursor
2. Initialize and index a project in Cursor
3. Run basic AI queries and inline edits

Cursor Architecture and Workflow

1. How Cursor works
2. Editor-based AI interaction (Chat, Cmd+K, Composer)
3. Codebase context, embeddings, and file access
4. Terminal integration and command execution
5. Interaction with various LLM models

Key Concepts

1. Context awareness and @ symbol
2. Cursor Tab (predictive editing)
3. Safe execution and approvals

Working with Cursor Features

1. Using the Chat panel for codebase questions
2. Inline code generation and editing (Cmd+K / Ctrl+K)
3. Multi-file editing Composer (Cmd+I / Ctrl+I)
4. Utilizing the integrated terminal with AI assistance
5. Debugging code and fixing linter error with Cursor

Hands-On Lab

1. Explore an unfamiliar codebase using Cursor Chat and codebase indexing
2. Fix a bug using inline edits and terminal error pasting

Automating Development Tasks

1. Large-scale code generation and refactoring
2. Automated documentation generation
3. Writing unit tests and integration tests with Claude
4. Investigating build errors and test failures
5. Managing Git workflows within the editor

Hands-On Lab

Use Cursor to:

1. Implement a multi-file feature using Composer
2. Generate tests for a new feature
3. Review and Commit changes

Customizing Cursor

1. Using configuration files and .cursorrules
2. Defining project-specific coding standards and rules
3. Managing custom system prompts
4. Customizing Cursor’s AI behavior per project
5. Managing extensions and VS Code compatibility

Hands-On Lab

1. Create .cursorrules file to guide AI code generation behavior
2. Setup custom documentation links (@Docs) for the AI to reference

Advanced Workflows and Agentic Editing

1. AI orchestration in the editor
2. Multi-file refactoring agents
3. Utilizing @ symbols for advanced context pinning (Files, Folders, Web, Git_
4. Managing context windows and token usage

Hands-On Lab

1. Build and execute a complex, multi-file refactoring workflow using Composer Agent mode

Best Practices for Using Cursor

1. Structuring prompts for accurate code generation
2. Managing context effectively (avoiding context pollution)
3. Ensuring secure handling of proprietary code
4. Model selection: Cost, speed, and performance considerations