Apex is Salesforce's strongly typed, object-oriented programming language used to implement complex business logic on the Salesforce Platform.

Apex can be used for:

• Triggers
• Database operations
• Custom business logic
• REST and SOAP services
• Callouts
• Queueable Apex
• Batch Apex
• Scheduled Apex

Bulkification means writing Apex that can process multiple records efficiently within a single transaction.

Salesforce automation can process many records at the same time, so Apex should never assume that only one record will be processed.

Collect IDs in a Set, execute a single SOQL query using the IN operator and store records in a Map when required.

Governor Limits are platform limits that protect the shared Salesforce environment from inefficient resource consumption.

Developers need to consider limits related to:

• SOQL queries
• DML statements
• CPU time
• Heap size
• Callouts
• Database operations

The exact limits depend on the execution context, so developers should always refer to the current Salesforce documentation when designing limit-sensitive solutions.

A trigger is Apex code that executes automatically before or after specific Salesforce database events.

Common events include:

• Before Insert
• Before Update
• Before Delete
• After Insert
• After Update
• After Delete
• After Undelete

The Trigger Handler Pattern separates trigger event detection from business logic.

The handler class contains the actual business logic.

Trigger recursion occurs when automation causes the same logic to execute repeatedly.

A handler framework can maintain transaction-level state and track which records and events have already been processed.

Avoid relying only on a single static Boolean for complex applications. A more robust framework can track object, event and record-level execution.

Batch Apex is useful when processing large numbers of Salesforce records in manageable chunks.

Example:

Suppose a company needs to process millions of historical Opportunity records.

A typical architecture could be:

1. Select only the fields that are required.
2. Use selective filters.
3. Avoid unnecessary queries.
4. Review query selectivity.
5. Use indexed fields where appropriate.
6. Avoid retrieving huge datasets unnecessarily.
7. Use appropriate query strategies for large data volumes.

LWC can communicate with Apex using either the @wire service or imperative Apex calls.

Wire example:

Imperative example:

Use @wire when:

• You want reactive data.
• Parameters should automatically react to changes.
• You want framework-managed data provisioning.

Use imperative Apex when:

• You need to control when the call happens.
• A button should trigger the operation.
• You need custom execution sequencing.
• You are performing operations such as save or delete.

For unrelated components, Lightning Message Service (LMS) can be used to publish and subscribe to messages.

Other communication approaches include parent-to-child properties and child-to-parent custom events.

• Avoid unnecessary Apex calls.
• Retrieve only required fields.
• Use Lightning Data Service where appropriate.
• Use caching where appropriate.
• Implement pagination for large datasets.
• Lazy-load expensive data.
• Debounce search inputs.
• Avoid rendering thousands of DOM elements.

• Request and Reply: Salesforce sends a request and waits for a response.
• Fire and Forget: Salesforce sends a message without waiting for an immediate response.
• Batch Data Synchronization: Large volumes of data are synchronized periodically.
• Remote Call-In: An external system calls Salesforce.
• Data Virtualization: Salesforce accesses external data without necessarily storing all of it locally.

Named Credentials provide centralized configuration for external endpoints and authentication.

They help avoid hard-coding endpoint and authentication details directly in Apex.

A secure API design should consider:

• Authentication
• Authorization
• Object permissions
• Field-level security
• Record-level sharing
• Input validation
• Error handling
• Logging
• Sensitive-data protection

An idempotent API allows repeated processing of the same request without unintentionally creating duplicate business results.

For example:

Salesforce can use a unique external business key to identify the request and avoid duplicate records when an external system retries the request.

A class declared with sharing respects record-level sharing rules for the execution context.

A class declared without sharing does not enforce record-level sharing in the same manner.

A secure Apex implementation should consider:

• Record-level access
• Object-level permissions
• Field-level security
• Sharing rules
• User permissions
• Appropriate execution mode

Modern Salesforce development also provides user-mode approaches for performing database operations while respecting the user's access.

I first determine whether Flow can meet the requirement in a maintainable way.

Flow is a good choice for declarative automation and business processes that don't require complex programming.

Apex becomes more appropriate when the requirement involves sophisticated business logic, complex integrations, advanced processing or programmatic control that would be difficult to maintain in Flow.

Agentforce is Salesforce's platform for building and deploying AI-powered agents that can work with business data and perform tasks.

A Salesforce Developer should understand Agentforce from an implementation perspective rather than simply knowing its definition.

Important concepts include:

• Agents
• Topics
• Actions
• Instructions
• Grounding
• Data access
• Security
• Integration

Grounding means providing the AI system with relevant and trusted business context so that responses can be based on current enterprise information.

RAG stands for Retrieval-Augmented Generation.

Instead of relying only on the model's general knowledge, relevant information is retrieved and supplied as context before generating an answer.

Developers should not stop learning Apex and LWC simply because AI is becoming more important.

A strong Salesforce Developer should understand:

The important change is that developers increasingly need to explain not only how they implement something, but also why they selected a particular architecture.

I would first evaluate whether the request should be synchronous or asynchronous.

For large processing, I would consider an asynchronous architecture rather than attempting all processing inside one synchronous transaction.

Important considerations:

• Payload size
• Governor limits
• Bulk processing
• Database operations
• Error handling
• Retry mechanism
• Monitoring

I would design the integration to be idempotent.

A unique external transaction or application ID can be used as the business key.

The Salesforce API should identify whether the request has already been processed before creating a new record.

1. Review debug logs and identify expensive operations.
2. Check for nested loops.
3. Check SOQL queries inside loops.
4. Check unnecessary DML operations.
5. Review automation triggered by the transaction.
6. Check Flow and other automation interactions.
7. Move appropriate processing to asynchronous Apex.
8. Optimize data structures and algorithms.

I would first understand whether the calls are actually necessary.

Possible improvements include:

• Combine related server operations.
• Use Lightning Data Service where appropriate.
• Use caching for suitable read operations.
• Load data only when needed.
• Lazy-load secondary sections.
• Reduce duplicate server requests.

I would evaluate Batch Apex and other appropriate large-data processing options based on the exact requirement.

I would also consider query selectivity, processing time, transaction limits, failure handling and monitoring.

The correct answer is not simply "Batch Apex." A senior developer should explain the architecture and trade-offs.

I would use field-level security to control access to the sensitive field.

Apex, UI and API access should also be designed so that the field isn't unintentionally exposed through another path.

A reliable integration should consider:

• Timeout handling
• Error logging
• Retry strategy
• Retry limits
• Idempotency
• Monitoring
• Failure notifications
• Dead-letter or manual recovery process

A high-level design could be:

The important consideration is that the agent should only access information that the user is authorized to access.

Security should be designed into the complete architecture.

• User permissions
• Record-level access
• Object permissions
• Field-level security
• Secure data retrieval
• Controlled agent actions
• Prompt and instruction design
• Testing with different user profiles

I would first understand the business requirement and transaction boundaries.

The final decision should be based on scalability, complexity, transaction requirements, maintainability and integration needs.

I would focus on architecture rather than simply writing Apex.

• Bulkified code
• Selective SOQL
• Appropriate asynchronous processing
• Reusable service classes
• Trigger handler architecture
• Secure data access
• Efficient LWC design
• Reliable integration patterns
• Centralized configuration
• Monitoring and error handling

Both are important, but architecture determines how the solution behaves as requirements, users and data volumes grow.

A senior Salesforce Developer should be able to explain why a particular solution was selected and what trade-offs were made.