Here are the Salesforce Lightning Interview Questions (Basic to Advanced – 2026)
Salesforce Flow is a low-code automation tool that allows users to build complex business logic without heavy coding. It automates processes such as record updates, approvals, and guided user interactions. Flow is now the primary automation tool in Salesforce.
Salesforce provides Record-Triggered Flows, Screen Flows, Scheduled Flows, Autolaunched Flows, and Platform Event-Triggered Flows. Each serves different automation needs, from background processing to user-guided interactions.
A Record-Triggered Flow runs automatically when a record is created, updated, or deleted. It replaces Workflow Rules and Process Builder. It can execute before or after the record is saved.
Screen Flow provides a user interface with input fields and guided steps. It is commonly used for wizards, surveys, or service processes. It improves user interaction and data collection.
An Autolaunched Flow runs in the background without user interaction. It is triggered by another Flow, Apex, or API call. It handles backend automation tasks.
Scheduled Flow runs at a specific time and processes records in batches. It is useful for periodic updates or maintenance tasks.
Before-Save Flows update fields before the record is committed and are highly efficient. After-Save Flows are used when related records or additional actions must be performed.
Flow elements include Assignment, Decision, Get Records, Create Records, Update Records, and Loop. These elements define the logic and data manipulation steps.
The Decision element acts like an “if-else” condition in Flow. It directs the process path based on defined criteria.
Use the Debug tool in Flow Builder to simulate execution. You can view variable values and identify errors during runtime.
Apex methods annotated with @InvocableMethod can be called from Flow. This is useful when complex logic cannot be handled declaratively.
Subflows allow you to reuse Flow logic inside another Flow. They improve modularity and reduce duplication.
Use Fault paths to capture and manage errors. Display meaningful error messages and log failures when necessary.
Flow Trigger Explorer helps manage and visualize multiple record-triggered flows on the same object. It allows control over execution order.
Use entry criteria carefully and check conditions before updating records. Avoid unnecessary record updates that retrigger the Flow.
Design Flows to process collections rather than single records. Avoid multiple DML operations inside loops.
Workflow Rules are limited in functionality. Flow provides advanced logic, multiple actions, and better scalability.
Use Before-Save Flows for simple updates, minimize DML operations, and reduce unnecessary queries.
A Collection Variable stores multiple records in Flow. It is used for bulk processing and looping through records.
Flows can be deployed using Change Sets, DevOps tools, or Salesforce CLI. Proper testing is required before activation.
AI tools like Einstein Copilot assist in generating Flow logic and predicting automation outcomes. AI-driven recommendations improve process efficiency.
Use Flow for simple to moderately complex automation. Use Apex when advanced logic, heavy processing, or complex integrations are required.
Break logic into subflows, minimize DML operations, and ensure bulk-safe processing. Maintain clear naming conventions and documentation.
Flow respects object permissions, field-level security, and sharing rules automatically. Always validate user access before automation.
Use Platform Event-Triggered Flows for asynchronous processing. This enables real-time communication between systems.
Maintain documentation, naming standards, version control, and regular reviews to prevent automation conflicts.
Use meaningful names, limit complexity per Flow, document logic clearly, and avoid deep nested decisions.
Use batch processing logic and optimize filters to prevent performance issues. Monitor execution logs regularly.
Use debug logs, Flow error emails, and monitoring tools to track failures and performance.
Use Flow for maintainable, low-code automation and Apex for complex business logic. Architects must decide based on scalability and long-term maintenance.
AI transforms Flow automation by auto-generating logic, suggesting optimizations, and enabling predictive, intelligent process automation.
Scalable enterprise Flows are designed using modular subflows, bulk-safe logic, minimal DML operations, and clear governance standards.
Event-driven automation is implemented using Platform Event-Triggered Flows for asynchronous, real-time system communication.
Balancing Flow and Apex involves using Flow for maintainable low-code automation and Apex for complex logic and integrations.
Optimizing Flow performance for large data volumes requires selective record filters, batch processing, and avoiding DML operations inside loops.
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