Development & technology · Salesforce Development

AI training for Salesforce Developers

Salesforce orgs grow over the years into complex platforms of Apex classes, triggers, flows, Lightning Web Components and integrations. AI coding assistants and agents help Salesforce developers write Apex and LWC faster, generate test classes with meaningful coverage, account for governor limits early and move sprawling trigger logic into clean frameworks. They support SOQL optimisation, metadata analysis and the migration from Process Builder and workflow rules to Flow. Because Salesforce code must be multi-tenant aware, bulkified and security-conscious, AI needs targeted context and clear rules. In this course you learn to combine AI tools with Salesforce CLI, scratch orgs and your DevOps pipeline while reliably respecting sharing rules, field-level security and platform limits.

Who is this course for?

  • Salesforce developers working with Apex and Lightning Web Components
  • Salesforce architects and technical leads
  • Salesforce administrators who also develop
  • Integration developers building Salesforce interfaces
  • Salesforce consultancies and partner teams

Typical challenges we address

  • Governor limits, bulkification and trigger recursion cause hard-to-reproduce errors
  • Mandatory test coverage consumes a lot of time writing test classes
  • Mature orgs with overlapping triggers, flows and processes and no documentation
  • Security requirements such as CRUD and FLS checks and sharing are often forgotten in code

Practical scenarios from your field

Writing bulkified Apex

Generate trigger handlers, service classes and batch or queueable jobs that keep SOQL and DML out of loops, respect governor limits and apply patterns such as trigger frameworks consistently.

Generating test classes

Create meaningful Apex tests with test data factories, positive and negative cases, bulk scenarios and assertions that verify real logic rather than just coverage, including mocks for callouts.

Building Lightning Web Components

Develop LWC components with wire adapters, Apex controllers, Lightning Data Service and Jest tests, and migrate existing Aura components step by step. Accessibility and loading states are covered too.

Optimising SOQL and performance

Write selective queries, interpret Query Plan results, spot large data volume issues and propose alternatives such as custom indexes, skinny tables or asynchronous processing. This prevents timeouts as data grows.

Analysing org metadata

Evaluate retrieved metadata to document automations per object, dependencies between fields, flows and Apex, and unused components, and plan clean-up work. The result is finally up-to-date documentation.

Preparing for security review

Examine Apex and LWC for missing CRUD and FLS checks, SOQL injection, unsafe sharing settings and cross-site scripting, and implement fixes using user mode and stripInaccessible.

Possible hands-on projects

Automation map

A script that reads an org’s metadata and shows every trigger, flow and validation rule per object, including execution order, in one overview.

Test data factory generator

A tool that produces a reusable Apex factory from object and field definitions, with required fields and valid picklist values.

LWC dashboard component

A Lightning Web Component that aggregates an account’s key figures from several objects and displays them with filters and drill-down.

Data protection & compliance

Salesforce orgs hold customer and sales data: you learn to share only metadata and anonymised samples with AI services, protect credentials and connected app secrets, implement GDPR requirements for data retention and clarify licensing questions around generated code in AppExchange packages.

Prerequisites

You already develop in Apex or Lightning Web Components and have a working knowledge of the Salesforce data model, governor limits and Salesforce CLI.

Frequently asked questions

How well do general-purpose AI assistants know Apex and Salesforce specifics?

Current models handle Apex syntax and common patterns well. Weaknesses show up around governor limits, bulkification and org-specific objects. With rule files covering your trigger framework, naming conventions and security standards, plus retrieved metadata as context, results become far more reliable. In the course you build exactly this context for your org.

Should an AI agent deploy straight into our Salesforce org?

We recommend letting agents work in scratch orgs or sandboxes and promoting changes to higher environments through version control and your deployment pipeline. That preserves reviews, test runs and approvals. Production orgs should be reachable by agents read-only at most, using a restricted user. You practise this way of working hands-on in the course.

Request without obligation

We will get back to you within one working day with a confirmation or an alternative suggestion.

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Total €949 plus VAT