AI Tool Calling Pattern for Salesforce Apex
How to implement AI tool calling (function calling) in Salesforce Apex, working around the DML-before-callout transaction limitation with a multi-transaction follow-up pattern.
How to implement AI tool calling (function calling) in Salesforce Apex, working around the DML-before-callout transaction limitation with a multi-transaction follow-up pattern.
How to pull, manage, and analyze Salesforce Apex debug logs using SFDX CLI and Claude Code for fast root cause diagnosis.
Core Apex programming — classes, interfaces, triggers, governor limits, and order of execution.
Salesforce approval workflows — multi-step approvals, routing, actions, and integration patterns.
Using Custom Metadata Types to externalize AI chatbot configuration -- model settings, behavior rules, and UI prompts -- with cached Apex queries and fallback defaults.
Data operations in Salesforce — import/export, migration, quality, and storage optimization.
Schema design, object and field configuration, relationships, and platform configuration patterns.
Salesforce Flow automation — screen flows, record-triggered flows, scheduled flows, and advanced patterns.
Reference articles for building Lightning Web Components — lifecycle, events, data binding, wire adapters, and component design patterns.
Salesforce-native AI capabilities — Data Cloud, Einstein, Agentforce, Prompt Builder, and the Trust Layer.
A strategic guide to implementing CI/CD for Salesforce orgs — covering environment progression, tooling, workflows, and how to incorporate admin-driven declarative changes into a source-controlled pipeline.
Salesforce security model — access control, sharing, permissions, and programmatic enforcement.
Querying and accessing Salesforce data — SOQL, SOSL, relationships, and DML patterns.
Apex testing strategies — test classes, data factories, mocking, and deployment requirements.