Some SOQL queries in our org used to run quickly, but as data volume increased, response times degraded. The queries themselves haven’t changed much, and indexes exist on some fields. I’m trying to understand what causes SOQL performance to decline ...
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Many Salesforce teams begin solutioning by listing objects, fields, and relationships.While technically correct, this approach often misses how work actually flows across users and systems.The result is a build that looks structured but feels disconnected in daily use.
I’ve already removed SOQL queries and DML operations from loops in my Apex code. Despite that, I’m still hitting limits in real production scenarios with large datasets. The logic itself isn’t very complex, but the limits seem easy to hit. ...
Deployments move metadata, not configuration completeness. Permission sets, licenses, feature toggles, and org-level settings are often excluded. As a result, deployed features may exist but remain inaccessible or inactive.
We started with a few simple record-triggered Flows, and they worked well initially. Over time, more conditions, paths, and updates were added to handle new requirements. Now debugging and updating these Flows feels risky and time-consuming. I’m trying to understand ...
Flows worked before deployment but not after. I want to understand why.
Custom Metadata is often used to externalize configuration from code.However, it struggles when logic involves multiple conditions and outcomes.This limitation becomes visible as rule complexity increases.
