Catching Salesforce Custom Field Drift With the Postman AI Engineer
Blog post from Postman
Salesforce custom fields can silently alter API payload requirements, causing lead-creation requests to fail with `REQUIRED_FIELD_MISSING` errors and frontend applications to encounter unfamiliar response fields when teams are not notified of schema changes. The described approach uses Postman AI Engineer to inspect a failing request, response, collection, environment variables, and OpenAPI specification, identify a newly required Salesforce field, and generate a coordinated pull request updating frontend code, Postman requests, specifications, and drift-detection tests. Postman Agent Automations can then run on new repository pull requests to compare collection changes with downstream frontend artifacts, add required fields, remove obsolete usages, or update validation and types while leaving changes available for review. Important considerations include Salesforce field-level security, which may still prevent writes after a field is added; compile-time errors from regenerated required types; choosing an appropriate Postman agent for private networks; and separating automations by artifact type for clearer, faster results. The pattern can also be applied to other services with live schemas that change without explicit versioning, such as HubSpot custom properties and internal APIs.
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