Salesforce / AIGIS resources

Salesforce architects should review AI context like a new integration boundary.

For Salesforce architects, an LLM prompt is a new integration surface with its own context and audit boundary.

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Executive read

The short version, before the deep dive.

Inspect object, field, and record checks as part of the AI path.

Review field stripping before prompt construction.

Ask how callbacks, audit logs, and provenance records are secured.

Choose a proof workflow with meaningful sharing differences.

Analysis

What matters

Architecture review points

Treat the AI runtime as middleware that must respect Salesforce's permission decisions before it composes context.

The review should include how the runtime authenticates, checks access, filters fields, and records provenance.

Proof workflow design

Pick a workflow where two users should get different allowed context.

The result should show not just different answers but different governed input boundaries.

Resource packet

Turn this into a review worksheet.

Evidence packet

Permission-Provenance Evidence Packet

Capture user context, system of record, enforcement tier, stripped fields, model route, response, hash marker, and fallback notes.

Salesforce is the production proof path. ServiceNow and SAP are design-partner co-development paths with asymmetric enforcement that must be disclosed in diligence.

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