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AI audit logging (weekly) - model-training log capture

StageEstimated
StatusDeferred
Design statusIn progress
Estimate1w (M)
ConfidenceMedium
LinearPIN-836 ↗ PIN-117 ↗
Linear statusDone
DesignDesign ↗
Linear epicPlatform Foundation
ModuleSettings & Admin ↗

Status check: deferred, but shipped work exists

This surface is marked deferred, yet Linear shows PIN-836 and PIN-117 as Done. Confirm whether it actually shipped (move the status off deferred) or only the remaining scope is deferred. Flagged for reconciliation.

Priority: High

Scope

Pre-launch review confirming AI calls (Cara, Smart Import, estimate/scope extraction, RFI/SOV drafting) are safe for production from a data-governance standpoint, backed by an audit-log interceptor that captures every AI request. Verifies the provider's no-training / zero-retention terms and reviews what the corrections-learning loop persists. (Source: PIN-836, PIN-117.)

Acceptance criteria

  • Every AI call site logged with actor, timestamp, and request/response metadata, traceable to user + entity
  • Provider data-handling posture confirmed: no-training / zero-retention terms in force for the production API key
  • Field-level change diffs + business context (bid/project/estimate/org) captured on each audit entry
  • Entries tagged by source (user action vs system vs integration) so training-data feeds can be isolated
  • Learning-from-corrections loop reviewed for what's persisted and whether it's acceptable for pilot
  • Admin-only bulk export of the audit log for compliance/training-data extraction
  • Written go/no-go verdict required before AI features go live in production

Conor's comments

Ivan & Jonny question. Not part of design

Notes

INFRA / NO DESIGN - not a Claude Design surface; build item, not awaiting design sign-off. Meeting action item; AI model training depends on it

Open question for Conor

Confirm robust AI logs before go-live (pre-prod blocker)