Work Track Iteration: Deliverable Versioning & Lifecycle Controls

As ideas progress from research into active incubation, users activate specialized Work Tracks (such as Articles, Coding Scaffolds, and Blog Entries). Because iterative AI generation produces successive drafts of documents, we introduced a structured versioning engine and fine-grained lifecycle management.

Key Enhancements

1. Document Versioning Engine

• Extended work_track_outputs with version, is_current, and model_used attributes.
• Whenever a workflow re-runs, previous deliverables are automatically archived with incremented version numbers, ensuring historical drafts remain viewable and restorable without overwriting.
• Added version badges (v1, v2, v3) in the UI displaying generation timestamps and attributing the specific LLM model used for each version.

2. Fine-Grained Deletion & Soft-Delete Lifecycle

• Added single-document deletion (DELETE /api/ideas/work-tracks/outputs/{output_id}) allowing users to delete specific versions or entire deliverable series.
• Introduced two-stage idea lifecycle controls:
  • Soft Trash (TRASHED): Moves discarded ideas to the Trash section while preserving full provenance and allowing one-click restoration.
  • Permanent Purge (DELETE_PERMANENT): Cascades deletion across categories, tags, processor runs, work tracks, external resources, and on-disk files with audit logging.

3. UI Tab State Persistence

• Resolved UI focus jump regressions where triggering asynchronous workflow executions inadvertently reset the active tab to the first panel.
• Synchronized tab navigation with window.location.hash, sessionStorage, and localStorage, providing persistent tab focus across page refreshes and asynchronous job updates.