BackPrototype

Imagen-inspired photographer ops cockpit

EditFlow AI

Built around what Imagen does best: personal style consistency, faster culling, and accelerated post-production. Use this to plan each shoot from import to delivery with hard numbers before you start editing.

Quick Start

Workflow Inputs

Keep Target

704 photos

Manual Time

50.3 hrs

AI-Assisted Time

29.3 hrs

Time Reclaimed

21.1 hrs

Performance Snapshot

This setup projects 42% faster turnaround with AI-assisted culling and style-based editing.

Batch Count

6 batches

Batch Time

2.2 hrs total

Daily Output

176 finals/day

Pipeline Timeline

Ingest + Backup: 0.3 hrs (3%)
AI Culling: 0.3 hrs (3%)
AI Editing
AI Editing: 5.6 hrs (56%)
QA Review
QA Review: 3.5 hrs (35%)
Delivery Prep: 0.3 hrs (3%)
Ingest + Backup(0.3h)
AI Culling(0.3h)
AI Editing(5.6h)
QA Review(3.5h)
Delivery Prep(0.3h)
Total AI pipeline: 29.3 hrsvs manual: 50.3 hrs

Copy-Paste Editing SOP

EDITFLOW SOP
Genre: Portrait
Input volume: 3,200 photos
Target kept: 704 photos (22%)

1) Ingest + backup
- Copy cards to /RAW/{job_name}/ and mirror to backup disk
- Generate Smart Previews before culling

2) AI culling pass
- Auto remove blinks, duplicates, misfocus, burst repeats
- Tag shortlist with 1-star and reject obvious misses
- Keep target around 704 photos

3) AI edit pass
- Run personal style profile on all shortlisted images
- Edit in 6 batches (~22 min each)
- Prioritize skin tone consistency and straight horizons

4) QA + delivery
- Manual QA estimate: 3.5 hours
- Flag hero images for local brush/mask refinement
- Delivery target: 4 days (176 final images/day)

How this maps to Imagen AI research

  • 1. Personal AI profile concept: assumes your style stays consistent and improves over projects.
  • 2. Workflow end-to-end: culling, color correction and delivery schedule are planned together.
  • 3. Real output target: optimize for client-ready images/day, not only editing speed.
  • 4. Fast operator loop: review, tweak, and rerun your assumptions in under 60 seconds.