synthetic examples
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ShotSort
An AI-assisted macOS workflow for renaming, tagging, searching, quarantining, and organizing screenshots and local files.
Synthetic public view Screenshot review queue
Capture
AI suggestion
Quarantine
Search index
Fake screenshotsUndo pathEditable tags
low-confidence review
human-correctable memory
Recruiter answer
What proof does this case study show?
This case study shows AI implementation ability through confidence-aware AI suggestions, quarantine, human correction, undo, search, and local workflow adoption.
Role fit
- AI productivity workflow implementation
- Local-first AI tooling
- Operator enablement and adoption
Validation signals
- Confidence-aware suggestions
- Quarantine for uncertain output
- Undo and correction loop
Problem
Operators accumulate screenshots and local files faster than they can name, sort, retrieve, or trust.
What I Designed
Designed the intake, confidence, quarantine, undo, search, and sync workflows, then used AI-assisted coding to implement and iterate.
Validation
The key test was whether AI output stayed reviewable and easy to correct, especially when file names or tags were uncertain.
Public Handling
The public view uses fake screenshots and synthetic queues so real local artifacts never become portfolio material.
Synthetic artifacts
What the public proof can show safely.
These artifacts describe the workflow shape without exposing private data, credentials, logs, internal strategy, or real customer/user records.
Screenshot intake -> AI suggestion -> quarantine/review -> searchable local index.
Synthetic file queue with suggested names, tags, confidence, and undo state.
Low-confidence output stays quarantined until a human accepts or edits it.
No real local screenshots, file paths, or private desktop artifacts are public.
Positioning note
This work is framed as AI-assisted implementation. My ownership is problem definition, workflow design, evaluation criteria, validation, rollout, user feedback, and adoption. Coding-heavy pieces were built with AI coding assistance.
Good fit for teams that want AI-assisted productivity workflows designed around trust, review, and repeat use.