Current Project · AI life logging ecosystem

TracklyReborn

TracklyReborn remodels life logging around the moment of capture. The work is less about forms and more about quickly saving material that can be structured, reviewed, and assisted by AI later.

AI ProductizationiOSShortcutsLocal Data

Narrative

Design and engineering judgement

Product frame

The hard part of logging products is sustained use. Shortcuts, Action Button, multi-image capture, and AI assistance all reduce the cost of each entry.

Engineering frame

The main app owns local data and visual experience, system entry points handle frequent capture, and prompt/VLM settings bridge fuzzy input with structured records.

Design frame

The project is about merging native iOS workflow surfaces with AI, instead of adding AI as a separate conversation layer.

System

Components and visibility

Component	Type	Visibility	Role
TracklyReborn app	iOS app	Private source	Local data, capture flow, and core product experience.
Public TestFlight	Distribution	Public	Public testing and actual usage entry.
Shortcuts / Action Button	Workflow surface	Product feature	Reduces friction for frequent capture.
TracklyPrompt	Prompt material	Private source	Internal rules for AI-assisted input.

Public URLs

Public surfaces

Product test TestFlight

Public testing entry for the AI-assisted life logging workflow.

testflight.apple.com/join/aQ64Cnfv Notion Getting started

Usage-facing documentation for the current app experience.

www.notion.so/267c1b36c40180ec9489d4f84ef1c079 Media YouTube demo

Public video surface for seeing the AI-assisted logging workflow and interaction model.