Focus blocks
Periods where apps, sites, and window context align with meaningful work.
AI time tracker
Context-aware AI time tracking for Mac.
Your Mac knows which app was open. drifty helps explain what you were actually doing, classifying focus, drift, learning, and communication by intent and context.
The useful signal is not the app name. It is the intent.
YouTube can be a lecture or a drift spiral. Slack can be a launch thread or a distraction loop. Reddit can be research or avoidance. A useful AI time tracker has to look past the label on the window.
drifty focuses on context-aware classification so your reports explain why the day felt focused, fragmented, or scattered.
In drifty's first-party survey, users repeatedly pointed to a gap in current screen-time tools: they do not just want time totals. They want to know what the time meant.
What drifty tries to make reviewable.
The goal is not more raw logs. It is a cleaner explanation of where attention went.
Drift patterns
Repeated checks, rabbit holes, or context switches that pull attention away.
Mixed-use activity
Sessions where the same tool can be useful or distracting depending on the task.
Related drifty pages.
AI time tracker FAQ.
How is drifty different from app-level time tracking?
App-level tracking can tell you which app was open. drifty aims to classify the meaning of that activity, so the same app or site can count differently depending on context.
Does drifty require manual timers?
No. drifty is built around automatic Mac activity capture, with AI classification layered on top for focus and drift analysis.
Can I control how AI classification runs?
Yes. drifty is designed around processing choices such as hosted AI, local classification, and API key-based setup.