Time tracking in the AI age
Working with AI agents broke the assumption every time tracker was built on: that work means a moving keyboard. When you direct an agent and it runs for 40 minutes, you're working, but no key is pressed, so the tracker drops the time. This guide explains the problem and how to fix it.
Why AI-assisted work breaks old trackers
Traditional time trackers fall into two camps, and AI-assisted work defeats both. Manual timers(like Toggl or Harvest) depend on you remembering to start and stop them, and when you're deep in directing an agent, you forget. Activity trackers watch keyboard and mouse input and mark you "idle" after a minute of stillness, which is exactly what supervising a running agent looks like. Either way, the hours you spend attending an agent vanish from the record.
The cost is concrete. A developer who runs several long agent tasks a day can lose two or more billable hours daily to this misclassification. At a typical rate, that adds up to tens of thousands of euros a year.
The vocabulary that fixes it
The fix starts with better categories. These are the terms Atend uses, and what each one means:
- AI-age time tracking
- AI-age time tracking is time tracking designed for work where a person directs AI agents that then run on their own. Its defining problem is that a running agent produces no keystrokes, so traditional trackers misread the supervising person as idle and drop billable time.
- Attending time
- Attending time is the time a person spends supervising or waiting on a running AI agent: present and on the hook, but not typing. It is billable work, yet activity-based trackers classify it as idle because there is no input.
- The idle gap
- The idle gap is the billable time lost when a tracker equates 'no keyboard input' with 'not working'. In AI-assisted work this gap is large, because long agent runs are normal and produce no input.
- Three-state classification
- Three-state classification sorts every moment into Engaged (actively working), Attending (waiting on a running agent, billable), or Away (genuinely stepped out, not billed), instead of the two states (active/idle) that older trackers use.
- Metadata-only capture
- Metadata-only capture records signals about activity (whether there was input, the foreground app's name, whether an agent is running) but never the content of work: no keystrokes, no screenshots. It is the privacy-respecting opposite of employee-monitoring 'bossware'.
How three-state tracking works in practice
- 1Capture signals, not content. A lightweight desktop agent reads input activity, the foreground application's name, and whether a known AI agent is running. Metadata only.
- 2Classify into three states. The server reconstructs the day as Engaged, Attending, or Away, counting agent-attending time as billable while excluding time you genuinely stepped away.
- 3Approve, then export. You confirm a day, or a whole month at once, and export a rounded, client-ready timesheet or invoice.
Is automatic tracking the same as surveillance?
No. Those are different things, and the difference is what gets recorded. Surveillance tools ("bossware") capture keystrokes and screenshots to watch a worker. Metadata-only tracking records only that work happened (input or no input, which app, whether an agent ran), never the content. Atend is built metadata-only on purpose, because most of the time the person being tracked is the user themselves.
See your real day, automatically
Atend reconstructs it for you, including the hours you were attending an agent.