An AI agent can complete a useful piece of work in one turn or keep working across an afternoon. Either way, the invoice later needs a clearer answer than “the agent was busy.”
Which client was the work for? When did it begin? Was the agent actively working or waiting for input? What result was delivered? Is that time covered by the client agreement?
AI agent time tracking is the habit of connecting that work to a project timer and a reviewable time entry instead of reconstructing billable hours from chat history.
TaskTime Pro gives a same-device agent structured timer and time-entry tools while the visible browser app remains the source of truth.
Why AI agent work needs a real timer
Chat timestamps are not a dependable billing record. A conversation may contain planning, waiting, failed attempts, unrelated questions, and the final deliverable in the same thread.
A project timer creates a cleaner boundary:
- Start when the agreed client work begins.
- Keep the timer attached to a specific project and task.
- Pause while the agent is genuinely blocked or waiting.
- Stop when the output is ready for review.
- Review the resulting time entry before treating it as billable.
The timer does not decide what you may charge. It gives you an accurate record from which to make that decision.
If you want the broader product and security overview first, read AI Agent Task Management for Freelancers: TaskTime Pro Agent Bridge. This guide stays focused on tracking agent work from timer start to billable-hours review.
The AI agent timer loop
The cleanest time record starts before the agent does the work.
- Ask the agent to inspect active projects and existing tasks.
- Reuse the right task, or create a specific one if it does not exist.
- Check active timers before starting another.
- Start or resume the timer for the selected task.
- Do the work.
- Pause the timer during a genuine interruption.
- Stop the timer when the output is ready for review.
- Open the project or recent time entries in TaskTime Pro.
That sequence keeps the timer tied to the client context and gives the agent clear instructions about when tracking should end.
A good task is concrete enough to recognize later. “Website work” will not help much at invoice time. “Review checkout error states and prepare fixes” tells you what the recorded time was for.
Use a prompt that protects the client boundary
An agent works better when the prompt states both the goal and the limits:
Use TaskTime Pro to find the Acme website project and inspect its open tasks.
Reuse the task for checkout error states if it exists; otherwise create it.
Check active timers, then start or resume only the timer for that project.
Do not change timers belonging to other clients.
When the work is ready for review, stop the timer and open the project view.For a shorter working session:
Before starting, use TaskTime Pro to confirm the task and current timer state.
Track this work against the correct client project.
When finished, stop the timer, summarize the created time entry,
and leave invoicing for a separate review step.These prompts turn “track AI agent work” from a vague intention into a repeatable operating rule.
What happens across longer agent sessions?
Real agent work does not always fit inside one message.
A coding task may continue across several turns. You might refresh TaskTime Pro, close the tab, return later in the same browser profile, and then ask the agent to stop the original timer.
The current TaskTime Pro agent integration is designed for that longer loop. A normal tab refresh can resume the current session. Closing and reopening TaskTime Pro in the same browser profile can reconnect to the same live bridge using browser proof of possession instead of storing a reusable bearer token.
There is still an honest boundary: if the bridge or managed Gateway restarts, the old in-memory authorization is gone and the browser must pair again. That is a security property, not a timer reset. The timer itself remains part of the TaskTime Pro workspace.
OpenClaw users can use the native TaskTime Pro OpenClaw integration so one Gateway-managed bridge remains available across ordinary agent turns. Claude Code and other MCP hosts can use the documented plugin or standalone bridge paths.
Time records still need human judgment
An AI agent can help keep time tracking consistent. It cannot decide what your client agreement allows you to bill.
Pause or stop a timer when the agent is:
- Waiting for credentials or a human answer
- Retrying a failed approach with no useful output
- Running unrelated work for another client
- Producing exploratory work you do not intend to charge for
If several agents are working across different projects, TaskTime Pro can keep multiple project timers active, with one timer state per project. The multi-agent time tracking guide explains that pattern in more detail.
The record is there to support an honest invoice, not to turn every minute of compute into a billable minute.
Why TaskTime Pro uses structured timer actions
TaskTime Pro exposes named actions for checking, starting, pausing, resuming, stopping, and updating timers. The agent does not have to guess which visible stopwatch belongs to which project.
The browser still applies the same timer rules used by the normal UI:
That matters for timer behavior:
- Starting a timer should not replace another timer accidentally.
- Pausing should preserve elapsed time without creating an entry.
- Stopping should create exactly one corresponding entry.
- A retry should not create duplicate time records.
- Time entry edits should respect billing and overlap rules.
The agent gets a focused time-tracking interface; you keep one consistent work ledger. The local MCP agent bridge documentation covers the underlying pairing, scopes, and browser-owned command model.
Quick answers
Can an AI agent track its work in TaskTime Pro? Yes. After local pairing, a supported agent can check timers and start, pause, resume, or stop work against a selected project task.
Can TaskTime Pro track more than one agent workflow? It can keep multiple active timers across different projects, with one timer state per project. Each agent or workflow must respect the correct client and project boundary.
Can an agent continue tracking time across several turns? Yes. The timer persists in TaskTime Pro independently of one chat turn. Browser refresh and same-profile reopen recovery are supported while the same local bridge remains alive.
Is all AI agent time billable? No. Billability depends on the client agreement and the useful work delivered. Pause or exclude waiting time, unrelated work, and exploratory output you do not intend to charge for.
Can this work with Claude Code, Codex, or OpenClaw? Yes. TaskTime Pro provides dedicated guidance for Claude Code and OpenClaw, while the standalone local bridge works with compatible MCP hosts such as Codex.
Start with one dependable loop
Do not begin by asking an agent to reorganize every project.
Start with one task: find it, start the right timer, do the work, stop the timer, and review the entry. Once that loop feels dependable, add project planning, reports, and invoice preparation.
The TaskTime Pro MCP quickstart covers setup and pairing. The agent security guide explains scopes, approvals, local access, and revocation.
Good AI agent time tracking is not about billing every minute an agent runs. It is about preserving enough context to review the work honestly and turn the right time into a defensible client record.