As developers in 2026, our productivity isn't linear anymore, we dispatch multiple tasks that run simultaneously. Yet, most time trackers still treat work like a single-threaded process, failing to account for the reality of modern, AI-driven work.
I built TripleTime because I was tired of hacking my timesheet to account for the fact that I’m effectively running three parallel agents, while in a meeting, all at once.
The problem: traditional trackers are single-threaded
Most time tracking software is built on a legacy assumption: you start a timer for Task A, then stop it to start Task B.
But if you’re using Claude Code, Gemini CLI, or other AI agents, your workflow looks more like an orchestrated cluster:
- Thread 1: A Claude agent is refactoring a legacy module for Client A.
- Thread 2: A Gemini session is generating content for Client B.
- Thread 3: You’re in a Zoom call discussing architectural debt for Client C.
Technically, you’re delivering value across three different buckets simultaneously. In a traditional tracker, overlapping entries usually trigger a validation error, or they treat concurrency as a messy "edge case". We’ve multi-threaded our output, but our billing is stuck in a synchronous loop.
Why "digital stopwatches" are a DX nightmare
For the modern Orchestrator, manual logging is barely possible. If you spend 10 minutes spinning up three agents that each run for a different amount of time, traditional manual logging becomes a secondary job.
If you forget to "punch out" because you were deep in a bug-hunt rabbit hole, your data becomes junk. We need a system where concurrency is a first-class citizen and the tracking happens through full, automated integration.
Enter TripleTime: time tracking for the agentic era
I designed TripleTime to feel less like an "HR tool" and more like a high-performance, easy to use spreadsheet that connects to your terminal.
1. Native concurrency
In TripleTime, overlapping logs aren't an error—they're the point. The UI is built to visualize parallel work streams so you can see exactly where your "human" time and "agentic" time intersect.
2. The MCP & plugin architecture
This is the core for developers. TripleTime supports the Model Context Protocol (MCP) and offers a Claude plugin.
Your agents can log their own time directly through the API. For example, you can tell an agent to fix a bug and track the task in TripleTime; the agent then pings the API to start the log and keeps track of the task automatically. By the end of the day, your timesheet is essentially drafted based on actual IDE and CLI activity.
3. Low-latency manual entry
For the time you spend in meetings or brainstorming, I’ve kept manual entry dead simple. It’s a spreadsheet-like environment where speed and simplicity are prioritized over clunky dropdowns.
4. The "staging area" for your billables
TripleTime acts as a high-speed buffer for your data. Once your concurrent hours are logged, you can sync them to the "Source of Truth" your client or company uses, such as Jira, Linear, or Teamleader.
It even attempts to automagically find the related task in your target system based on your log's description.
Need to sync to a platform we don't yet support? Please let me know, I prioritise building syncs for people that actually use the software.
The future of work is parallel
The billable hour isn't dead, but the way we fill those hours has changed. If your tracker doesn't understand that you can command multiple models simultaneously, it’s costing you mental clarity and money.
TripleTime is currently being built in the open. I’m building this for the developers who are tired of fighting 2010-era timers while writing 2026-era code.
Try it out
Check out TripleTime for free at tripletime.site.
I’m looking for feedback: What integrations are missing from your workflow? How are you handling agentic billing right now? Let's talk in the comments.