Why I built MakerTime: an AI copilot to supercharge your focus
From tracking billable hours to becoming your personal deep work tracker — here’s how MakerTime evolved into something much more powerful than initially planned.
The Origin Story: More Than Just Time Tracking
When I first built MakerTime, I had a simple goal: automate my freelance time tracking. But after showing an early prototype to fellow developers, they helped me zero in on a much bigger problem — the constant battle against distractions during deep work sessions.
Sure, there are plenty of productivity trackers out there. I’ve tried many of them — RescueTime, Rize.io, you name it. While they’re useful tools, they’re missing something crucial: true understanding of what you’re actually doing.
The Problem with Traditional Productivity Tools
Let’s talk about Slack — the perfect example of why context matters. Consider these two conversations:
Bob: Hey, drinks tonight at 8?
Alice: Count me in! 🍻
versus:
Bob: Getting this weird TypeError in the auth flow
Alice: Can you paste the stack trace? Bob: Here you go: [stack trace details] Alice: Ah, looks like you’re trying to access a key on null…
Traditional productivity tools might flag both these conversations as “distractions” because hey, Slack is Slack. But we know better. That debugging conversation is legitimate deep work — you’re solving a real technical problem that moves your project forward.
Enter AI-Powered Context Understanding
This is where MakerTime takes a different approach. Instead of making simplistic judgments based on which application you’re using, MakerTime leverages Large Language Models (LLM) like Llama3 to actually understand what’s happening on your screen.
Reading documentation in your browser? That’s work. Debugging on Slack? That’s work. Planning weekend plans on Slack? Maybe save that for later.
The AI isn’t perfect, but it’s surprisingly good at distinguishing genuine work from distractions. And as LLM technology improves, so will MakerTime’s accuracy.
The Real Goal: Work Less, Achieve More
Let’s be honest — constant context switching doesn’t just hurt productivity, it forces us into longer work hours. Those extra hours come at the cost of life outside work — whether that’s hitting the gym, spending time with family, or simply recharging.
MakerTime aims to help you:
1. Measure your actual deep work time
2. Identify patterns in your distractions
3. Gradually increase your focused work efficiency
4. Know when you’ve genuinely accomplished enough for the day
Imagine getting a notification saying you’ve hit your deep work goal for the day. Instead of pushing through with diminishing returns, you can confidently wrap up and enjoy your evening — guilt-free.
Data-Driven Improvement
The current version of MakerTime (Alpha) focuses on daily deep work tracking, but I’m building toward a comprehensive system that will:
- Track focus patterns across different time scales
- Identify your peak productivity hours
- Spot common distraction triggers
- Suggest science-backed strategies to maintain focus
Future versions might even help identify systemic issues. For example, if you consistently lose focus during long compile times, maybe that’s a signal to optimize your build process or explore faster tooling.
Privacy First, Always
A note on privacy and ethics: We’ve all seen how productivity tracking can be misused for surveillance. That’s not MakerTime. I’m building this for makers who want to improve their own work habits, not for managers looking to monitor their teams.
Commitments:
- No stealth mode
- No hidden monitoring
- Your data stays local by default
- Full transparency about any future data sharing features
- You remain in control of your data
MakerTime Demo
Ready to Try It Out?
If you’re using macOS with Apple Silicon and want to help shape a new kind of productivity tool, head over to www.makertime.ai to download the alpha version.
