Tomatick: Yet Another Attempt to Rethink Productivity 🎯

Meh… what’s with the name? Well, it’s a combination of “tomato” and “tick” (as in a timer) 🤷 Dad joke? Maybe.

The Problem with Traditional Productivity Tools ⚠️

Every productivity tool promises to make you more efficient. Most fail. (At least, that’s my experience.) Why? Because they fundamentally misunderstand how human cognition works. They treat our brains like simple input-output machines: set a timer, get focused work. Reality is far more complex.

The average knowledge worker:

  • Loses ~23 minutes to each context switch, though estimates vary ⏱️
  • Makes approximately 35,000 decisions per day, experiencing gradual decision fatigue 🧠
  • Has varying optimal focus periods, which may not align with specific time management techniques ⚖️
  • Can experience perfectionism-induced paralysis (This isn’t quantified, I don’t think. But perfectionism is my problem. How, why and details are for another post, but I think this thing called ‘being a perfectionist’ is seen as a good thing in our society. I’m a victim of it, and perfectionism, IMHO, is a mental disorder. I’m not sure if there’s a nicer way to put it, but I’ll choose to be black and white about it.) 🔒
  • May benefit from focusing on energy management alongside time management ⚡

Maybe a different approach: Cognitive-First Design 🎯

I’ve tried numerous popular productivity tools - Forest, Focus@Will, Be Focused, and countless others. While they’re well-designed, they all seem to share the same fundamental limitations:

  1. They treat users as input-output machines: “Set a -minute timer, get focused work”
  2. There’s no built-in way to measure what actually works for you personally
  3. They require you to manually track and analyze your productivity patterns
  4. The accountability features are either non-existent or feel like busy-work

The irony? A productivity tool should work for you, not the other way around. You shouldn’t need a separate system just to figure out if your productivity system is working.

So instead of building yet another timer, I started with a different question: “How does the brain actually work during complex cognitive tasks, and how can we design around that?”

A new tool? What’s inside? 🏗️

The system is built on three core principles:

  1. Neural Pattern Recognition 🧩

    • Monitors cognitive load in real-time
    • Adapts to individual work patterns
    • Predicts optimal task sequencing
    • Prevents decision fatigue through intelligent suggestions

  2. Strategic Momentum Building 🚀

    • Engineers task sequences for optimal flow state entry
    • Minimizes context-switching costs
    • Maintains cognitive momentum while preventing burnout
    • Optimizes recovery-progress ratios

  3. Predictive Burnout Prevention 🛡️

    • Analyzes energy expenditure patterns
    • Forecasts cognitive fatigue
    • Suggests strategic breaks based on neural load
    • Maintains sustainable progress velocity

Memory.. Is it ever enough? 🧠

Traditional productivity tools treat each session as isolated. But our brains don’t work that way. We build on previous experiences, learn from patterns, and develop intuition over time.

This is where the mem.ai integration becomes crucial. It’s not just about storing notes; it’s about building a cognitive map of your productivity patterns:

  • Temporal Pattern Analysis: Understanding how your productivity fluctuates over time
  • Context-Aware Optimization: Learning which tasks work best in which contexts
  • Strategic Insight Accumulation: Building a personalized productivity profile
  • Cross-Session Pattern Recognition: Identifying higher-order productivity patterns

PS: I’m not affiliated with mem.ai, but I kinda like their product for these good reasons:

Who needs a second brain? 🤝

  • mem.ai endeavors to create a web out of your thoughts and ideas. Thanks to LLMs, you can interact with this knowledge web naturally, reducing cognitive load on your brain. While their product is still in alpha (they call it ‘production grade’, but it’s very rough around the edges), I haven’t found anything else that approaches personal knowledge management quite this way. Not yet, anyway. Did someone say Obsidian? Yeah sure. If you have the time to make it work for you AND the time to work to make it work for you, go for it.
  • Your tasks don’t exist in isolation; they’re connected to your notes, research, and thoughts
  • Temporal search means you can find task patterns across time (“What was I working on last quarter?”)
  • Chat with your notes to understand how your productivity intersects with your knowledge base

Perfect Integration 🔄

  • Natural language task logging that becomes part of your knowledge graph
  • Seamless connection between your productivity data and your broader knowledge base (should you choose to go all in with mem.ai, that is)
  • Future-proof your productivity data—it’s all searchable and connected
  • Cross-pollination between your tasks and your notes (because context matters)

Long-term Value 📈

  • Your productivity data becomes part of your personal knowledge base
  • Understand how your tasks relate to your broader goals and notes
  • Query your past productivity patterns alongside your notes
  • Build a genuine understanding of your work patterns over time

Is there some science behind this? 🔬

1. Flow State Engineering ⚡

The system uses pattern recognition to optimize for mythical flow state entry and maintenance:

  • Task Sequencing: Orders tasks (at least attempts to) to maintain optimal cognitive load. Well, it’s a ‘copilot’ (thanks for democratizing that word, Mr. Satya Nadella!) so it’s only ‘suggesting’. You’re in control, of course.
  • Context Preservation: Minimizes disruptive context switches
  • Energy Management: Aligns complex tasks with peak energy periods
  • Recovery Optimization: Engineers breaks for maximum cognitive restoration

2. Decision Fatigue Prevention 🛡️

Rather than overwhelming users with choices, the system:

  • Suggests tasks based on current cognitive state (Again, as a copilot, it attempts to do this for you. You’re in control, of course.)
  • Batches similar tasks to reduce context-switching
  • Provides clear, actionable next steps
  • Eliminates decision points during focus periods

3. Sustainable Progress Optimization 📊

The system’s core innovation is its focus on sustainable progress:

  • Momentum Building: Creates self-reinforcing progress loops
  • Energy Conservation: Prevents cognitive resource depletion
  • Strategic Deloading: Implements planned recovery periods
  • Progress Velocity: Optimizes for long-term sustainable progress

Real-World Impact 📊

Early testing shows promising results (this is all just me, btw😁 and the sample period is ~3 months, with each workday being ~8-10 hours, including professional work, side projects & personal work):

  • 31% reduction in context-switching costs
  • 47% improvement in task completion satisfaction
  • 28% decrease in reported decision fatigue
  • 42% increase in sustained flow state periods

More importantly, what I’ve noticed:

  • Reduced perfectionism-related delays ⚡
  • Better energy management throughout the day 🔋
  • Improved work-life balance. It’s something when a tool says - “Can you please call it a day? You’ve been killing yourself. It’s not the end of the world if you don’t finish that one thing today.” ⚖️
  • More consistent progress on complex projects 📈

Where I want to take Tomatick from here 🚀

The current implementation is just the beginning. On my ever-growing list of things to do:

  1. Enhanced Pattern Recognition

    • Deeper understanding of individual work patterns - integrating with health data from fitness devices (garmin first, maybe fitbit later) to better understand correlations between health metrics, productivity, and stress-inducing activities
    • Getting better at predicting optimal task sequencing
    • Getting better at forecasting cognitive fatigue and achieving a sustainable pace

  2. Expanded Memory Integration

    • Richer knowledge graph integration
    • Better temporal pattern analysis (i.e., getting insights from questions like “when I worked on something similar to last time, what worked and didn’t work for me?”)
    • Enhanced cross-session optimization

  3. Personalized Cognitive Models

    • Individual-specific optimization
    • Adaptive learning systems

Conclusion: Beyond Simple Time Management 🎯

My intentions are for Tomatick to represent a fundamental shift in how we think about productivity. Instead of working to fit into a productivity system, I want to build a system that works with how our brains actually work.

The future of productivity isn’t about working harder or longer or clichéd bullshit like “work smarter, not harder”. IMHO, it’s about working in harmony with our cognition—which is influenced by many factors—to maintain sustainable progress and prevent burnout before it happens.

So, how can you use this? 🤔

If you’ve read this far, thanks for taking the time. If you’re interested in trying it out, Tomatick is FOSS and available here:

PS:

  • Tomatick is a CLI tool
  • This is a tool I built for myself to help me build something else I’m cooking up. So, it’s work in progress.
  • If you prefer an app/website, sorry for wasting your time 🤷