How a Technical Co-Founder Spends His Time

The biggest thing I learned when analyzing my time, which I wish I had recognized earlier, was that I can have two types of productive days:<p>I can have days where I do a million small things and hop quickly from task to task.<p>Or, I can have days where I work on big issues and should not be interrupted by small issues.<p>But, if I <i>think</i> I&#x27;m going to have a day where I work on a big thing and it turns out I get interrupted by a million little things, I end up doing nothing well and end up very unproductive.

The notion that a 130h work week is admirable, desirable, sustainable or useful is ridiculous and should be criticised every time it&#x27;s raised.<p>Unless you&#x27;re working for yourself or working in a job where your contract compensates you by the hour then investing such huge swathes of time I think is destructive.<p>There is a reason workers united, fought and were martyred for the 8 hour work week and the creeping clawback by industry is a problem.<p>That aside, very interesting to see such a consistent time keeping record.

Thanks for sharing this. Is the metime code publicly available? I&#x27;m the CTO of another small tech company (<a href="https:&#x2F;&#x2F;sourcegraph.com" rel="nofollow">https:&#x2F;&#x2F;sourcegraph.com</a>) and I&#x27;m also a bit obsessive about time tracking.<p>I wrote a small open-source CLI that gives you a CPU-profile-like view of time spent on your computer: <a href="https:&#x2F;&#x2F;github.com&#x2F;sourcegraph&#x2F;thyme" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sourcegraph&#x2F;thyme</a>. Thought I&#x27;d share since OP and others here might find it useful, and I&#x27;d love to hear any feedback.

(Author here.) It&#x27;s great to see my write-up on HN, and I&#x27;m glad to see it generating good discussion here.<p>Since several people have asked, I have now made my &#x27;metime&#x27; tracking app open source: <a href="https:&#x2F;&#x2F;github.com&#x2F;jdleesmiller&#x2F;metime" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;jdleesmiller&#x2F;metime</a><p>Being in London, I have just woken up, so I will now be more able to answer any questions!

Off-topic: I really like Overleaf. It removes the barrier of installing all of the compiler, editor and dependencies and allows anyone to jump right in and and start typing manuscripts. That&#x27;s why I always recommend Overleaf to anybody looking to learn Latex initially.

It&#x27;s interesting to note that the meetings time decreased as the management time increased, because often the two are strongly correlated.<p>In my experience meetings and management time grow proportionally, since meetings are a good way to talk with the team, set expectations and review the results. Or, in other words, some meetings == management.

In the 5 seconds of thinking what I&#x27;d wish I&#x27;d seen before I clicked the link:<p>Pre MVP: 80% dev, 20% biz dev<p>Pre Revenue: 20% dev, 80% biz dev<p>Pre Profit: 80% hiring, 20% dev<p>Profitable: 100% biz dev

&gt; My app had some simple charting built in but no real analysis. It’s only now, six months later, that I’ve had a chance to really get into the dataset<p>I&#x27;m interested to find out if the data influenced the OP from week to week (month-to-month) during the collection phase? Did it influence his keeping up his development by shifting it to weekends? Or was there other catalysts to that? What were they? Were there planned development milestones? were they sized?<p>Fascinating article.

Awesome project! I&#x27;m a big fan of using econometric methods in Quantified Self -type analysis.<p>A couple of thoughts on your regressions:<p>Keeping holidays in the data seems counterintuitive. I&#x27;m fairly sure just from eyeing the graphs that the increase in your work week might reach statistical significance if you were to use a regression method more resistant to outliers, like Least Trimmed Squares.<p>Another idea - in microeconometrics it&#x27;s standard to use some type of Poisson regression four count data, which this could potentially qualify as.<p>And furthermore, I would have loved to see some sort of distributed lag model of the timeseries (or at least a scatterplot of all activities against each other) to see which ones tend to co-occur.

I work as a freelancer (Europe) and I think I work reasonably hard. But is really difficult for me to honestly log more than 10-15 dev-billable hours during the week. The rest of the time is spent in chat and learning &#x2F; playing with a new things.

Interesting article, pretty remarkable to be that committed to the time tracking -- I can barely stick with using the pomodoro technique for longer than a few days in a row...<p>I hope OP continues to grow the dataset. Will be interested in a follow up later on!

I recommend not only track your time, but also write down what you do, and have project-names. Using this I can give very accurate estimates by going back and see how long time things took. And it makes it easier to plan things. Also if you are in an early startup it&#x27;s good to have this so your co-founders know how much you work and on what. And if you are employed you can use it to tell your boss exactly what you did (and why it took so long). There&#x27;s a saying though, that you&#x27;ll spend 50% of your time documenting what you do.

*Or her time.