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How to find your ‘productive song’.

I can remember last year reading a post by Matt Mullenweg, lead developer of WordPress, about the way he works. In it he mentioned how he gets ‘into the zone’ whilst coding by listening to the same song over and over and over again:

Music is my muse and I listen to it all day. There’s a lot of jazz — Dexter Gordon and Sonny Rollins — but I’m also a big fan of Jay-Z, Beyoncé, and Method Man… When you’re coding you really have to be in the zone so I’ll listen to a single song over and over on repeat, hundreds of times. It helps me focus.

(my emphasis)

Music can have a massive effect on your productivity and it’s really important to find music that puts you in the zone that Matt talks about. I can only speak of what works for me, and what is currently my ‘productive song’, but I don’t think you’ll got too far wrong if you follow the suggestions below! :-p

1. Long

The track needs to be fairly long. Not your 3 minute pop song. You’ll get sick of that very quickly.

2. Repetitive

It needs to have a steady beat that’s not too fast and not too slow. I can’t tell you how fast that is (I think it probably varies between people). It’s probably about 100-120bpm for most of us, though.

3. Minimal lyrics

If you’re doing anything that involves writing words then you want as few lyrics as possible. Some lyrics are OK so long as it’s easy not to focus on them. 🙂

In addition, I’d suggest that even if one of your favourite songs of all time meets the above criteria that you don’t use it as your ‘productive song’. Why? The association it will carry will displace the original reason you liked it…

You may find that you wear out your productive song after a while and my need to find another one. What’s my ‘productive song’ at the moment? Slightly randomly it’s a track by Apparat called Arcadia (Telefon Tel Aviv Remix) <–Spotify link. Don’t ask how I came across it – serendipity! 😉

Image CC BY skippyjon

Music I’m running to at the moment,

CC BY-NC-SA el patajo

As those who have joined me in the #uppingyourgame project will know, I believe it’s important to get a ‘virtuous circle’ of productivity started. One of the best ways of doing this is by doing more exercise and, more specifically, running.

But running without music is like Laurel without Hardy, or Batman without Robin. And it’s important to get the music you run to right, as it makes running that much more motivational and enjoyable.

Recently I’ve been listening to one of two albums whilst running:

Morning run

My good friend and collaborator Nick Dennis pointed me in the direction of De La Soul’s Are You In? Nike+ mix on iTunes (£7.99) a few weeks ago. It’s great. The reason it’s perfect for running in the morning is that it starts off nice and gently with mention of getting up and ‘reaping what you sow’. Then, after some quality beats, around the 17-minute mark, steps it up a gear with exhortations to “Pick up the pace”. Awesome. 😀

Evening run

Being a big fan of mashups, I visit Mashuptown and The Hype Machine regularly. A couple of months ago I stumbled across The White Panda, a couple of guys mashing up hip-hop and rap with all kinds of stuff. The mashup album entitled Versus that they’ve released for free features NSFW language but is fantastic. I’m a massive fan of Passion Pit vs. T.I. What You Know About Little Secrets? Did I mention it’s free? 😉

Do you have runningmusic that you find motivational? Share it in the comments below!

LastHistory: a great way to generate Last.fm visualizations

(click image for larger version)

As you can see from the above visualization of my Last.fm history I’ve been using it for a fair while (since 19 March 2003 according to my profile). Recently, as I’ve gone Spotify-only, everything that I listen to is ‘scrobbled’ to Last.fm. Which makes the data from the latter part of 2009 onwards much more representative of my listening habits.

The time of day is down the side and putting your mouse over each ‘node’ links to other times you played that track. Sweet. 🙂

You can download LastHistory, the free Mac OSX app used to create this at: http://www.frederikseiffert.de/lasthistory/

(via FlowingData)

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