The Natural Selection of Tasks
Monday, February 6, 2017 at 10:10
Mark Forster in Articles, natural selection

When I first started developing Autofocus one of the ideas that was at the foundation of what I was trying to achieve was the natural selection of tasks. By this I meant that I wanted to find a method that would free our minds to naturally focus on what was important to us and leave the rest.

This never quite worked out with Autofocus or its successors. Recently I been spending quite a bit of time trying to work out what I was doing wrong.

Here are some of the conclusions I’ve come to: 

If you compare the above list with Autofocus you can see exactly why Autofocus ultimately failed to provide a long-term satisfactory answer.

The solution is not to make Autofocus more complicated or effective. It is to radically simplify it and remove even the faintest suspicion of compulsion from every part of it.

Current Method

What I have been working with over the last few days is a “Catch-all” list to which I add everything that I think of. I scan it continuously as one list from one end to the other, taking action on tasks that stand out and re-entering recurring and unfinished tasks.

At the end of the day (or beginning of the next) I remove pages on which there has been no movement during the day. This purely a housekeeping matter to keep the list manageable. It’s not a penalty or “dismissal”.

This is proving extremely effective. I’m getting a vast amount of work done without any of the usual heartache (or brainache) about what I should be doing.


As you will realise if you’ve been around my website for a bit, there’s nothing new about any part of this. In fact the difference is not so much in the method as in the mental attitude that goes with it. It’s a matter of learning to trust that your subconscious mind is quite capable of sorting through your tangled priorities without any interference from your conscious mind. In fact it does a much better job on its own.

Article originally appeared on Get Everything Done (
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