Kent Beck’s Paint Drip People

Kent Beck’s Paint Drip People

PaintDrip22

I repeat Kent Beck’s “Paint Drip People” article here for the benefit of all those having trouble finding or accessing it, or just hate having anything to do with Faceberks.

Keith Adams worked on kernels at VM Ware. Then virtual machines. Then search performance at Facebook. Then the HHVM implementation of PHP. Then machine learning. Now he’s Chief Architect at Slack. In between he worked on hundreds of little projects that lasted hours or days or weeks. Keith is a Paint Drip Person.

I was a big fan of the T model of skills, introduced by David Guest in 1991: know about a lot of things, be really good at one. The more I taught it, the more unhappy I got with the metaphor:

  • Skilled people are good at several things.
  • Skilled people’s interests develop over time.
  • Skilled people don’t plan their next focus area. Sometimes it seems completely unrelated to their previous focus area.
  • Skilled people are always exploring, just for the sake of curiosity.
  • Skilled people resurrect interests sometimes.

All of these metaphor fails led me to the paint drip model of skills.

  • You draw a brush across the top of the canvas.
  • Sometimes enough paint accumulates that a drip starts to roll.
  • Once a drip starts to roll, it’s not clear how far it will go.
  • You keep drawing the brush across the canvas, regardless.

“Moving the brush” is the curious exploration. Keith reports that he tries a project a week or so, but that most “don’t go anywhere” (I beg to differ). The drip rolling down is an area of specialization. Once it starts rolling, it’s not clear how far it will go. In any case, the brush keeps moving. Eventually the last drip stops and a new one starts.

1 comment
  1. Bob, I haven’t read Kent’s article before. Thanks for sharing. I used in the past a slightly modified TTT-shaped metaphor as I was aware most skilled people are not only good at one thing, but they spike down into many areas. What I like better about the paint-drip is that it reflects better the fluidity of knowledge and learning and it better describe the different depths of mastery, as not all drops go similarly low. I am using it from now on. Thank you.

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