Current Version: 0.1 – Story & Vision

3 Elements on 3 Layers


The smallest unit of action. At the heart of the model, each atom symbolises a task that, like a checklist, has to be performed to continue the flow.


Tasks might correlate with physical or digital things. They are symbolised in the stuff element, and the direction of the arrow indicates whether they are produced, required, or just for support.


Required information to perform an atom’s action, e.g. a link to Wikipedia, an internal Wiki, or a lecture on quantum mechanics. Skills are the application of knowledge.

Through its parallel layers, the SLF model provides the necessary knowledge and an overview of the involved stuff at the right time. The simple flow in the middle shows the chaos that’s going on, the stuff layer manages all assets, and the knowledge layer supports when needed. A new hire can start working on his first day with a good straight line, and while experts might require less information, it is always there.

The Flow

  • Every SLF has a beginning and an end
  • The flow is from the left to the right
  • Take at least one path through each area

Path and area?

SLF’s version of and/or. An unlimited amount of paths can follow each atom. Each individual outgoing path has to be taken, and an atom can only start once all incoming paths have been completed. If a path splits into alternative routes, only one has to be completed to fulfil the path. The other actions can but don’t have to be executed.

Both paths have to be taken
One path is enough


Flows can be embedded within other flows through sub-flows. Following the principles of a Zettelkasten, atoms should be the smallest possible action – something that can be done within a few minutes. To still ensure a good overview of complex flows, we work with nested flows instead, and there is no limit to how many layers of flows there are. This way, SLFs and other atoms can be perfected once and then used in other flows again and again.

Any Concerns?

Tell us!

The Straight Line Flow is a work in progress, with this page aiming to be the most efficient explanation. Help us by telling us everything you don’t instantly understand, find confusing, or see a use case in which the model might fail.