A sketch of a model for choosing what projects to invest in.

Imagine all of the projects you could do as a graph of possibility.

Every node you build opens up other adjacent nodes, too.

The frontier of possibilities has a combinatorial explosion... so you need some way to decide which ones to invest in.

Parallels to the Assembly Theory academic paper I linked last week.

Imagine a north star representing your vision or long-term goal.

Imagine each adjacent (edge + node) combo has a few components:

An orientation (angle towards or away from the north star)

A one-time cost to build

A marginal cost to operate

A marginal value to users when they use it

An uncertainty term that obscures all of the other terms

One approach is to pick the node that is most aligned with your north star.

You might even do some instrumental UXR to reduce some local uncertainty, given that you want to take a big step in a given direction.

Downsides of this approach: the cost to build might turn out to be exorbitant, or the activation gradient (marginal value / marginal cost) might be shallow, or even negative!

Another approach is to first sit with the problem, almost communing with it.

Taking the time for the cloud of uncertainty to lift, just a bit.

You should spend at least some time looking for novel, disconfirming evidence. You might find a great pathway you hadn't considered.

Then, you look for cheap projects that have the strongest activation gradient (marginal value / marginal cost) and also bring you at least incrementally more in the direction of the north star.

This research is broader, more exploratory, more based on intuition and sensing.

You might call this approach "novelty search with vibes"

This approach goes slower in the short-term, but is more likely to discover long-term viable/fast paths.