Lukeprog's How to Beat Procrastination includes in its framework a term for expectancy or how likely/accomplishable a successful outcome feels internally. One of the levers to combat procrastination is thus to increase the perceived odds of getting a reward. I think this misattributes low expectancy to poorly calibrated self-confidence, when really it boils down to your own actual capabilities and the problem structure.

In many cases, the root cause for low expectancy is that you personally do not have experience, knowledge, or resources. Expectancy should be low rationally. While the original post does prescribe learning/process goals, this is framed as a means to the end of increasing self-confidence. In practice, this framing can lead you to focus on goals that increase confidence without tackling underlying understanding/competence. Competence can lead to confidence, but false confidence (which is fairly easy to manufacture via the methods in the original post) can lead to disaster. An unfortunate side effect: If you're optimizing for self-confidence, when reality hits back, you will start to distrust self-confidence as a signal, leaving you in an even worse place than where you started. (I actually think this is the main cause of chronically miscalibrated low self-confidence.)

Another common case that brings low expectancy: a task has long feedback loops and credit assignment is difficult. Even if you have the fundamental skills, there's no way of knowing if your actions are moving the needle. Setting intermediate process goals here can help sustain effort in one direction, but it cannot change the nature of the problem: it takes time to know if the intermediate process goals you choose are actually moving you towards your terminal goals effectively, especially in a new/unstructured domain. Society's answer here is to create concrete, well-trodden paths with visible rewards (structure the domain) or to work closely and learn from someone who has similar experience. This works great when it works (though it also relies on you to generally understand your direction/terminal goals).

However, the above solution is founded on an implicit trust that the promises will be fulfilled, and the environment and institutions will remain similar enough by the time you complete the intermediate goal. For rationalists who put some credence in short AI timelines (and anyone else in an unstable environment), this assumption is tenuous. Even if you distance yourself from the problem or try to reframe it (e.g., by coming up with plans that work on shorter horizons, or framing your work as a bet on a specific world, or by trying to create robust plans that work across many worlds), that doesn't eliminate the underlying reality that things are going to change, rapidly and unpredictably. The only answer I can think of here is to make peace with that fact. After you acknolwedge it and factor it in, continuing to dwell on it provides no new information, and will just cause paralysis.