Both terms reflect the fact that we encounter large amounts of information in everyday life and our brains need some way to synthesize and contextualize that information.

Collaborating with another human is better than working with generative AI in part because conversation allows us to establish common ground, build shared semantics and engage in repair strategies when something is ambiguous.

You’ve got a complex system and it spews out a lot of wonderful numbers that enable you to measure some factors. But there are other factors that are terribly important, [yet] there’s no precise numbering you can put to these factors. You know they’re important, but you don’t have the numbers. Well, practically (1) everybody overweighs the stuff that can be numbered, because it yields to the statistical techniques they’re taught in academia, and (2) doesn’t mix in the hard-to-measure stuff that may be more important. That is a mistake I’ve tried all my life to avoid, and I have no regrets for having done that.

A large part of the difference between the experienced decision maker and the novice in these situations is not any particular intangible like “judgment” or “intuition.” If one could open the lid, so to speak, and see what was in the head of the experienced decision maker, one would find that he had at his disposal repertoires of possible actions; that he had checklists of things to think about before he acted; and that he had mechanisms in his mind to evoke these, and bring these to his conscious attention when the situations for decisions arose.

Epics, issues, requirements, and others all have similar but just subtle enough differences in common interactions that the user needs to hold a complicated mental model of how they each behave.

A model might show you some risks, but not the risks of using it. Moreover, models are built on a finite set of parameters, while reality affords us infinite sources of risks.

Same here, and I think this is not correct. The more I think about it, the more I am convinced it's a wrong mental model.

My mental model has always been that a reactive declaration like $: b = a * 2 defines b in it's entirety ("Here's my recipe for b and all the ingredients, please Svelte make b always up to date"). And outside of this declaration b is immutable.

A mental model is what the user believes about the system at hand.

Modules from the following layer can require anything from all the previous layers, but not vice versa.

Concepts seem to be structurable, in that a new concept can be composed of an organization of established concepts. For present purposes, we can view a concept structure as something which we might try to develop on paper for ourselves or work with by conscious thought processes, or as something which we try to communicate to one another in serious discussion. We assume that, for a given unit of comprehension to be imparted, there is a concept structure (which can be consciously developed and displayed) that can be presented to an individual in such a way that it is mapped into a corresponding mental structure which provides the basis for that individual's "comprehending" behavior. Our working assumption also considers that some concept structures would be better for this purpose than others, in that they would be more easily mapped by the individual into workable mental structures, or in that the resulting mental structures enable a higher degree of comprehension and better solutions to problems, or both.