Musk Wiki

Concept

Maximize usefulness

NextMerging with AI

Maximize usefulness

The heuristic Elon Musk gives, in the 2016 Y Combinator conversation, for deciding what to work on: maximize usefulness, defined as the size of the improvement you make times the number of people it reaches. It is the decision rule sitting under the grand missions — the test by which a candidate project earns the effort at all.

The rule

Asked how someone should figure out how to be most useful, Musk states it almost as a formula — impact per person, multiplied by reach:

“Whatever this thing is that you’re trying to create, what would be the utility delta compared to the current state of the art times how many people it would affect.” 🔗

The geometric image he uses for it is the area under the curve — a big improvement for a few people and a tiny improvement for a vast number can score the same:

“Area under the curve would actually be roughly similar for those two things, so it’s actually really about trying to be useful.” 🔗

Crucially, the rule explicitly licenses small work. World-changing ambition is not required; a modest good, spread widely, qualifies:

“Stuff doesn’t need to change the world to be good.” 🔗

“if it has a small amount of good for a large number of people, that’s fine.” 🔗

He frames it as the thing he himself optimized for as a young man — usefulness, not prestige or even world-changing scale:

“That’s the optimization, what can I do that would actually be useful?” 🔗

What it reveals

  • It is a quantified decision rule, not a slogan. “Utility delta times people affected” is a first-principles-flavored move: turn the vague question “what should I do?” into a product of two estimable quantities. The grand civilizational missions are then just the cases where both factors are enormous.
  • It separates “useful” from “world-changing.” A recurring misreading of Musk is that he only respects civilization-scale work. Here he explicitly says the opposite — a small improvement at large scale is genuinely good. The missions follow from the math, not from disdain for ordinary work.
  • It reframes impact as throughput. The “area under the curve” framing is of a piece with how he later answers what he optimizes for — how many useful things he can get done — and with his contempt for talent aimed at low-impact problems. The unit is always useful output, integrated over people.
  • It is the upstream filter for everything else. Before the AI work, the energy mission, or the species-level bets, this is the test that selects them: each is a place where the product of impact and reach is maximal.