Aggro is the Foundation | Radimentary
Short summary
The author argues that across games, strategy, and mathematics research, the simplest, most direct approach (aggro) forms the bedrock that all other complex strategies must be built on top of. In math research specifically, solo technical work on hard problems is foundational—you can't effectively network, attend seminars, or collaborate without first mastering this basic skill.
- In card games like Magic, aggro decks are the simplest to build but dictate the entire metagame; all other deck types must be designed as explicit counters to the fastest aggro strategies in play.
- This pattern repeats across domains: in RTS games, the earliest possible rush determines defensive timing; in geopolitics, military capacity shapes all negotiations regardless of whether conflict occurs.
- For mathematicians, solo technical problem-solving is the aggro foundation—without competence here, you can't meaningfully evaluate seminars, learn from peers, or support other researchers, making advanced skills like grant-writing and mentorship ineffective.
Full summary
The author borrows a concept from trading card games to explain how metagames work across different domains. In Magic or Hearthstone, aggro decks—fast, straightforward strategies that kill opponents quickly—are the easiest to build because they just pack efficient early cards with minimal optimization needed. Everything else in the metagame gets built around countering aggro. Control and midrange decks must be constructed with specific knowledge of what aggro threats exist; if the fastest deck wins in three turns, you need cards playable in those first three turns. This principle extends beyond card games. In StarCraft, rush strategies arriving at 3:30 force all other strategies to have defensive plans by the 3-minute mark. In geopolitics, the mere possibility of nuclear war shapes every negotiation, even when no actual conflict occurs.
The author applies this framework to mathematics research. Solo work on hard technical problems is the "aggro" of academic math—simple in concept, straightforward in execution, but foundational to everything else. All the other layers of the metagame—seminars, networking, collaboration, mentoring students, securing grants—only make sense if built on top of genuine technical skill. Without knowing how to do independent research, you can't evaluate what matters in a seminar, ask meaningful questions of other researchers, or understand how to support someone else's work.
The tension the author identifies is real. Early-career systems select heavily for hard technical skills, which some argue is too narrow and misses competencies needed for later success. But the counterargument holds: if someone gets funding and PhD students without proving they can do solid theorems themselves, you can't tell if they're genuinely skilled or just a smooth talker. The foundation has to be solid first.