2. Eight dimensions of sophistication

The patterns from the corpus become useful only when they become measurable. The instrument is a rubric of eight dimensions, each scored 0–4 against anchored, observable indicators, with half-steps allowed. The anchors themselves, the grep/AST cheat-sheet, the measured prevalence table, and the full catalog of profile shapes all live in one place — the rubric in full. This chapter is the part that page doesn’t carry: where the instrument came from, and why it is shaped the way it is.

The eight dimensions

Each dimension runs the same arc — level 0 is absence, level 1 the baseline, levels 2–3 real adoption, level 4 library-grade — because the corpus teardown kept finding that arc, dimension after dimension. The anchors were written by naming what the level observably looks like in a repo, not what it aspires to.

Why dimensions, not a single ladder score

The instrument did not start as a rubric. It started as the maturity ladder — a single ordered climb — and the ladder is genuinely right about sequence within a dimension: the IO layer is what makes a subsystem testable, so tests cannot precede it. But the moment the ladder met real repos, it broke as a measuring stick, because teams adopt unevenly across dimensions — a clean IO layer with zero tests, AdvantageKit logging on tangled coordination, Choreo trajectories over dead-reckoned odometry. A single rung number averages those into mush, and the average hides precisely the fact a coach needs: which adjacent step a team has already paid for and is not taking.

So the design decision was to score each dimension independently, report the vector, and read the shape of the profile rather than the total. The sum is still reported; the profile is the finding. The same decision corrected the teaching ladder in one place: the progression plan bundles “IO layer + simulation + lightweight logging” as one leap and “FSM + tests + replay” as another, which is the right teaching order but the wrong measurement — in the wild those bundles decompose, so the rubric splits them.

What the pilot changed

Before the full survey, the rubric was piloted on three teams chosen as a deliberate spread — likely-high, mid, baseline — to test whether it discriminates and surfaces distinct profiles. It did, and the pilot fixed two scoring rules that the anchors alone underdetermined: D1 takes the lenient reading (a maintained 254-style generic base counts toward the top of D1 even without a Real/Sim IO swap — generalization is the achievement, not the naming convention), and D8 credits a team library that demonstrably exists, with a note where it is demonstrably consumed. Both calls are recorded on the San Diego scoresheet, which inherited them.

Why the anchors are calibrated against prevalence

An anchor is only meaningful relative to how common its marker is: a structure present in 3 of 55 teams is a ceiling signal, one present in 45 is table stakes, and confusing the two turns the rubric into either flattery or impossibility. That is why every marker in the cheat-sheet carries its measured corpus count — the numbers live in the prevalence table. The counts also guard against naming traps the corpus exposed: hardware implementations are named by device, not “Real,” so grepping *IOReal misses most IO layers — the robust signal is an interface *IO with two or more implementations, one of them a sim. The general rule — score what’s used, not what’s present — applies hardest exactly where naming and presence mislead.

Two smaller decisions round out the design. Equal weighting is deliberate: an EPA-optimal re-weighting of the eight dimensions was tested and was not distinguishable from equal weight, so the sum stays simple. Half-steps exist because real teams sit between anchors; the rubric’s scoring rules include an example of a legitimate 2.5 versus a lazy one.

Reading the profile

Scored vectors fall into recognizable shapes — balanced climber, architecture-without-verification, tooling adopter, template inheritor, legacy program, verification ceiling — and the shape, not the sum, determines the highest-leverage next step. The full catalog with its interventions is in the rubric in full; the design point here is simply that the rubric was built so that its output is a diagnosis, not a grade.

With the instrument’s rationale in hand, the next chapter returns to the ladder the rubric was carved from — the novice-to-elite maturity ladder.