experiment(cma): familiar-vs-unfamiliar — AILang is not harder for a frontier model given a scan (refs #68 #69 #70)

Follows up the SMA controls with the sharper question: does AILang cost a
frontier model MORE than a language it knows from training (Rust)? Claude
passing SMA is binary and cannot tell "effortless" from "barely". Measured with
pass@1 over 6 samples of the same task in AILang (two-example few-shot) vs Rust,
single-shot, fresh clueless agents, no tools, oracled afterward.

Task 1 (Expr-evaluator — ADT + match + recursion, all in the few-shot):
AILang 6/6 = Rust 6/6, no gap; all six AILang answers byte-identical. When every
construct is in the few-shot, AILang is not harder.

Task 2 (count-greater-than — needs a comparison, OUTSIDE the few-shot): AILang
0/6 vs Rust 6/6. But the logic was correct in all six; they fell on a guessed
name (`>`, which AILang lacks). A vocabulary gap, not a reasoning gap — and the
single-shot setup is unfair: in Rust Claude implicitly has its training plus the
obvious ability to scan an unknown crate, which AILang was denied.

The fair test (scan + compiler-loop, how Claude actually works): one Claude
context, count-greater-than, given the prelude as a scanned library, then
iterated on raw compiler output. Converges in two feedback rounds —
gt+match-on-Bool -> (case true ..) -> match (compare h N) .. GT -> green.
Decisive contrast: no-scan + terse errors -> Claude DIVERGES (invents gtPos,
sub, non-existent pat-var); scan + diagnostic errors -> Claude CONVERGES. Same
model; the difference is the discovery affordances, not the model. The 0/6 was
the artefact of an unfair test, not an intrinsic AILang weakness — with the
scan-plus-iterate workflow, the "language is harder" gap dissolves.

Two genuine AILang defects the thread exposed, filed as issues:
- #69: `ail builtins` is an incomplete API scan — it lists no comparison
  operator; gt/lt/le/ge/compare live in the prelude, which builtins does not
  surface. A model scanning the obvious discovery tool never finds half the
  comparison stdlib.
- #70: `match` on Bool passes `ail check` but codegen rejects it
  (`match on non-ADT scrutinee (i1); MVP supports only ADTs`); with no `if`,
  branching on a Bool has no working surface — one must route through
  compare->Ordering. A check/codegen inconsistency under an "internal:" prefix.

Answer, decomposed: cognitively AILang is not harder (the algorithm transfers);
vocabulary-without-scan is harder but that is any unfamiliar language; with scan
+ iteration Claude drives AILang like a foreign crate; where it genuinely is
harder is the two fixable tooling/compiler defects above. Caveat: n=6, two small
tasks, one model, low sampling variance — exploratory, not a study. Evidence
under experiments/2026-05-12-cross-model-authoring/familiar-vs-unfamiliar/.

experiments/2026-05-12-cross-model-authoring/familiar-vs-unfamiliar/README.md

@@ -0,0 +1,44 @@
+# Is AILang harder for a frontier model than a familiar language?
+
+Evidence corpus for the "Is AILang harder for a frontier model…" section of
+`../format-findings.md`. The question: does AILang cost Claude *more* than a
+language it knows from training (Rust)? Method: pass@1 over 6 samples of the
+same task in AILang (two-example few-shot) vs Rust, single-shot, fresh clueless
+agents, no tools, oracled afterward (`ail check`/`run` resp. `rustc` + stdout).
+
+## task1-eval — ADT + match + recursion (all in the few-shot)
+
+Evaluate `(A + B) * C` over a small `Expr` ADT. **AILang 6/6 = Rust 6/6**, no
+gap — and all six AILang answers were byte-identical. When every construct is in
+the few-shot, AILang is not harder for Claude. `ail/m.ail` runs to `20`.
+
+## task2-countgt — count elements `> N` (needs a comparison, OUTSIDE the few-shot)
+
+- `ail-noscan/m.ail` — the single-shot answer. The *logic is correct* (recurse,
+  test, accumulate); it fails only on a guessed name: `> ` is not an AILang
+  identifier. Representative of **0/6** in this condition. The Rust cell
+  (`rust.rs`, idiomatic `filter().count()`) is **6/6**. So the single-shot gap
+  is a *vocabulary* gap, not a reasoning gap — and the single-shot setup is
+  unfair: in Rust Claude has its training plus the obvious ability to scan a
+  crate, which AILang was denied.
+
+- `ail-scan-loop/m.ail` — the **fair test**: same task, but Claude is given the
+  prelude as a scanned library and then iterates on raw compiler output (how it
+  actually works on an unfamiliar crate). It converges in two feedback rounds:
+  `gt`+`(pat-ctor True)` → `(case true …)` → finally `match (compare h N) … GT`.
+  Runs to `3`. The idiomatic path matches on the `Ordering` ADT that `compare`
+  returns — never on a `Bool`.
+
+## The finding
+
+*No scan + terse errors* → Claude diverges. *Scan + diagnostic errors* → Claude
+converges. Same model; the difference is the discovery affordances. The
+"language is harder" gap dissolves under the workflow Claude really uses.
+
+Two genuine AILang defects the thread exposed (filed as Gitea issues):
+
+1. `ail builtins` lists no comparison operator — they live in the prelude, which
+   `builtins` doesn't surface. The discovery tool is an incomplete API scan.
+2. `match` on `Bool` passes `ail check` but is rejected by codegen
+   (`match on non-ADT scrutinee (i1); MVP supports only ADTs`); with no `if`,
+   branching on a Bool is a dead end. A check/codegen inconsistency.