AILang/docs/DESIGN.md

AILang — design decisions

This document records the core decisions for AILang. It is my contract with myself across future iterations. Prefer cuts over growth.

Goal

AILang is a programming language for LLM authors. It compiles to LLVM IR. Performance: native, no GC for the MVP.

Optimised for:

• Machine readability over human ergonomics. The source is structured.
• Local reasoning. Every definition carries its full type and effects.
• Provability. Pure core language, explicit effects, optional refinements.
• Robustness against hallucinations. Symbols are hashable; tools can verify existence without spending context window.

Project ecosystem

AILang is not just a language but an ecosystem. The language on its own is only valuable when its surroundings make it usable, checkable, and extensible for its target user (LLM authors). The repo therefore contains several equally important components — none of them optional, all of them evolving in lockstep with the language:

• Language core (crates/ailang-core, crates/ailang-check, crates/ailang-codegen): AST, type system, codegen.
• CLI (crates/ail): toolchain for tooling consumers — manifest, describe, deps, check, build, etc., preferably with --json for machine consumption.
• Examples (examples/): canonical .ail.json programs. They are specification anchors, not demos — the E2E suite hangs off them.
• Agents (agents/): specialised sub-prompts (implementer, architect, tester, debugger) that form the project's own LLM tooling. They are a versioned part of the repo. See agents/README.md.
• Docs (docs/): DESIGN.md (what and why), JOURNAL.md (history).
• Tests: unit tests per crate plus E2E in crates/ail/tests/e2e.rs. Every new compiler path needs a test, otherwise the feature does not count as done.

When the language grows, these components grow with it. New tools that strengthen the LLM tooling (e.g. ail diff, IR snapshot diffs, new agents) explicitly belong in the ecosystem inventory of this section and are added here as soon as they are established.

Project language: English

All in-tree content is written in English: source code (identifiers, comments, string literals, CLI help), design documents, the journal, agent prompts, READMEs, commit messages, examples, and CLAUDE.md. The live conversation between user and me stays German for ergonomic reasons; everything that lands in git is English. This keeps diffs and tooling output uniform and matches the audience for AILang (LLM authors), for whom English is the default.

Decision 1: source = data, not text

A module is a JSON object with a fixed schema. There is no parser for free-form text. Typos in identifiers turn into hash-lookup errors that the compiler proposes a fix for directly.

A textual form exists (.ail, S-expression-like), but only as a bidirectional projection of the JSON form. It is intended for human reviews and diffs.

Canonical format: .ail.json with deterministic key order.

Decision 2: content-addressed definitions

Every top-level definition has a hash value (BLAKE3 over canonical JSON without the hash field itself). References between definitions go primarily by name — names are for readability. The hash is the canonical identity.

Advantages:

• Refactoring by adding new defs, not by in-place change. Old versions stay callable until manually removed.
• Caching of typecheck results and codegen per hash.
• Diffs show exactly which def has changed.

Decision 3: pure core language + algebraic effects

The default is total, pure functions. Effects are declared as a set in the function type: (Int) -> Int ![IO]. The effect set is row-polymorphic (![IO | r]). In the MVP only the effects IO and Diverge (for infinite loops) are wired up.

This is the most important LLM property: when I read a function, I can trust its signature without reading the body.

Decision 4: Hindley-Milner + optional refinements

MVP: HM with let-polymorphism. All types are inferable, but at the top level they must always be explicitly annotated (for local reasoning).

Later: refinement annotations that escalate to SMT. (i: Int | i >= 0). They are reserved in the AST from the start, but in the MVP they are simply passed through as opaque strings.

Decision 5: emit LLVM IR as text

Instead of inkwell or llvm-sys: AILang produces .ll files as strings and hands them to clang for linking.

Rationale:

• The LLVM IR text syntax is largely stable across versions.
• No build dependency on a specific libllvm version.
• Generated code is trivially inspectable, which makes debugging much easier.
• An LLM can read the generated IR directly, which is harder with opaque library calls.

Trade-off: no inline optimisations through the LLVM API. We rely on clang -O2 as the standard pipeline.

Decision 6: authoring surface (Iter 14b — WIP)

Status: design pass in progress. Reading without skipping the JOURNAL will leave this section ahead of the implementation.

Why this is opening up

Iters 1 through 14a authored everything as raw *.ail.json. That worked for 17 fixture files (each ≤ 60 LOC of JSON) but does not scale. Two breaking signals:

1. The token-economy cost of the JSON-AST is massive: a single integer literal 1 is encoded as {"t":"lit","lit":{"kind":"int","value":1}} — ~38 tokens of structural overhead per bit of semantics. For a stdlib in the 200–500 def range this displaces real attention budget.
2. JSON-AST authoring exposes a class of errors (wrong field names, silently-accepted extra fields under #[serde(default)], inconsistent ctor casing) that surface only at load time. The schema is correct-by-construction in storage but error-prone in authoring.

Decision 1 anticipated this: it says a textual form exists "as a bidirectional projection of the JSON form." The pretty-printer already emits S-expression-style text (see crates/ailang-core/src/pretty.rs). What is missing is the inverse direction — text → AST. Decision 6 adds that inverse as one authoring projection alongside the existing pretty-printer; the JSON-AST remains the source of truth.

Architectural pin: data structure is the source of truth

The textual surface is not a replacement for the JSON-AST. It is one projection among potentially many. Concretely:

• The JSON-AST keeps its role as the canonical, hashable, content- addressed representation of a module. All hashing, content- addressing, cross-module references, and typecheck/codegen input flow through the JSON-AST. No new hashable form is introduced.
• The textual surface (form A, this Decision) is the AI authoring projection: optimised for me producing programs token-efficiently and for foreign LLMs producing programs from a spec. It is not optimised for human authors and does not need to be human-pleasant.
• Future projections are explicitly anticipated: a visual / graphical front-end is a plausible second projection for human review and inspection (display being the one case where non-AI eyes matter). The architecture leaves room: any producer of well-formed ailang-core::ast::Module values is a valid front-end.
• No human is expected to author AILang seriously. Authoring is AI work. Display and verification, by contrast, are concerns where human-facing alternatives may be useful — and which can therefore layer their own projections on top of the same AST without touching the surface or the core.

In code terms: ailang-core owns the AST. ailang-surface (new in Iter 14c) is one producer/consumer pair: text-form-A → AST → text- form-A. A hypothetical ailang-visual would be a different producer of the same AST. ailang-check and ailang-codegen consume only the AST and remain projection-agnostic.

Constraints (hard, in priority order)

1. Formalizable for a foreign LLM. The grammar must fit in an EBNF/PEG spec of ≤ 30 productions. A model that has never seen AILang must be able to read the spec and produce conforming source zero-shot. Rules out: precedence between binary operators, semantic indentation, maximal-munch lexing, context-sensitive reductions.
2. AST-isomorphic. Every surface form maps to exactly one AST shape. Round-trip surface → AST → canonical JSON → AST → surface is the identity (modulo formatting). Hashes computed via the round-tripped JSON must equal hashes of the same module written directly in JSON.
3. No external symbols. ASCII only. No Greek (∀), no arrows (→), no subscripts. Reasoning: I substitute mojibake for non-ASCII characters under context pressure; foreign LLMs vary in how they tokenize Unicode.
4. No precedence. Either everything is parenthesized, or there are no infix operators. Prefer the latter — add(x, 1) over x + 1. Removes a fail mode for both me and foreign LLMs.
5. No semantic indentation. Block structure expressed by paired delimiters or terminator tokens. Indentation is informational only; the parser ignores it.
6. One construct per token-list. Every AST node corresponds to exactly one parenthesized form (or atom). No "sometimes you can omit the parens" rules.
7. AST surface stays frozen. The surface adapts to the AST, not the other way around. We do not change the JSON schema or invalidate hashes to make the surface prettier.

Candidate notations (same map encoded in each)

The reference target — the polymorphic map from examples/list_map_poly.ail.json:

data List a where Nil | Cons a (List a)
fn map : forall a b. ((a) -> b, List a) -> List b
       = \f xs. match xs of Nil -> Nil
                          | Cons h t -> Cons(f(h), map(f, t))

(A) S-expression with fully-tagged AST nodes

(module list_map_poly

  (data List (vars a)
    (ctor Nil)
    (ctor Cons a (con List a)))

  (fn inc
    (type (fn-type (params (con Int)) (ret (con Int))))
    (params x)
    (body (app + x 1)))

  (fn map
    (type
      (forall (vars a b)
        (fn-type
          (params (fn-type (params a) (ret b)) (con List a))
          (ret (con List b)))))
    (params f xs)
    (body
      (match xs
        (case (pat-ctor Nil) (term-ctor List Nil))
        (case (pat-ctor Cons h t)
          (term-ctor List Cons
            (app f h)
            (app map f t)))))))

Grammar core (3-rule lexical layer + ~25 named-form productions):

sexpr  ::= atom | "(" sexpr* ")"
atom   ::= integer | string | ident
ident  ::= any maximal non-whitespace, non-paren run that is not
           a recognised integer or string literal.

The lexer recognises one delimiter (( / )) and whitespace. Every other maximal token is classified post-hoc:

• All-digit run with optional leading - → integer atom.
• "-delimited run → string atom.
• Otherwise → ident.

Consequence: operators like +, ==, <=, **, qualified names like io/print_int, and cross-module references like std_list.map are all single ident tokens with no special lex rule. The only reserved tokens are (, ), and whitespace. Bool literals (true, false) and unit ((lit-unit)) are disambiguated by parser context, not by lex.

Every AST node form has a unique head keyword (module, data, fn, forall, fn-type, con, var, app, lam, match, case, pat-ctor, term-ctor, do, seq, ...). A bare atom in a positional slot (e.g. inside (con List a) second position) is a name reference whose sort is determined by the parent slot:

• inside (con NAME args...) second-and-later positions → type expression. Bare atom there ⇒ Type::Var { name }.
• inside (app HEAD args...) first position ⇒ Term::Var.
• inside (pat-ctor CTOR fields...) field positions ⇒ Pattern::Var.
• inside (case PAT BODY) second position ⇒ term.

There is no lexical case rule. To construct a value with a ctor, write (term-ctor TypeName CtorName args...). To match against one, write (pat-ctor CtorName fields...). Capitalised identifiers carry no special meaning to the parser. This rules out a class of silent errors ("I forgot to capitalise Cons and it parsed as a function call").

Pros: smallest formal grammar of any candidate (the lexical core is 3 rules; the named-form productions are uniform — every node a tagged list). Foreign-LLM bar lowest. Round-trip with the existing pretty-printer is a refactor of pretty.rs to emit this tagged form, plus a new parser.

Cons: paren density is high. (forall (vars a b) (fn-type ...)) has more visual nesting than the current pretty-printer's forall a. (...) -> .... Verbosity is ~2× JSON for the same node when measured in characters, but ~8× shorter in lines (the existing JSON box.ail.json of 160 lines becomes ~20 lines in this form).

(B) Indented record-style with explicit terminators

module std_list

data List(a):
  Nil
  Cons(a, List(a))
end

fn map:
  type: forall a b. fn(fn(a) -> b, List(a)) -> List(b)
  params: f, xs
  body:
    match xs:
      Nil          => Nil
      Cons(h, t)   => Cons(f(h), map(f, t))
    end
end

Grammar core (~20–30 productions): module-level (def/data/end), type sub-grammar (forall, fn, con, var), term sub-grammar (lam, match, ctor, app, lit, var, seq), pattern sub-grammar.

Pros: higher information density per line, closer to mainstream ML/Haskell shape. Cons: four sub-grammars instead of one. forall a b. fn(...) keeps a pseudo-precedence (-> binds tighter than the outer fn(...) wrapper). Foreign-LLM bar higher.

(C) Pretty-printer-as-source

Use exactly the format pretty::module already emits, plus a parser that accepts it. The existing pretty-printer's quirks (:: for type-of, [params] for fn-params, <a> for type-args, forall a. ..., !IO, () ambiguous between unit-arg-list and empty-form) become the spec.

Pros: zero churn — the existing pretty-printer is already the spec; only the inverse is missing. Round-trip is the identity by construction. Cons: the existing format mixes four mini-dialects (s-expr at term level, ML-shape at type level, square brackets for params, <> for type args). Formalising it crisply is harder than designing a uniform form from scratch.

First choice and rollback plan

Try (A) first. Reasoning: constraint 1 (formalizable) outweighs constraint readability. (A) has a 3-rule core grammar with one lexical disambiguation rule. (B) doubles the rule count and re-introduces a soft form of precedence (-> inside forall). (C) is tempting because it is zero-design but the resulting spec is visibly heterogeneous, which is exactly what constraint 1 was meant to rule out.

If implementing (A) reveals that paren density actively hurts my authoring (measurable: I make more wrong-paren errors than the JSON-AST shape produced before), roll back and try (C). (B) stays on the shelf for a future iter only if both fail.

Implementation outline (Iter 14c onwards, not done in 14b)

• crates/ailang-surface — new crate. Strictly additive. PEG parser produces existing ailang-core::ast types. No new AST nodes, no schema changes, no new hashable form. Pretty-printer for form (A) lives here too (the round-trip is the contract).
• ailang-check, ailang-codegen are not modified. They continue to consume ailang-core::ast::Module values regardless of which projection produced them.
• Round-trip test: for every examples/*.ail.json, parse the corresponding hand-written *.ailx, canonicalise, and assert hash-equivalence to the original. Hash equivalence is the truth check; the surface ships only if every fixture round-trips identically.
• CLI: ail parse <file.ailx> -o <file.ail.json>. Symmetric to existing ail render. .ail.json remains a first-class input to every existing subcommand; the parser is a producer, not a gatekeeper.
• Iter 14d: stdlib (std_list, std_maybe, ...) authored in form (A) from day one because that is the AI authoring projection, not because JSON authoring is forbidden. The resulting .ail.json is what tests and downstream tools see.

What this Decision deliberately does not do

• It does not promote form (A) to the source of truth. Form (A) is one projection; the JSON-AST stays canonical.
• It does not foreclose visual or graphical front-ends. The crate layout (core owns AST; surface/visual/... are siblings) reserves that lane.
• It does not remove .ail.json as input. Every existing CLI subcommand (check, render, describe, emit-ir, build, run, manifest, deps, diff, workspace, builtins) keeps its current .ail.json interface.

Form refinements during Iter 14c implementation

Two productions in the original 14b sketch had to be widened during implementation to round-trip the existing AST faithfully. Captured here for the spec record:

1. lam-term carries types and effects. The AST's Term::Lam stores parallel params, param_tys, ret_ty, and effects fields. The 14b sketch had only names. The implemented form is

   lam-term ::= "(" "lam" "(" "params" typed-param* ")"
                          "(" "ret" type ")"
                          effects-clause? body-attr ")"
   typed-param ::= "(" "typed" ident type ")"
   

   This keeps the no-precedence / one-construct-per-token-list invariants and adds no new lexical rules.

2. import-clause admits an optional alias. The AST's Import.alias is Option<String>; the original sketch only supported the None case. The implemented form is

   import-clause ::= "(" "import" ident ("as" ident)? ")"
   

   as is a bare ident token in this position; no special lexical rule is needed.

Neither change extends the grammar's rule budget meaningfully: the 30-production ceiling of constraint 1 is intact (the parser implements ~28 named productions). All 17 examples/*.ail.json fixtures round-trip identically through print → parse → canonical JSON; the three hand-written .ailx exhibits parse to canonical JSON identical to their corresponding .ail.json files.

3. Tail-call surface (Iter 14e). Decision 8 ships two new productions, both positional analogues of their non-tail counterparts. Their result terms set Term::App.tail = true / Term::Do.tail = true; the typechecker's verify_tail_positions pass enforces that the marker is only used in tail position.

   tail-app-term ::= "(" "tail-app" term term+ ")"
   tail-do-term  ::= "(" "tail-do" ident term* ")"
   

   Production count after Iter 14e: ~30, still inside the 30-rule constraint-1 budget. No new lexical rule (tail-app / tail-do are bare ident tokens; no special casing).

Decision 7: redundancy removal — Term::If is not a primitive

Term::If { cond, then, else_ } is semantically a subset of Term::Match on Bool. Per CLAUDE.md the language must contain no redundancies; two AST nodes for the same operation produces an authoring decision with no semantic content and an extra codegen path. Iter 14d removes Term::If. Migration shape on the JSON side:

{"t":"if","cond":C,"then":A,"else":B} → {"t":"match","scrutinee":C, "arms":[ {"pat":{"p":"lit","lit":{"kind":"bool","value":true}},"body":A}, {"pat":{"p":"wild"},"body":B}]}

The wildcard arm satisfies the typechecker's primitive-needs-wildcard rule. A future iter may upgrade the exhaustiveness check to recognise the true+false arm pair as covering Bool without a wildcard; until then, wildcard is the canonical migration target.

No schema version bump (no third-party consumes ailang/v0). Hash invalidation for the three migrated fixtures (sum, sort, max3) is intentional; the new hashes become the new identity.

Decision 8: explicit, verified tail calls

For an LLM author, recursion is the natural iteration form (\n. if n == 0 then () else loop(n-1) is what I reach for, not a for-loop). Without a tail-call guarantee, every recursive program has a silent stack-depth ceiling that no compile-time diagnostic warns about. That is exactly the class of correctness hazard the language exists to eliminate.

Solution: explicit, verified tail calls.

• AST. Term::App { fn, args, tail: bool } and Term::Do { op, args, tail: bool } gain a tail flag, serde-defaulting to false so existing fixtures load with tail: false and their hashes stay bit-identical.
• Typecheck. A new pass verify_tail_positions(fn_body) runs after the main type-check. It walks the body with an is_tail_context: bool threaded down. The flag is true at the start, true for the body of every Term::Match arm, true for the right operand of Term::Seq, true for the body of Term::Let, true for the body of Term::Lam (each Lam opens its own tail scope). The flag is false for: args of any App/Do/Ctor, scrutinee of Match, left of Seq, condition of Let-bound expression. When the walker visits an App { tail: true } or Do { tail: true }, the flag must be true at that visit; otherwise emit diagnostic tail-call-not-in-tail-position.
• Codegen. Emit musttail call (LLVM IR) for marked calls instead of plain call. LLVM rejects at IR-verification time if the call cannot physically be a tail call (calling convention mismatch, signature divergence, etc.). The reject surfaces as a hard build error, not a silent runtime surprise.
• Form (A). Two new keywords: tail-app, tail-do. Productions are positional analogues of app/do with tail: true set on the resulting term. EBNF gains 2 lines; total production count goes from ~28 to ~30, still inside the constraint-1 budget.

What this does NOT promise. Per the 14d tail-call survey, many existing recursive calls are not in tail position because they are arguments to constructor calls (e.g. Cons (f h) (map f t)). 14e adds annotation + verification; it does not add a CPS transform or accumulator-form rewrite. Programs whose recursion is constructor-blocked will continue to be stack-bounded by recursion depth. The canonical authoring pattern in such cases is to write the accumulator-form variant (map_acc, fold_left, etc.) explicitly. The stdlib (15a onward) ships both forms where relevant.

The 14d migration of existing fixtures will be partial: only print_list-style terminal recursions get marked. The constructor-blocked recursions in map, sort, insert remain unmarked — they cannot benefit from musttail without a source-level rewrite.

Decision 9: memory management — Boehm conservative GC

Through Iter 14e, every ADT box, lambda env, and closure pair was allocated with bare malloc and never freed. That worked for the 17 test fixtures (all small, all short-lived) but is incompatible with any real workload — a stdlib fold over a million-element list would leak a million boxes. The "Goal" section's "no GC for the MVP" framing predates the parameterised-ADT pipeline (Iter 13) and the explicit-recursion expectation (Iter 14e); both make a collector necessary.

Choice: Boehm-Demers-Weiser conservative GC. The simplest working option:

• Replace malloc(...) with GC_malloc(...) in every IR site (currently lower_ctor's ADT box, lower_lambda's env block and closure pair).
• Replace the IR-level declare ptr @malloc(i64) with declare ptr @GC_malloc(i64).
• Add -lgc to the clang link command (in crates/ail/src/main.rs's Build / Run paths).
• No language-level change. No AST change. No schema change.

Rationale:

• Mature. Boehm has been the default conservative GC for decades. Linux distros ship it as libgc / libgc-dev / gc (Arch).
• No language work. Conservative scan of the C stack handles AILang's stack frames without LLVM stack-map infrastructure (which is its own multi-iter design).
• Single-iter integration. Lift-and-shift of the four allocation sites; all existing tests must still pass with identical output.

Trade-offs accepted:

• Conservative over-retention. A user-supplied Int field whose value happens to coincide with a heap address will pin that allocation. In practice, vanishingly rare for typical values; survivable.
• Pause time non-deterministic. Boehm uses stop-the-world mark-sweep. For LLM-author-written stdlib code at MVP scale, pause times are not the bottleneck.
• Build-time dependency. libgc must be installed on the build host. Users without it get a link-time error from clang, not a silent failure.

A future iter may layer a per-fn-arena optimisation on top: when a fn's return type contains no boxed ADT, ADT boxes allocated inside that fn cannot escape, so an arena freed at fn return is sound by construction (per the 14e GC notes). That requires escape analysis, the corresponding AST/IR plumbing, and is its own design pass. Boehm-everything is the floor; arena is an optimisation above it.

Mangling scheme (Iter 5c)

All AILang functions are mangled to @ail_<module>_<def> — even in the single-module case. Constants likewise (@ail_<module>_<const>). Global string literals carry a short hint for readability: @.str_<module>_<hint>_<idx> (e.g. @.str_sum_fmt_int_0). The entry point is a define i32 @main() trampoline (C / LLVM ABI) that calls @ail_<entry-module>_main(). source_filename exists exactly once per workspace and carries the entry-module name (<entry-module>.ail).

Convention: qualified cross-module references (Iter 5b)

Cross-module calls use no new AST node. Instead, a Term::Var { name } with exactly one dot in the name is a qualified reference: <prefix>.<def>.

• <prefix> is an import alias (import { module: "X", as: "<prefix>" }) or, when imported without an alias, the module name itself.
• <def> is the name of a top-level definition in the target module.
• Def names MUST NOT contain a dot — the typechecker reports invalid-def-name with ctx: { "reason": "contains-dot" }.
• The workspace loader (Iter 5a) finds all reachable modules; the typechecker (Iter 5b, check_workspace) resolves dotted names through the import map. Diagnostic codes: unknown-module (prefix not imported), unknown-import (module found, def not).

Hash stability: no new AST node, no renamed fields — all previous module hashes stay bit-identical.

Data model (MVP)

Module

{
  "schema": "ailang/v0",
  "name": "<id>",
  "imports": [{ "module": "<id>", "as": "<id>" }],
  "defs": [Def...]
}

Def

kind ∈ { "fn", "type", "effect", "const" }. In the MVP only fn and const.

{
  "kind": "fn",
  "name": "<id>",
  "type": Type,
  "params": ["<id>"...],
  "body": Term,
  "doc": "<optional string>"
}

Term (expression)

{ "t": "lit", "lit": { "kind": "int" | "bool" | "unit", "value": ... } }
{ "t": "var", "name": "<id>" }
{ "t": "app", "fn": Term, "args": [Term...] }
{ "t": "let", "name": "<id>", "value": Term, "body": Term }
{ "t": "do", "op": "<eff>/<op>", "args": [Term...] }
{ "t": "ctor", "type": "<id>", "ctor": "<id>", "args": [Term...] }
{ "t": "match", "scrutinee": Term, "arms": [Arm...] }
{ "t": "lam",
  "params": ["<id>"...],
  "paramTypes": [Type...],
  "retType": Type,
  "effects": ["<id>"...],
  "body": Term }
{ "t": "seq", "lhs": Term, "rhs": Term }

In the MVP, do is only a direct call to a built-in effect op (no handler). A lam term constructs an anonymous function value; free variables of its body are captured from the enclosing scope (see Iter 8 closure conversion in JOURNAL). A seq term evaluates lhs for its effects (its result must be Unit) and yields rhs's value — equivalent to let _ = lhs in rhs.

Type

{ "k": "con", "name": "Int" }
{ "k": "con", "name": "Bool" }
{ "k": "con", "name": "Unit" }
{ "k": "fn", "params": [Type...], "ret": Type, "effects": ["IO"...] }
{ "k": "var", "name": "a" }
{ "k": "forall", "vars": ["a"...], "body": Type }

Pipeline

.ail.json  ─┐
            ├─ load + validate schema
            ├─ resolve names + assign hashes
            ├─ typecheck (HM, effect rows)
            ├─ lower to MIR (SSA-like, named SSA values)
            ├─ emit LLVM IR (.ll)
            └─ clang -O2 *.ll -o binary

CLI

ail check <module.ail.json>      — loads, validates, typechecks
ail manifest <module.ail.json>   — table: name :: type !effects [hash]
ail describe <module> <name>     — detail of a definition
ail render <module>              — JSON → pretty-print
ail parse <module.ail>           — pretty-print → JSON (for bootstrapping)
ail emit-ir <module>             — writes .ll
ail build <module>               — full pipeline → binary
ail run <module>                 — build + execute (tempdir), passthrough exit code

Verification and correctness (across cycles)

1. Snapshot tests for the pretty-printer and IR emit. The diff makes regressions visible immediately.
2. Property tests for the JSON ↔ pretty-print roundtrip.
3. End-to-end tests for examples/ with expected program output.
4. Hash stability: a test ensures the same def always produces the same hash.
5. CI pin of the outputs in tests/expected/.
6. Rustdoc cleanliness: cargo doc --no-deps runs warning-free. Maintained by the ailang-docwriter agent (Iter 13d onward); fixing a rustdoc warning is part of the iter that introduced it, not a follow-up.

What is not (yet) supported

Snapshot of the boundary at the end of Iter 13. Items move out of this list as iterations land; the JOURNAL records the exact iteration.

• No effect handlers — only the built-in IO and Diverge ops.
• No refinements / SMT escalation.
• No HM inference inside bodies. Top-level def types are explicit; polymorphism is opt-in via Type::Forall { vars, body }. Inside a body, lambdas check monomorphically against their declared type.
• Polymorphic fns must be directly called at the use site. Passing a polymorphic fn as a value (let f = id in f(42)) is not yet supported — it would need one closure-pair global per instantiation, deferred.
• No higher-rank polymorphism. Passing a polymorphic fn to another polymorphic fn (apply(id, 42)) is not supported.
• No cross-module ADTs. ADTs are local to a module; ctor names must be unique within their module but may collide across modules.
• No visibility rules in imports. Every top-level def of an imported module is reachable; there is no pub / priv.
• No GC. ADT boxes, lambda envs, and closure pairs all leak. Acceptable for current example programs; required before any longer-running program.

What is supported (and used as the smoke test for the pipeline):

• Int, Bool, Unit, Str as primitive types.
• let, function calls, recursion. Bool branching is expressed via match on Bool with a (lit-bool true) arm and a wildcard fallback (Decision 7); there is no separate if AST node.
• Effects on function signatures, with do op(args) for direct effect ops (io/print_int, io/print_bool, io/print_str).
• ADTs + flat pattern matching (Iter 3). Sub-patterns of a Ctor pattern are restricted to Var / Wild.
• Imports + qualified cross-module references via dotted names (Iter 5).
• First-class function references (Iter 7). A top-level fn name (or qualified prefix.def) used as a Term::Var is a fn-value.
• Anonymous lambdas with capture (Iter 8). Term::Lam constructs a closure that captures any free variables of its body from the enclosing scope. All fn-values share a single ABI: a ptr to a closure pair { thunk_ptr, env_ptr }. Top-level fns get an auto- generated adapter and a static closure pair (env = null) so they remain passable as values without heap overhead.
• Polymorphism via Type::Forall at top-level def types (Iter 12). Use sites instantiate fresh metavars; unification pins them against the concrete types of the call args. Codegen monomorphises on demand: each unique instantiation emits a specialised LLVM fn mangled @ail_<m>_<def>__<descriptor> (e.g. id__I for id at Int, apply__I_I for apply at (Int, Int)).
• Parameterised ADTs (Iter 13). TypeDef.vars: Vec<String> declares type parameters; Type::Con.args: Vec<Type> carries the type arguments at use sites. Both fields default to empty and are skipped during serialization, so canonical-JSON hashes of every pre-13a definition stay bit-identical (regression test in crates/ailang-core/src/hash.rs). Ctor and match codegen stay inline at every use site — there is no specialised ADT symbol — but LLVM field types are derived per use site by substituting through cdef.ail_fields. The substitution is read off the call's arg types (ctor) or the scrutinee's Type::Con.args (match). An unresolved Type::Var reaching llvm_type is a hard error rather than a silent fallback to ptr.

Pipeline regression smoke tests:

• examples/sum.ail.json → prints 55 (recursion, arithmetic).
• examples/list.ail.json → prints 42 (ADTs + match).
• examples/hof.ail.json → prints 42 (first-class fn-refs, indirect call).
• examples/closure.ail.json → prints 42 (lambda capturing a let-bound var).
• examples/list_map.ail.json → prints 2/4/6 (ADTs + closure + recursive HOF + IO; the dogfood smoke test).
• examples/sort.ail.json → prints sorted [3,1,4,1,5,9,2,6,5,3,5] one-per-line (insertion sort over an 11-element list).
• examples/poly_id.ail.json → prints 42 then "true" (polymorphic identity at Int and Bool; two specialised fns emitted).
• examples/poly_apply.ail.json → prints 42 (polymorphic apply with a fn-typed parameter; apply(succ, 41)).
• examples/box.ail.json → prints 42 (parameterised ADT round- trip: MkBox(42) constructed, then projected by a polymorphic unbox : forall a. (Box<a>) -> a and printed).
• examples/maybe_int.ail.json → prints 7 then 99 (pattern match over Maybe<Int>: or_else(Some(7), 99) then or_else(None, 99)).