# AILANG > Row-polymorphic Hindley-Milner with capability-based effects (IO, FS, Net, Clock, AI). No loops, lambda calculus only. Written autonomously by AI agents. **Camp:** Verification **Author:** Mark Edmondson / Sunholo **Implementation language:** Go **Compilation target:** Native binaries, WebAssembly **Licence:** Apache-2.0 **First seen:** September 2025 **Maturity:** working compiler **Site:** https://ailang.sunholo.com **Repo:** https://github.com/sunholo-data/ailang **AILANG Benchmark Dashboard:** https://ailang.sunholo.com/docs/benchmarks/performance **Agent tooling:** - SKILL.md - AGENTS.md - CLAUDE.md - MCP server - llms.txt - Claude Code plugin - Gemini CLI extension - slash commands ## Key idea AILANG ships a purely functional, effect-typed substrate for AI-generated code. The type system is Hindley-Milner with row polymorphism; the effect system carves authority into capability categories (IO, FS, Net, Clock, AI) that must be granted at the CLI with --caps. There are no loops — the language commits to lambda calculus, pattern matching, and ADTs as the only forms of control. The compiler itself is written autonomously by AI agents via a coordinator. ## The thesis. AILANG takes the verification camp's diagnosis and applies it at the layer of authority. The diagnosis is that LLMs hallucinate side effects — network calls in pure functions, filesystem writes in helpers that look read-only, model calls in code paths the operator never approved. AILANG's answer is to carve effects into capability categories — `IO`, `FS`, `Net`, `Clock`, `AI` — and make every one of them visible in the function's signature, row-polymorphically, with Hindley-Milner inference filling in the rest. A function that doesn't declare an effect can't perform it; a run that wasn't given a capability at the CLI can't grant it from inside.

For humans, a language is a tool for expression. For AIs, it's a substrate for reasoning.

The distinctive move is the no-loops decision. AILANG commits to lambda calculus, pattern matching, and ADTs as its only forms of control flow — no `for`, no `while`, no mutable accumulator. Where Vera tracks model calls as a single `` effect, AILANG splits the world into five capability categories and refuses to let the language grow a construct that obscures any of them. The bet is that determinism, replay, and structured per-effect traces are worth giving up the loop. ## What it looks like. 
module examples/hello

import std/io (println)

export func main() -> () ! {IO} {
  println("Hello from AILANG!")
}

The ! {IO} after the return type is the effect row. A caller without an IO capability granted via ailang run --caps IO cannot invoke this function. Effect rows compose: a function that calls IO- and FS-effecting helpers must declare {IO, FS}.

## Distinctive moves. - **Capability carving, not capability tracking.** Effects are partitioned into `IO`, `FS`, `Net`, `Clock`, `AI`. Each is granted (or refused) separately at the CLI with `--caps`. The model can't widen authority from inside the program. - **No loops.** Lambda calculus, recursion, and pattern matching only. The language has a dedicated "Why No Loops?" reference page; the design axioms treat the absence of mutable iteration as load-bearing for replay. - **Row-polymorphic Hindley-Milner.** Effect rows are first-class type-level objects, inferred and unified the same way row-typed records are. A helper that doesn't touch the network has a smaller row than its caller. - **Written by agents, end-to-end.** The README declares the language is "written autonomously by AI agents via its own coordinator"; static-analysis and supply-chain badges (Sonar, OpenSSF Scorecard, OpenSSF Best Practices) are cited as third-party verification of the output. - **MCP-first developer surface.** A hosted MCP server at `mcp.ailang.sunholo.com` ships typed tools over stdlib, examples, and benchmarks. The Claude Code plugin and Gemini CLI extension install the compiler, the prompt, and the MCP server in one command. ## Maturity. v0.20.1 with 110 published releases on GitHub, Apache-2.0 licensed, 2,958 commits, 26 stars. The compiler is implemented in Go (85.5% of the source) and ships native binaries for macOS (Intel and Apple Silicon) and Linux plus a WebAssembly target used by nine in-browser demos. Standard library covers `std/io`, `std/fs`, `std/json`, `std/zip`, `std/xml`, `std/crypto`, `std/http`, `std/net`. The benchmark dashboard runs 33 tasks across 8 frontier models in three modes — zero-shot, self-repair, and full agentic — on every release. The bet is that the rest of the catalogue's verification entries are designing a language a human reads and an AI writes, while AILANG is designing a language an AI both writes and maintains. The next test is whether the agent-authored development model produces a standard library deep enough to compete with MoonBit's roughly two-year head start (MoonBit launched 18 August 2023). ## Agent tooling. `SKILL.md`, `AGENTS.md`, and `CLAUDE.md` ship in the repository; `llms.txt` and `llms-full.txt` are served from the docs site. A remote MCP server exposes typed tools for stdlib lookup, examples, design docs, and the benchmark dashboard. The `ailang_bootstrap` plugin installs slash commands (`/ailang:prompt`, `/ailang:new`, `/ailang:run`, `/ailang:challenge`) into Claude Code and the equivalent extension into Gemini CLI; both download a platform-matched compiler binary on install. The CLI emits structured per-effect traces designed for the agent's next iteration to act on. ## Design DNA - **[Vera](https://agentlanguages.dev/languages/vera.md)** *(Verification)* — Vera tracks LLM inference as one <Inference> effect; AILANG carves authority into IO, FS, Net, Clock, AI as separate capability categories granted per run. - **[Boruna](https://agentlanguages.dev/languages/boruna.md)** *(Orchestration)* — Both build capability-based effect systems; Boruna enforces declared effects at the VM, AILANG enforces them at the type system and the CLI capability flag. - **[MoonBit](https://agentlanguages.dev/languages/moonbit.md)** *(Verification)* — Both ship effect typing on a functional core; MoonBit's effects are conventional and general-purpose, AILANG's are row-polymorphic and carved for agent-relevant authority. ## Timeline - **Sep 2025** — First public release on GitHub under Apache-2.0. - **Jan 2026** — AILANG reaches v0.6.2; Mark Edmondson publishes the language framing on dev.to. - **May 2026** — v0.20.1 ships. 110 releases, 2,958 commits. 33-benchmark dashboard runs across 8 frontier models on every release. MCP server, Claude Code plugin, and Gemini CLI extension all in production. --- HTML version: https://agentlanguages.dev/languages/ailang/ Catalogue index: https://agentlanguages.dev/llms.txt Catalogue homepage: https://agentlanguages.dev/index.md