AI Parlance

v0.1 is still a draft language. The monorepo ships a full v0.1 parser/validator (Core + Infra + Security + Behavior) and Preview emitters across the transpiler matrix (aip parse / validate / emit). Phase C (reference toolchain) is complete; Phase D deepens TypeScript / OpenAPI / SQL and distribution — see ROADMAP and Get started here. This documentation remains the normative source for the language.

AI Parlance is an AI-first language for intermediate representation (IR) in AI-assisted software generation — focused on data-oriented applications, APIs, authorization, and declarative automations. Humans, agents, and LLMs describe systems in .aip; transpilers turn the spec into concrete implementations.

Human or AI
↓
AI Parlance (.aip)
↓
AST + validation
↓
Transpilers
↓
Go, TypeScript, SQL, OpenAPI, …

Normative details: Specification.

Why it exists

When models generate code directly in general-purpose languages, they face:

large amounts of boilerplate (CRUD, routes, validation, migrations)
inconsistency across stacks
large context → more tokens and more hallucination
business rules and permissions scattered in generated code

AI Parlance concentrates intent in a compact semantic layer before implementation.

What it describes (and what it does not)

Describes	Does not describe
entities, types, relations	custom UI
CRUD, indexes, migrations	complex algorithms
auth, policies	integrations without a dedicated block
domain workflows and events	hand-written imperative SQL

Minimal example

app Demo @0.1 {
  database postgres
}

entity User {
  name: string required
  email: email required unique
}

crud User

See examples/minimal.aip. Every v0.1 spec requires one app block (Specification). One definition can feed multiple generators (see transpiler matrix).

AI-first principles

The language prioritizes, in order:

domain intent and semantics
predictable structure for LLMs
static validation before generation
multi-target implementation via transpilers

Documentation map

Page	Content
Get started here	Install, CLI, emit, and test
First emitters	Official Preview emitters (matrix)
CRUD walkthrough	Complete blog CRUD → emit
Examples	All reference `.aip` specs
Emitters	Maturity scores & objectives per emitter
Specification	Grammar, builtins, policies, stability
Cost impact	Tokens, honest comparisons
Syntax	Core + Infra blocks
Database	Migrations, indexes, naming
Security	Auth, policies, rate limit
Workflows	Events, jobs, queues
Agents	Prompts, `ai_context`, best practices

Next step for newcomers: Get started here or the CRUD walkthrough. Reference specs: blog-crud.aip · crm-reference.aip.

Overview

Examples

Emitters

Reference

Domains

AI

Introduction

AI Parlance

Why it exists

What it describes (and what it does not)

Minimal example

AI-first principles

Documentation map

​AI Parlance

​Why it exists

​What it describes (and what it does not)

​Minimal example

​AI-first principles

​Documentation map

AI Parlance

Why it exists

What it describes (and what it does not)

Minimal example

AI-first principles

Documentation map