ALP v80.0.0The Autonomous Lifecycle Protocol

Why ALP? ​

Git standardized version control. Docker standardized environments. OpenAPI standardized APIs. ALP standardizes how AI builds software.

Today every AI coding assistant (Devin, Claude Code, Cursor, OpenHands) relies on unstructured prompts and brittle context-scraping. They forget decisions, overwrite each other's work, and lose track of dependencies. ALP replaces scattered README.md, PRD.md, AGENTS.md, and TASKS.md files with one deterministic protocol stored natively in your repository (.alp/).

How it works ​

ALP turns your repository into a deterministic, machine-readable project specification that any AI agent can read, understand, and act on.

flowchart LR
    ALP[.alp/ Files] --> Parser[ALP Parser]
    Parser --> Graph[Dependency Graph]
    Graph --> Engine[Execution Engine]
    Engine --> Agent[AI Agent]
    Agent --> Task[Task Execution]
    Task --> Verify[Quality Gates]
    Verify --> State[Project State]

1. Write — Define your project in .alp/ files using the ALP protocol
2. Parse — The parser builds a dependency graph and validates against 49 JSON schemas
3. Execute — The engine topologically sorts tasks and compiles context bundles in < 2ms
4. Verify — Quality gates ensure tasks aren't marked done until tests pass
5. Remember — Cross-session memory eliminates redundant context scraping

Quick Example ​

Create a .alp file in your repository:

!alp-version: 80.0.0

@project
  id: my-project
  name: My Project
  version: 1.0.0
  state: active

@feature
  id: feat-auth
  name: Authentication
  description: OAuth2 + JWT authentication flow

@task
  id: task-login-ui
  name: Build login UI
  status: [ ]
  depends_on:
    - task-setup-db
  verify:
    - npm run test:login
    - npm run lint:login

@agent
  id: agent-frontend
  name: Frontend Specialist
  capabilities: [react, typescript, tailwind]

Then run:

# Validate your workspace
alp validate

# Execute the next available task
alp run

# Verify quality gates
alp verify task-login-ui

How it works (detailed) ​

1. The Execution & Verification Cycle ​

ALP parses your workspace into a Directed Acyclic Graph (DAG). Agents only receive the exact context they need, exactly when they need it.

graph TD
    subgraph Repository [Your Repository .alp/]
        D[Decision: Use PostgreSQL] --> T1[Task: Setup DB Schema]
        T1 --> T2[Task: Build REST API]
        R[Rule: No Raw SQL] --> T2
        C[Contract: @contract c-api] --> T2
    end

    subgraph ExecutionEngine [Execution Engine - alp run]
        T2 -->|Context Bundle - 1.8ms| Agent[Claude / Cursor Agent]
    end

    subgraph QualityGates [Quality Gates - alp verify]
        Agent -->|npm test| V{Tests Pass?}
        V -->|Exit 0| X[Mark x Done]
        V -->|Non-Zero| B[Mark ! Blocked]
    end

2. Autonomous Swarm Mesh & Skill Marketplace (v80.0.0) ​

flowchart LR
    subgraph SwarmNodes [Autonomous Swarm Nodes]
        A1[Agent Alpha\nCoder] <--> EM((Event Mesh\nPub/Sub))
        A2[Agent Beta\nReviewer] <--> EM
        A3[Agent Gamma\nTester] <--> EM
    end

    subgraph Marketplace [Swarm Marketplace]
        EM <--> SWM[Skill Registry\n@swarm_marketplace]
        SWM -->|Discover & Invoke| Cost[Cost & Metering Engine]
    end

The ALP Ecosystem ​

Getting Started in 60 Seconds ​

Step 1: Install the CLI ​

npm install -g @autonomous-lifecycle-protocol-alp/cli

Step 2: Initialize your workspace ​

alp init

This creates a .alp/ directory with a starter project.alp file.

Step 3: Define your first feature ​

Create .alp/features.alp:

!alp-version: 80.0.0

@feature
  id: feat-auth
  name: User Authentication
  description: OAuth2 + JWT authentication flow

@task
  id: task-login-ui
  name: Build login UI
  status: [ ]
  depends_on:
    - task-setup-db
  verify:
    - npm run test:login
    - npm run lint:login

Step 4: Validate and execute ​

# Validate your workspace
alp validate

# Execute the next available task
alp run

# Verify quality gates
alp verify task-login-ui

1. Ecosystem Overview ​

Future Plans & Roadmap ​

Released versions are tracked in the versioning spec. This section captures active and planned focus areas.

Current Release ​

V9 — Native Desktop (v80.0.0) — SHAM IDE cross-platform release with native ALP integration, Monaco editor, agent manager, auto-updater, and Pro/Enterprise licensing.

V10 — The Intelligence Era (v80.0.0) — Autonomous multi-agent orchestration with self-healing DAGs, predictive governance, edge-native execution, and AI-native lifecycle management.