Ralph Loop Agent

ralph-loop-agent

**Continuous Autonomy for the [AI SDK](https://ai-sdk.dev/)**

**Note**: This package is experimental. APIs may change between versions.

Packages

Package	Description
ralph-loop-agent	Core agent framework with loop control, stop conditions, and context management

Examples

Example	Description
cli	Full-featured CLI agent with Vercel Sandbox, Playwright, PostgreSQL, and GitHub PR integration

Installation

npm install ralph-loop-agent ai zod

What is the Ralph Wiggum Technique?

The Ralph Wiggum technique is a development methodology built around continuous AI agent loops. At its core, it's elegantly simple: keep feeding an AI agent a task until the job is done. As Geoffrey Huntley describes it: **"Ralph is a Bash loop."**

Named after the lovably persistent Ralph Wiggum from *The Simpsons*, this approach embraces iterative improvement over single-shot perfection. Where traditional agentic workflows stop when an LLM finishes calling tools, Ralph keeps going—verifying completion, providing feedback, and running another iteration until the task actually succeeds.

Think of it as `while (true)` for AI autonomy: the agent works, an evaluator checks the result, and if it's not done, the agent tries again with context from previous attempts.

┌──────────────────────────────────────────────────────┐
│                   Ralph Loop (outer)                 │
│  ┌────────────────────────────────────────────────┐  │
│  │  AI SDK Tool Loop (inner)                      │  │
│  │  LLM ↔ tools ↔ LLM ↔ tools ... until done      │  │
│  └────────────────────────────────────────────────┘  │
│                         ↓                            │
│  verifyCompletion: "Is the TASK actually complete?"  │
│                         ↓                            │
│       No? → Inject feedback → Run another iteration