Iterative Agent Loop

Process agents published

Also known as: Ralph Wiggum Loop, Ralph Loop, Persistence Loop, Autonomous Iteration

Definition

A pattern for running AI coding agents autonomously by wrapping them in an external loop that restarts execution after each completion or failure until a verifiable completion condition is met. Unlike traditional agent loops where the LLM decides when to stop, iterative agent loops use external verification (tests passing, completion promises, build success) to determine when the task is truly done. This enables hours-long autonomous operation without human intervention.

What this is NOT

  • Not a standard agent loop (agent loops are internal; iterative loops are external)
  • Not ReAct (ReAct trusts self-assessment; iterative loops use external verification)
  • Not human-in-the-loop (though humans can monitor)
  • Not the same as retrying on error (iterative loops embrace failure as data)

Alternative Interpretations

Different communities use this term differently:

ralph-wiggum

A bash-loop pattern where an AI agent is run repeatedly, with each iteration getting a fresh context window but persistent filesystem state (via Git). The loop continues until external verification confirms completion or a maximum iteration count is reached.

Sources: Geoffrey Huntley - ghuntley.com/ralph, Anthropic Claude Code Ralph Wiggum plugin, HumanLayer: A Brief History of Ralph

ai-engineering

A design pattern that shifts control from the AI agent to an external orchestrator, enabling more reliable autonomous operation by not trusting the agent's self-assessment of task completion.

Sources: Various AI engineering blogs, VentureBeat coverage (2026)

Examples

  • while :; do cat PROMPT.md | claude-code; done - the original Ralph Wiggum bash loop
  • An agent that runs tests after each change and only stops when all tests pass
  • A migration agent that processes files one by one, restarting until no files remain
  • An overnight coding session that produces a working feature by morning

Counterexamples

Things that might seem like Iterative Agent Loop but are not:

  • A standard chatbot conversation (no persistence across restarts)
  • A ReAct agent that decides when it's done (self-assessment, not external verification)
  • A single LLM API call with retry logic (no persistent state between attempts)
  • Human-supervised coding with approval at each step

Relations

  • specializes agent-loop (Iterative loops are a specific pattern of agent loop execution)
  • requires sandbox (Safe execution requires sandboxed environments)
  • overlapsWith autonomous-agent (Enables truly autonomous agent operation)
  • inTensionWith human-in-the-loop (Iterative loops minimize human involvement during execution)

See Also

Implementations

Tools and frameworks that implement this concept: