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phodal
phodal
May 10, 2026 · Artificial Intelligence

From /goal to Long‑Running Asynchronous Agents: Making AI Sustainably Deliver Complex Tasks

By experimenting with OpenAI’s /goal feature, the author shows how to turn ad‑hoc AI prompts into a structured, long‑running loop that records progress in Git, README and test artifacts, enabling agents to handle complex engineering tasks across multiple sessions with clear checkpoints and human‑in‑the‑loop control.

AI agentsPrompt EngineeringRalph Loop
0 likes · 12 min read
From /goal to Long‑Running Asynchronous Agents: Making AI Sustainably Deliver Complex Tasks
Architect
Architect
May 10, 2026 · Artificial Intelligence

Long‑Running Agents: From Ralph Loop to Hand‑over‑Ready Harness

The article analyzes the challenges of long‑running AI agents, showing that persistence alone is insufficient and that reliable hand‑over requires explicit specifications, external state files, drift mitigation, sub‑agents, and a verifiable evidence chain to keep the work understandable for the next model or human.

AI agentsContext EngineeringHarness
0 likes · 25 min read
Long‑Running Agents: From Ralph Loop to Hand‑over‑Ready Harness
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Feb 26, 2026 · Artificial Intelligence

How One Developer Built a Full AI‑Powered Development Team with OpenClaw and Claude Code

The article details how a solo developer used OpenClaw as an orchestration layer together with Claude Code, Codex and Gemini agents to automate the entire software development pipeline—from customer request to PR merge—achieving 94 commits in a day, 7 PRs in 30 minutes, and a production‑ready system for under $200 a month.

AI agentsAutomationClaude Code
0 likes · 16 min read
How One Developer Built a Full AI‑Powered Development Team with OpenClaw and Claude Code
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 27, 2026 · Artificial Intelligence

Why AI Coding Assistants Quit Early and How Ralph Loop Keeps Them Working

The article examines common pitfalls of AI programming assistants—premature exits, fragile single‑prompt workflows, costly re‑prompting, and context loss—explains that these stem from unreliable LLM self‑evaluation, and introduces the Ralph Loop (also called Ralph Wiggum Loop) as a robust, stop‑hook‑driven solution that forces continuous iteration until explicit, verifiable completion criteria are met.

AI codingAgent LoopAutomation
0 likes · 28 min read
Why AI Coding Assistants Quit Early and How Ralph Loop Keeps Them Working
Tech Minimalism
Tech Minimalism
Jan 21, 2026 · Artificial Intelligence

Why a Simple Bash For‑Loop Beats Complex Multi‑Agent Systems in Claude Code

The article explains how the Ralph loop, a minimalist bash for‑loop design introduced by Geoffrey Huntley, lets Claude Code repeatedly execute tasks until completion, offering a simpler, more reliable alternative to elaborate multi‑agent orchestrations for quantifiable, verifiable programming work.

AI automationClaude CodeRalph Loop
0 likes · 12 min read
Why a Simple Bash For‑Loop Beats Complex Multi‑Agent Systems in Claude Code
AI Tech Publishing
AI Tech Publishing
Jan 12, 2026 · Artificial Intelligence

Ralph Loop: Engineering Continuous Iteration for AI Agents

Ralph Loop introduces an externalized iterative loop that forces AI agents to keep working until objective completion criteria are met, dramatically extending effective runtime from hours to a full day or more and shifting human‑agent collaboration from frequent supervision to efficient delegation.

AI AgentIterative AutomationLLM
0 likes · 17 min read
Ralph Loop: Engineering Continuous Iteration for AI Agents