Australian sheep farmer uncle breaks through AI programming ceiling with 5 lines of code, causing a major shakeup in Silicon Valley. Claude Code’s father hasn’t written code in 30 days, even sparking a new breed of Cowork explosion, leading to a revolutionary shift in software development. This article is based on a piece by Xin Zhiyuan, organized, translated, and written by Foresight News.
(Background recap: Elon Musk xAI launches “Grok Code Fast 1” programming model: Cursor, Copilot, Windsurf… limited-time free use, breaking through speed, scale, and price)
(Additional background: OpenAI’s rumored $3 billion acquisition of “automatic coding神器 Windsurf,” targeting the Vibe Coding big business opportunity)

Table of Contents

• The mystery of five lines of code
• Claude Code’s father praises: I don’t need to write code anymore
• Closest to AGI? Ralph-Wiggum震動整個硅谷
• Failure itself is valuable data
• Ralph Wiggum rising, software development dying

Recently, a story about an Australian sheep farmer uncle using 5 lines of code to break the AI programming ceiling has gone viral.

By the end of 2025, during sheep dung shoveling breaks, Geoffrey Huntley wrote the following Bash script containing only 5 lines:

while :; do cat PROMPT.md | claude-code ; done

At that time, he probably never imagined that within just a month, these few lines of code would trigger a wave of technological frenzy, directly overturning today’s Silicon Valley!

It can be said that the previously popular Claude Code and the recent viral Claude Cowork are all intricately connected to these five lines of code.

Even an engineer predicted: 2026 will be the year Ralph Wiggum takes over Silicon Valley!

The mystery of five lines of code

What exactly do these five lines of code mean?

In plain language: “Please complete this task. If tests fail, don’t bother trying again. You can look at error messages yourself, write code yourself, retry yourself. Try as many times as you want; as long as there’s no error, modify it to death. No leaving work!”

AI truly believed it.

This endless loop of abusive commands allowed AI to really write code without human intervention.

Therefore, the sheep farmer uncle named this loop Ralph Wiggum, the eternally optimistic little boy from “The Simpsons.”

Unlike traditional “aim to get it right the first time,” Ralph Loop’s core idea is to assume you won’t get it right on the first try.

But as long as it’s wrong, the compiler will report an error, and tests will fail. This error message is the most valuable treasure, precisely telling AI where it went wrong.

Thus, AI can have a great epiphany.

Now, Ralph Wiggum has gone from a cartoon character to one of the most influential names in AI.

It can even be said that Ralph-Wiggum has brought today’s large AI models very close to AGI.

Claude Code’s father praises: I don’t need to write code anymore

Why do Ralph-Wiggum loops lay the foundation for Claude Code and Cowork?

The story begins at the end of 2025.

After noticing the magical effect of these five lines of code, Boris Cherny, head of Anthropic’s Claude Code, officially incorporated Geoffrey Huntley’s script and launched the official Ralph-Wiggum plugin.

Since then, Claude Code has been like divine aid.

In Claude Code, as long as you give the following command:

/ralph-loop “Build a REST API for todos. Requirements: CRUD operations, input validation, tests. Output COMPLETE when done.” –completion-promise “COMPLETE” –max-iterations 50

Claude can realize:

• Continuous iteration – trying repeatedly, even on failure
• Self-referential learning – improving based on test results and previous code
• Until completion – looping until all requirements are met
• Output completion promise – outputting a specified completion mark when done

At the end of 2025, Boris Cherny’s sharing caused a major earthquake in the developer community.

He personally admitted: in the past thirty days, 100% of his contributions to the Claude Code project were completed by Claude Code itself!

Boris recalled that in the past thirty days, he submitted 259 PRs—497 commits, added 40,000 lines of code, and deleted 38,000 lines. Every line was written by Claude Code + Opus 4.5.

At that time, Claude could already run continuously for minutes, hours, or even days. It can be said that software engineering is undergoing a dramatic transformation, and we have stepped into a new era of coding.

Why can Claude run continuously for days? Boris explained that when it stops, a stop hook can be used to “poke” it, allowing it to continue.

And the behind-the-scenes hero of this hook is Ralph-Wiggum!

See this link for details: https://github.com/anthropics/claude-plugins-official/tree/main/plugins/ralph-wiggum

Because this news was too explosive, developer messages almost overwhelmed Boris’s private messages. Two days later, Boris shared his exclusive secret.

In part 12, Boris mentioned that for tasks with especially long execution times, he usually adopts several methods, one of which is using the Ralph-Wiggum plugin.

(a) After task completion, prompt Claude to use a background agent to verify its work;

(b) Use the agent’s Stop hook for a more certain, controllable verification;

© Or use the Ralph-Wiggum plugin

In other words, just one month after its birth, these 5 lines of code gave rise to today’s huge Claude Cowork explosion!

Closest to AGI? Ralph-Wiggum震動整個硅谷

At the same time, Ralph-Wiggum’s continuous iteration and looping design have also enabled other developers to create miracles repeatedly.

At Y Combinator Hackathon, someone used it to generate 6 complete code repositories overnight; someone spent only $297 on API costs to complete a $50,000 contract.

Within three months, someone used this method to develop a programming language called cursed!

Videos explaining the Ralph loop are flooding YouTube.

Developer educator Matt Pocock recently explained in detail why Ralph is “so powerful.”

The ultimate dream of programming intelligences is that when you wake up in the morning, the code is already written.

Your AI intelligence quietly worked all night, cleared the backlog, and the code it produced can run directly.

In his view, the Ralph plugin is already very close to this dream: “This is the most powerful AI programming tool I’ve used, enabling long-running intelligent agents to truly deliver usable code.”

CEO and founder of blockchain token creation platform Tally, Dennison Bertram, posted:

No joke, this might be the closest thing I’ve seen to AGI:

This prompt and Claude are definitely a beast.

Arvid Kahl, founder and CEO of the automatic podcast business intelligence extraction and brand detection tool Podscan, said the new approach is pioneering the future with excellent results:

As Chicago entrepreneur Hunter Hammonds said: The million-dollar opportunity is right in front of you, but you’re not ready.

AI engineer and serial entrepreneur Ian Nutall said, “2026 is the year Ralph Wiggum takes over.”

Failure itself is valuable data

Ultimately, Ralph’s core technology is very simple: a Bash loop.

But the official plugin implements this simple principle more cleverly:

Instead of executing scripts outside the dialogue, it directly embeds a Stop Hook within Claude’s conversation.

You assign Claude a task and a “completion marker.”

Claude attempts to exit after completing the task—

If it doesn’t detect the completion marker, the Stop Hook intercepts the exit and re-sends the same prompt into the system.

Thus forms a “self-feedback closed loop”:

Claude can see its previous output, error logs, or Git history each round, then try to fix issues.

Developer educator Matt Pocock describes this shift as a “paradigm shift” in AI programming:

Evolving from waterfall development (Waterfall) to true AI agile development (Agile).

You no longer need to preset a series of fragile execution steps, but instead:

• AI autonomously “claims a task card”
• After completing, it finds the next one itself
• Continues looping until all tasks are done

The true power of the initial Ralph version is not just the “loop” itself, but that naive, persistent trial-and-error attitude.

The most critical point: Ralph is not protected, not shielded from “erroneous outputs.”

It faces chaos directly, admits failure.

Behind this is an extreme but effective philosophy: if you let the model constantly face its failures without safety nets, it will eventually “dream” of correct answers under pressure, just to break out of the dead cycle.

Huntley’s version emphasizes brute-force iteration and relentless tactics; Anthropic’s version is based on a gentler principle: failure itself is valuable data.

This is clearly stated in the official documentation:

The plugin achieves self-feedback control through a special mechanism called Stop Hook—intercepting AI’s exit behavior and determining whether the task is truly complete.

The plugin’s execution mechanism is as follows:

• Intercept exit: When Claude believes it has completed the task and is about to exit, the plugin intercepts this action
• Verify completion marker: Detect whether the specified (e.g., “pass all tests”) has been output
• Inject feedback: If not completed, the plugin formats the error as a structured data object and feeds it back into the AI model for another attempt

But the official Ralph Wiggum plugin from Anthropic disappointed Geoffrey Huntley’s collaborator Dex:

• Without adding --dangerously-skip-permissions, it easily crashes
• Hook installation location is strange, and the state tracking files are hard to find
• Complex logic, deleting error files can even cause the entire repo to go out of control

More importantly, it misunderstood Ralph’s essence: Ralph should not “run forever,” but rather “break the task into pieces and slowly chew through it in separate windows.”

So, he still chose those 5 lines of Bash.

( Ralph Wiggum rising, software development dying

The entire developer community is just now realizing the power of AI.

Recently, Ralph Wiggum has become popular.

But most people haven’t realized yet: Ralph is just a starting point.

True advanced AI users have already mastered much more complex techniques than Ralph.

And they’re not just doing small tricks—they’re using these techniques to clone entire companies in just a few hours.

Michael Arnaldi started programming at age 11, initially to crack games.

![])https://img-cdn.gateio.im/social/moments-490c9a5f3a-0b33572f09-8b7abd-e2c905###

Since then, from core-level development to the highest abstraction layer of TypeScript, he has written almost all levels of code, now serving as founder and CEO of Effectful Technologies.

He once believed that programming was everything in life. But now, all that has been thoroughly ended.

Most software developers haven’t even realized the essence of this huge change.

They are obsessed with model wars: Is Claude better or GPT? Has Gemini caught up? Can open-source models compete? Frankly: they are completely missing the point.

The key lies in “process,” not “model.” The model is just one part of the process.

Just like traditional software development: not all programmers need top-tier skills, but as long as the process is mature, ordinary developers can produce good products.

The same applies to AI programming:

A mid-tier model + excellent process far surpasses a top-tier model + chaotic process.

This is an unsettling fact: the truly advanced practices are not yet public.

High-level users don’t share because these techniques are too powerful and disruptive. We will eventually move toward openness, but not yet.

Ralph is indeed a good starting point, but it has limitations.

In the next two years, you will start hearing more about Lean, TLA+, Agentic Infrastructure discussions.

From programming intelligences to intelligent programming infrastructure, the entire software industry will undergo a profound transformation.

He gave two examples:

• He used 2 hours to create a modernized simplified Bloomberg terminal version with Ralph;
• A friend in the legal profession, with almost zero programming experience, completed a GDPR compliance detection tool by chatting with Claude Code.

To speak with facts, he decided to open-source an Accountability accounting system:

• Supports cross-company, multi-currency, US GAAP-compliant accounting system,
• Normally takes several months for a development team.

And he plans to “bring Ralph out” in his spare time, deliberately not using any “black tech” or hidden tricks.

Just using open, basic technology, applied correctly.

But don’t misunderstand: “software development is dead” doesn’t mean “software engineering is dead.”

Engineers are no longer “people who write code,” but “people who build systems that can write code.”

They design technical routes, build tools…

They can master new tools in minutes—at most a few hours.

This means: many of the best practices accumulated over the past 40 years are already outdated.

Team structures, development processes, technology stack choices—all need to be reconstructed.

Individuals are becoming more powerful than ever.

One person = an entire team of the past.

Software development is dead, engineering is reborn, and AI will reshape everything.

Welcome to the new era.

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