AI Ate Its Own Tail, and I Learned Something About Writing

# The Experiment

I used AI to analyze the repository of a project AI itself was working on. The AI went through every commit and file history, and from that it reconstructed the entire development process.

The project itself was a game challenge. I was using mostly Claude Code in “YOLO mode.” In practice, that meant setting the flag dangerously-skip-permissions and run it in the loop:

alias loop='while :; do cat prompt.md | claude -p --dangerously-skip-permissions; done'

My idea was simple: create a human-readable record of how the project evolved. Not just code. A story. How AI agent tried one thing, failed, switched to a new algorithm, improved it, created another, and kept iterating. I wanted a narrative version of the repo. Something I could come back to later and instantly understand what had happened.

So I asked AI to write an article from the repo’s history. The result wasn’t bad. I got a timeline of algorithms, changes, snippets of code. A deep dive into how the project came together. The downside? It was padded with AI filler—sloppy sentences, too much noise. That was my fault. I’d just said something like, “go through it and write a super long deep dive article.” With better prompting, I’m sure it would have been sharper. But even so, it worked.

I shared the experiment on Hacker News. It quickly picked up 20–something comments and a dozen or so upvotes before it was flagged. The response was mixed. Some people dismissed it. Others saw value in it. I jumped into the thread, adding explanations I hadn’t included in the blog post itself. That back-and-forth made me realize: this experiment wasn’t just about documenting a project. It was about the future of writing.

# The Real Question

Here’s the thought that stuck: if AI and humans are co-writing, how do we show the human effort? How do we prove what came from where? Do we really need to?

One idea is a verifiable proof-of-work system. Not a changelog, not a Git diff—something higher level, human-readable, but still verifiable. Imagine a lightweight metadata trail. Step by step:

• I started with an idea.
• I prompted AI.
• AI drafted an article.
• I added comments.
• AI revised.
• I made manual edits.
• I published.

Each step logged with a timestamp. Bundled into a signature. Anyone could open it up, verify it, and follow the creative flow. That kind of provenance would let us track how a piece of writing—or any piece of work—was actually made.

I’ve already experimented with this idea in another project, MindMark—an AI-native writing platform that makes human thinking visible through immutable process journals, cryptographic verification, and transparency tools.

# The Future is Collaborative

Because the truth is, the future of writing is AI-human collaboration. We’ll see fewer “pure” human works. But then again, what counts as pure? If I use spellcheck, a grammar linter, or even just autocomplete—am I writing alone? We already accept those tools.

AI is the next step, just louder, faster, more opinionated.

I’ve already started with declaring this on my blog. Now, when I publish something that was AI-augmented, it shows a clear tag “SLOP”, and a note at the top: “This article was heavily written by AI.”

It’s small, but it feels honest.

In the end, this whole process—from running YOLO code with Claude, to generating an article, to debating on HN—brought me to one realization: the line between human and machine writing is thin.

# This Isn’t New

What matters is not hiding it. What matters is building systems where the collaboration itself is visible, traceable, and human-approved.

Andy Weir’s The Martian is a great reminder that this kind of collaboration isn’t new. He first published the book chapter by chapter on his blog, where readers fact-checked the science and flagged pacing issues. Weir revised, reposted, and refined until the story was sharp enough to self-publish, which snowballed into a publishing deal and a movie.

The pattern is the same: draft, feedback, revision, iteration. Weir had a crowd of readers; today, we have AI. The tools change, but the creative loop—writing as collaboration—stays the same.