Mea Culpa – Dark Hours

Perceived Plagiarism and AI Blame

• Many commenters think the “Claude accidentally cloned another app” story is not credible.
• Evidence cited: same app name (or near-identical), same specific bug, same feature set, similar branding, and removal of the original project’s license.
• Some see this as “AI ate my homework” – a convenient way to dodge responsibility.

Misleading App Store Rejection Narrative

• The bigger scandal in the thread is the earlier narrative about Apple rejecting a “pure astronomy” app.
• It later emerged the original submission was an astrology/tarot app in a saturated category, and it’s unclear whether the astronomy clone was ever actually submitted.
• A well-known Apple blogger retracted a critical post after realizing the story he’d been given omitted key facts, leading many here to feel he was used for publicity.

Responsibility and “AI Did It” Excuses

• Strong consensus: you are fully responsible for anything you ship, AI-assisted or not.
• “Claude did it” is compared to “I was hacked” or “the computer did it” as a modern scapegoat.
• Several note a broader pattern: companies and creators repeatedly blame unnamed AI tools or workers after being caught.

How Likely Is Exact LLM Copying?

• Some argue LLMs can regurgitate training data or open-source code, citing ongoing copyright lawsuits and safety features that try to prevent close mimicry.
• Others with hands‑on experience say models usually don’t wholesale clone repos without explicit prompts, and often add attribution or fix bugs, so a bug-for-bug duplicate plus same name doesn’t “pass the sniff test”.
• Overall, whether the model itself cloned the app is considered unclear, but most think human intent is central.

Open Source, Licensing, and Provenance

• Several emphasize: OSS is fine to reuse, but re‑publishing nearly unchanged under almost the same name and domain is in poor taste.
• Discussion touches on whether the original project’s copyright was properly asserted, but moral responsibility is seen as separate from legal technicalities.
• People worry more generally about “vibe-coded” AI projects concealing unacknowledged third‑party code and the difficulty of tracking provenance.

Reactions to the Apology and Reputation Impact

• The new post is described as a “limited hangout”: partial admission while still omitting the most damaging parts (e.g., how the story to the blogger was framed).
• Some initially wanted to praise the apology and domain redirect to the original app, but changed their view after reading more context.
• Others feel fully burned: it now taints trust in the developer’s other work (including the RSS reader), with some users reporting that app feels AI‑built and buggy.
• A minority argues the apology and withdrawal from that product space are at least better than doubling down and that this shouldn’t be career-ending, though most agree the reputation damage is real.

Broader App Store and Astrology-App Issues

• Commenters clarify that Apple doesn’t ban astrology outright but treats it as an over‑saturated, low‑effort category (like flashlight or fart apps), requiring substantial differentiation for new submissions.
• Some note past problems with scammy horoscope subscription apps, suggesting Apple has pragmatic reasons to be stricter.

Wider Reflections on AI Slop and Content Trust

• The case becomes a springboard for broader worries about “AI slop” in code, games, marketing, and music, and the erosion of human authorship and accountability.
• People compare this to deceptive AI use in advertising (e.g., music demos for guitar strings) and to game devs quietly using AI without disclosure.
• Several foresee growing devaluation of online content and a shift of “prestige” toward in‑person, physical, or clearly human activities.