15 years later, Microsoft morged my diagram

Origin and Meaning of “Morged”

• The thread centers on a Microsoft Learn article whose GitFlow diagram was obviously AI-generated from the classic Git branching model diagram, producing text like “continvoucly morged” and “tiന്ന” instead of “continuously merged” and “time”.
• Commenters initially thought “morged” was new slang; after seeing the screenshot, they treat it as an instant meme.
• Multiple proposals to standardize “morge”:
  • As a verb: using an AI tool to badly, recognizably plagiarize and degrade an original work.
  • As a noun (“morgery”): the resulting AI-slop artifact.
• Many hope the term and story become a lasting reference for AI-mangled plagiarism.

Critique of Microsoft and Its Processes

• Strong consensus that the diagram is both plagiarized and technically nonsensical: broken arrows, missing elements, garbled text, incorrect axes.
• Several see this as “on brand” for Microsoft: half‑ass features, poor QA, and now AI in documentation without care.
• The fact it stayed live for ~5 months is viewed as evidence that:
  • Authors don’t read what they publish.
  • Review processes are weak or absent.
  • Documentation has become “checkbox output” that nobody really owns.
• A VP’s public response blaming a “vendor” and citing company size and speed is widely seen as hollow; many argue this is a systemic, not one‑person, failure.

AI Slop, Copyright, and “Copyright Laundering”

• Multiple comments frame this as typical AI “memorization”: near-copies of training data with small mutations.
• Worry that generative models function as de facto copyright laundering: washing recognizable works just enough to obscure origin and avoid attribution.
• Some argue intent (ignorant use of a tool vs deliberate theft) is less important than outcome: plagiarism is plagiarism.
• Concerns extend to code generation (e.g., GPL code leaking into proprietary codebases) and to search/answer systems that paraphrase journalism or docs while diverting traffic from originals.

Broader “Ensloffication” of Content

• Similar AI-slop examples cited from LinkedIn, Amazon-like marketplaces, YouTube documentaries, and AI thumbnails.
• Pattern described: more cheap, plausible-looking content; less human attention, review, and understanding.
• Several see this as cultural degradation: decades of human work diluted by low-quality, unattributed machine derivatives.

Side Discussion: GitFlow Itself

• Some use the occasion to re-litigate GitFlow:
  • Critics question the value of a long‑lived develop branch versus trunk‑based development with tags.
  • Defenders note its usefulness when maintaining multiple active release lines and doing hotfixes.
• Even supporters agree the original diagram was influential and carefully crafted, which heightens frustration at its morged copy.