AI makes you boring

AI and Writing Style

• Many commenters report a distinct “LLM voice”: grammatically correct, padded, and generic. When people replace their own prose with this, it feels uncanny and less personal.
• Others use models as scaffolding: generate outlines, reorganize notes, or turn bullet points into drafts, then aggressively rewrite in their own voice. They see this as a cure for blank-page syndrome, not a replacement for thinking.
• Several argue “writing is thinking”: if you outsource too much drafting, you offload the hard part where ideas sharpen.

Show HN, Gatekeeping, and Effort as Signal

• A major thread is about “vibe‑coded” Show HN posts: quick, AI-built demos with shallow problem understanding, often duplicating existing tools or solving non‑problems.
• Some see criticism of these posts as elitist gatekeeping; others say it’s just standards and curation. Effort and struggle are treated as a proxy for sincerity, depth, and domain insight.
• Debate over what Show HN is “for”: craft and deep technical discussion vs just showing anything that “works”.

Originality, Thinking, and “Vibe Coding”

• One side: original ideas emerge from long immersion and wrestling with constraints; offloading that to LLMs yields shallow, average ideas and trains users to only ask questions models handle well.
• Counterpoint: most human thinking is unoriginal anyway; AI can be a powerful rubber duck, critic, or research assistant and can even help reveal when your idea isn’t new or good.
• Several frame AI as raising the floor: it empowers previously non‑productive “idea people” to ship things, without changing how genuinely thoughtful people work.

AI in Programming Practice

• Productive pattern: let AI handle boilerplate, test scaffolding, and glue code, while humans make architectural, UX, and domain decisions and review every change.
• Critics respond that “boring parts” are where much learning happens; skipping them weakens intuition, maintainability, and security, especially when no one deeply understands the generated code.
• Consensus: AI is a power tool—can boost good engineers or enable massive slop, depending on taste, skill, and review culture.

Communication Slop and Workplace Use

• Multiple anecdotes of AI-written emails and docs: one person expands two sentences into ten AI paragraphs; another uses AI to re‑summarize them back to two. This is described as “productivity theatre” and the opposite of compression.
• In B2B outreach and corporate comms, polished AI text is now read as a negative signal; slightly messy human writing can stand out as proof of actual effort.

Art, Taste, and Derivativeness

• In writing, music, and visual art, LLM outputs are often seen as “structurally derivative”—smooth but lacking personal stakes or taste.
• Some argue that all art relies on randomness, tools, and prior work anyway; what matters is the human’s taste in prompting, curating, and editing.
• Others insist that intention, lived experience, and risk are what give art emotional weight, and current AI pipelines can’t substitute for that.

Effects on Online Content and Communities

• Several note a flood of shallow blogs, tools, and Show HN posts: AI makes it cheap to push half‑baked ideas past the old activation energy that used to filter them out.
• That, combined with AI‑optimized SEO prose, is blamed for homogenized search results and struggling niche sites.
• Some predict more private or tightly curated communities as traditional quality signals (effort, style, depth) get devalued by easy AI generation.

Diverging Attitudes Toward AI

• One camp sees “AI makes you boring” as mostly about low‑effort users; interesting people using AI thoughtfully remain interesting and may even do more ambitious work.
• Another camp views widespread AI use as genuinely corrosive to thinking, learning, and signal‑to‑noise, and is deliberately avoiding it for creative work.