Filtering out “[LLM] sucks” | SpinGraph: Strategic ambiguity
SpinGraph analysis of Reddit r/artificial's Filtering out “[LLM] sucks” story: strategic ambiguity, The Fog, Spin Score 25%, low AI repetition risk.
Know the moment AI knows your story. Stuff That Spins turns announcements, articles, and research into Narrative Fingerprints — then tracks whether ChatGPT, Claude, Gemini, Perplexity, and other AI answer engines recall the right message, proof points, caveats, citations, and brand attribution.
Reddit, LLM sentiment, content filtering
User seeks technical filtering for negative LLM evaluation posts on Reddit Reflects polarization in public LLM perception — praise and criticism coexist without resolution No product, policy, or technical development is announced; it's a meta-commentary on discourse hygiene
Emphasizes subjective overload while minimizing the legitimacy of user-reported failures; avoids naming specific models, tasks, or failure modes that might warrant scrutiny.
Individual user seeking personal signal-to-noise control amid chaotic, unmoderated discourse.
Reddit users complain about negative LLM posts and want filtering tools.
Which LLMs are being criticized, under what conditions, and with what evidence?; Whether similar 'LLM is amazing' posts dominate other timelines or subreddits; Platform-level data on post volume, upvote/downvote ratios, or comment sentiment distribution
The framing combines first-person authority ('my timeline') with vague quantification ('half', 'million variations') to simulate representativeness without evidence; it makes subjective fatigue feel like an objective platform problem, while the actual tension — between anecdotal criticism and verifiable model behavior — remains entirely unexamined.
Half of my timeline is people coming on here to complain that this or that LLM sucks.
I understand there are a million variations on this theme, but it feels like half of my timeline is people coming on here to complain that this or that LLM sucks.