AI red flags aren't vague answers. The real signal is precision you can't easily verify - numbers, named reports, exact citations. That's where errors travel furthest. 🎯 Most people look for the wrong signals: hedged language, awkward phrasing, obvious gaps. Those stopped working as models improved. What remains is counterintuitive: the more specific an answer sounds, the higher the risk. The model isn't retrieving facts. It's generating text that fits the pattern of a correct answer. And if correct answers normally include numbers, dates, and citations - the model produces them whether they're accurate or not. Before using AI output: scan for specific claims first. Numbers, named sources, exact figures. Ask: can I verify it quickly? If not, that's your signal. 🔗 https://unrsnbl.ai/notes/e035-red-flags ▶️ Full playlist: https://www.youtube.com/playlist?list=PL3pL28ov_GlKZ8fgcP04yi_nBuBc_i65C 📦 Join us in Telegram: https://t.me/unreasonableai Start tagging your content: www.contentags.com #ai #shorts #notesonai #aibasics #llm #genai #CTHuman

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