{"slug": "your-llm-cannot-tell-when-it-is-wrong-build-for-that", "title": "Your LLM Cannot Tell When It Is Wrong, Build for That", "summary": "A developer argues that large language models (LLMs) inherently hallucinate because next-token prediction rewards fluent text regardless of truth, and this cannot be fixed by future model releases. The developer advocates building systems that acknowledge uncertainty rather than fabricating answers, and provides a guide on hallucination taxonomy and architecture.", "body_md": "Every LLM hallucinates, and it is not a bug the next model release will fix. Next-token prediction rewards fluent, plausible text, and a confident fabrication scores exactly like a confident fact. The model has no internal mechanism that separates the two.\n\nThat means the reliable systems are the ones engineered around the model:\n\nUsers forgive a system that says it is unsure. They do not forgive one that invents an answer with a straight face.\n\nThere is a full developer guide covering the architecture, a taxonomy of hallucination types, and implementation walkthroughs here: [https://www.adaptiverecall.com/ai-hallucinations/](https://www.adaptiverecall.com/ai-hallucinations/)", "url": "https://wpnews.pro/news/your-llm-cannot-tell-when-it-is-wrong-build-for-that", "canonical_source": "https://dev.to/paulcrinigan/your-llm-cannot-tell-when-it-is-wrong-build-for-that-422i", "published_at": "2026-07-12 16:04:56+00:00", "updated_at": "2026-07-12 16:14:30.698873+00:00", "lang": "en", "topics": ["large-language-models", "ai-safety", "ai-research", "ai-ethics", "developer-tools"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/your-llm-cannot-tell-when-it-is-wrong-build-for-that", "markdown": "https://wpnews.pro/news/your-llm-cannot-tell-when-it-is-wrong-build-for-that.md", "text": "https://wpnews.pro/news/your-llm-cannot-tell-when-it-is-wrong-build-for-that.txt", "jsonld": "https://wpnews.pro/news/your-llm-cannot-tell-when-it-is-wrong-build-for-that.jsonld"}}