{"question":"Welche fundamentalen Schwächen haben Large Language Models (LLMs)?","shortAnswer":"LLMs haben 8 fundamentale Schwächen: Halluzinationen, kein Langzeitgedächtnis, Kontextfenster-Limits, probabilistische Natur, fehlender Unternehmenskontext, keine Selbstreflexion, Prompt-Abhängigkeit und fehlende Strukturierung. Diese Schwächen machen LLMs alleine nicht produktionsreif für Business-Anwendungen.","detailedAnswer":null,"keyTakeaways":[{"title":"Halluzinationen","description":"LLMs erfinden plausibel klingende Fakten - gefährlich für Entscheidungen"},{"title":"Kein Gedächtnis","description":"Nach jedem Chat beginnt alles von vorn - kein Lernen über Zeit"},{"title":"Kontextlimit","description":"LLMs können nicht alles gleichzeitig sehen - übersehen Zusammenhänge"},{"title":"Kein Business-Kontext","description":"Ohne Unternehmenswissen nur generische Antworten möglich"}],"faq":[{"answer":"Only partially. Better prompts reduce hallucinations but don't eliminate them. For reliable facts, you need an external, deterministic knowledge source like a Knowledge Graph.","question":"Can I avoid LLM hallucinations with better prompts?"},{"answer":"Some weaknesses will improve (larger context windows, fewer hallucinations), but the fundamental architecture remains probabilistic and stateless. An Intelligence Layer will be necessary even for future models.","question":"Will future LLMs like GPT-5 fix these weaknesses?"},{"answer":"RAG helps with some weaknesses but not all. Especially: relationships between data, proactive alerts, and workflow guidance require structured systems. GraphRAG with Knowledge Graphs is significantly more powerful than vector-based RAG.","question":"Isn't RAG (Retrieval Augmented Generation) enough?"}],"framework":{"name":"LLM Weakness Analysis","acronym":null,"useCases":["AI Strategy Evaluation","LLM Deployment Planning","Intelligence Layer Design","Business Case for Knowledge Graphs","Risk Assessment AI Implementation"],"prerequisites":["Basic understanding of LLMs","Awareness of business-critical processes"],"tools":null,"timeToImplement":null},"meta":{"contentType":"framework","difficulty":"beginner","estimatedReadTime":12,"published":"2025-12-02T11:04:53.775Z","updated":"2025-12-02T11:04:53.775Z","language":"en","isCustomerResource":true},"citations":null,"canonicalUrl":"https://aprixity.run/en/wissen/framework/llm-schwaechen"}