Unverified60% confidenceOpinionExact time
The stateless nature of LLMs (each conversation being independent) prevents them from maintaining design consistency across multiple interactions, which is a fundamental limitation at the technical architecture level.
2
Sources
60%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
Claude Code's Frontend UI Too Ugly? This Open-Source Skill Teaches AI Professional Design
bilibili郭宏志-老郭5/31/2026
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Related Claims
UnverifiedLarge language models (LLMs) have no memory and treat each conversation as an independent interaction, making it difficult to support continuous complex tasks.77% similarUnverifiedLLMs have obvious limitations: they lack long-term memory of the internal context of a specific organization, cannot truly understand interpersonal relationships and power structures, and are prone to hallucination or over-execution when facing ambiguous instructions.76% similarUnverified目前业界尚无完美的提示注入防御方案，指令与数据的根本性混淆是LLM架构层面的限制71% similarUnverifiedLLM本质上无法从架构层面区分被处理的数据和应当执行的指令，这类攻击极难从模型本身彻底根除70% similarUnverifiedThe root cause of LLM application issues is often not code logic errors, but soft factors such as prompt wording, context management, and retrieval strategies, which are difficult to automatically fix with deterministic rules and require agents with semantic understanding capabilities to close the loop.70% similar
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