Unverified50% confidenceOpinionExact time
The author points out that traditional mock tools such as Postman and WireMock are not well-suited for handling non-deterministic tool calls from LLMs.
1
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50%
Confidence
Long-term
Relevance
10/1/2026
First Seen
Sources
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Related Claims
Unverified"Capability illusion" overlaps with the Dunning-Kruger effect, but the version brought about by LLMs is more insidious: users mistake the tool's output for their own understanding.67% similarUnverifiedLLM call chains are long and highly non-deterministic, and a single failure may originate from any one of the following: prompt, tool call, context truncation, or model hallucination.67% similarUnverified由于 LLM 输出的非确定性，传统断点调试几乎无效，基于信号日志的回放调试是业界更具实践价值的替代方案66% similarVerifiedThe fundamental reason prompt injection is difficult to defend against is that LLMs cannot reliably distinguish between data and instructions.66% similarVerifiedLLM outputs are probabilistic, carry hallucination risks, and may misjudge context and invoke tools that should not be invoked.65% similar
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