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Research2026-06-14 · source-backed
Studdiford and Lupyan tested human participants and 25 LLMs on common-sense causal reasoning and found shared, predictable error patterns triggered by irrelevant prompt details (arXiv). They localized the attention heads driving it. The uncomfortable implication: the gap between human and machine everyday reasoning may be narrower than we assume, because both inherit the same brittleness. If you've watched an agent get derailed by an irrelevant detail in a ticket, this is the mechanism. We do it too.
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Simon Willison released LLM / Shared entity: LLM / Shared topic / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; overlapping topics (agent, assume, pattern).
Simon Willison released LLM / Shared entities / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover Human, LLMs; earlier Human coverage from 2026-04-13.
Simon Willison released LLM / Shared entity: LLM / Shared topic / What happened next
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; overlapping topics (agent, reasoning).
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; overlapping topics (agent, human).
LLM uses OpenAI / Shared entity: LLM / What happened next / Tension
Linked by a graph relationship (LLM uses OpenAI); both cover LLM; picks up the LLM thread on 2026-07-27.
Simon Willison released LLM / Shared entity: Human / Shared topic / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover Human; overlapping topics (between, human).
Simon Willison released LLM / Shared entity: LLM / What happened next / Tension
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-08-16.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-06-19.