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Skills2026-06-28 · source-backed
Isolate the agent from the evaluator, never pass reference answers into the agent's context, never eval() untrusted model output, sanitize LLM-judge inputs against injection, and adversarially test the evaluator before trusting its scores (AI Agent Insights). A leaking or injectable evaluator silently inflates your pass rate and hides real failures.
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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: Audit / Shared topic / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover Audit; overlapping topics (agent, audit).
Simon Willison released LLM / Shared entity: LLM / Earlier coverage / Tension
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; earlier LLM coverage from 2026-06-19.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; earlier LLM coverage from 2026-06-18.
LLM uses OpenAI / Shared entity: Audit / What happened next
Linked by a graph relationship (LLM uses OpenAI); both cover Audit; picks up the Audit thread on 2026-08-08.
LLM uses OpenAI / Shared entity: LLM / What happened next
Linked by a graph relationship (LLM uses OpenAI); both cover LLM; picks up the LLM thread on 2026-07-31.
LLM uses OpenAI / Shared entity: LLM / Earlier coverage
Linked by a graph relationship (LLM uses OpenAI); both cover LLM; earlier LLM coverage from 2026-06-19.
Simon Willison released LLM / Shared entity: LLM / What happened next
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-08-12.