Your AI Can't Tell You Why It Did That
Ask an AI why it did something and you get a fluent, confident explanation — generated by the same machinery that made the mistake. Why AI self-explanation is theater, not insight.
Read →Insights
Field notes on how AI reasoning fails in production, and what it costs the decisions built on top of it.
Ask an AI why it did something and you get a fluent, confident explanation — generated by the same machinery that made the mistake. Why AI self-explanation is theater, not insight.
Read →An AI confidently described my company's methodology in specific detail. I never wrote a word of it. A first-person look at manufactured authority, the AI failure that reads as expertise.
Read →A federal AI order vets frontier models for danger before release. Whether the AI in your decisions reasons soundly is another question, and where your risk lives.
Read →Red-teaming and reliability testing sound alike and measure opposite things. One checks whether an attacker can break your AI. The other checks whether it holds up when people simply use it.
Read →Your AI sounds confident whether it is right or wrong. Here is how to tell whether its reasoning actually holds up before your business depends on it.
Read →When AI output sounds authoritative but the reasoning underneath does not support the conclusion, the problem is not hallucination. It is a behavioral failure pattern called manufactured authority.
Read →When an AI workflow that used to produce reliable output starts giving inconsistent or degraded results, the problem is usually not the model. It is the decision path around it.
Read →If you have a nagging sense that your AI output is not quite right but cannot explain why, you are probably detecting a behavioral failure pattern that surface-level checks will not catch.
Read →Manufactured authority is the most operationally dangerous AI behavioral failure because it passes every surface-level check. Here is how it works and why benchmarks miss it.
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