Do Not Let Confidence Replace Verification
Verify AI output before using it in customer, financial, or policy-sensitive work.
The answer is formatted perfectly: bullets, caveats, a confident conclusion. That polish can make you skip the one step that matters: checking. > The more consequential the output, the stronger the verification must be. Fluency is not truth Large language models are optimized to produce plausible language, not guaranteed truth. OWASP lists overreliance as a major LLM application risk because uncritically accepting output can compromise decisions, create security issues, and produce legal exposure. Match review to consequence Low-stakes brainstorming may only need common-sense review. Customer-facing claims need source checks. Financial numbers need reconciliation to systems of record. Employment, legal, safety,…
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