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BLOG-007 · Version 1.0

Evidence Engineering for AI

Shift attention from fluent text to claims, sources, counter-evidence and uncertainty.

AI can produce persuasive language without a reliable evidence chain. Evidence engineering decomposes an output into claims and asks what supports each claim, what could contradict it and how uncertainty should be represented.

This approach is especially important when AI output will be published, used in policy, relied upon in a decision or presented as an expert conclusion.

Revision history

Version 1.0 — 26 July 2026: Initial publication.