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Don't Be a Meat Proxy
When engineers paste AI output directly into conversations or code reviews without understanding it, they create noise rather than signal—the recipient could query the AI themselves with better context. The real value an engineer can add comes from reading, validating, and synthesizing AI output into their own words, which demonstrates comprehension and filters out plausible-sounding nonsense.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
Relaying AI responses verbatim in Slack, code reviews, or group chats forces the recipient to parse verbose, jargon-dense output that they could have generated themselves with more control over context.
The author identifies code review as a particularly affected area, where an implementer can ship code by shuttling ticket descriptions and reviewer feedback through an AI tool without ever understanding the result, effectively making the reviewers the actual implementers.
The recommended practice is to prompt AI, then read, understand, and validate the output before responding in your own words as proof you've actually processed the information.
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