The idea is simple: use an existing LLM to estimate the probability of each word appearing in a given sentence. If nearly every word ranks high in the LLM’s predictions (e.g., in the Top-N), the sentence is likely AI-generated. Conversely, if many words are unexpected, it’s more likely human-written.
Store the embedded data in sorted form to remove the need to use hash tables.
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/ downstream-xmlstarlet (push) Successful in 23s
The Harvard Business Review recently documented what it calls “workslop”: AI-generated work that looks polished but requires someone downstream to fix. When that work is a memo, it is annoying. When it is a cryptographic library, it is catastrophic. As AI accelerates the pace of software production, the verification gap does not shrink. It widens. Engineers stop understanding what their systems do. AI outsources not just the writing but the thinking.
2026-02-26 12:00:00