Nathaniel Whittemore
speaker
51,978 appearances
203 recordings
3 series
first heard Oct 2025
last heard 2d ago
Nathaniel Whittemore’s voice in public audio — every appearance, attributed to the second.
Trend
recordings per month · last 12 monthsRecordings per month over the last 12 months — 203 in all, peaking in Jun 2026 with 31.
Appearances
Does it address the export problem?
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Does it promise something unsupported by the information provided?
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And part of what people are excited about opening up with this new approach is that cheap judgment makes frequent checking more practical.
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If a check adds a noticeable delay or expense, a team may run it only on selected cases or at the end of a task.
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If it becomes sufficiently fast and inexpensive, it could run on every incoming request after each draft revision across many candidate documents before an agent takes a consequential step.
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Back in Mike Taylor's article from Every, he gave Jeff the text from all 27 of his articles, alongside 10 deliberately AI-styled counterpoints, then asked the same 21 questions concurrently across all articles to check for AI tells.
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Basically, the check that he was doing with Jev was: does this essay do specific things that indicate to people that it is AI composed?
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Things like, does the text repeat an idea without adding evidence?
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Does it
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Force a symmetrical both sides argument, does it overexplain a straightforward point?
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In less than 0.7 seconds, Mike said, Jeff quote unquote read all 37 documents and answered all 21 questions for each, returning 777 judgments for an estimated quarter of a cent.
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As he points out, that's fast and cheap enough to AI check everything everyone at your company has ever written and get the results back in an instant.
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A comparison that Mike makes.
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Is a code linter for knowledge work.
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He writes, In software development, a code linter is a tool that analyzes your work and almost instantly flags syntax errors, catches bugs, spots bad patterns, and enforces stylistic consistency.
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TypeSafe's model is so fast at turning fuzzy tasks into clear structured answers that it could act as a kind of code linter for knowledge work.
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Give Codex or Claude access to JEV and a list of questions, and it can quickly check its own work for problems you've told it to avoid.
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Peringrat says, Most software is ultimately a giant tree of if this do that, if this root here, if this escalate, if this reject, if this, ask a human.
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Jev is basically asking, what if those if statements could understand messy human context?
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That's a much more interesting framing than another AI model.
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Showing 2721–2740 of 51,978 · page 137 of 2599
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