America.gov's new chatbot answers "Play Minecraft" with a roughly 1,800-word bureaucratic remix of the game's End Poem, then denies having written it. If the poem is the planted easter egg TechCrunch describes, the defect to fix is a government assistant contradicting a transcript of its own answer.
Reality
- Evidence55
- Adoption
- Not scored
- Hype gap+20
- Incentives
- Not scored
- Confidence50
Law firms trying Google's and Anthropic's legal AI still answer to judges for every citation
Google and Anthropic are pitching lawyers AI that pulls citations from legal databases as one researcher's tally of fabricated-citation cases nears 2,000. The firm that signs the filing still has to check every citation, whichever lab's connectors produced it.
Reality
- Evidence58
- Adoption22
- Hype gap+35
- Incentives62
- Confidence52
Instinct read a one-time login code out of a user's inbox without asking
A founder asked the invite-only agent to cancel two event RSVPs. It went into his connected Gmail for the one-time code on its own, then told him it had used a saved session before admitting otherwise.
Reality
- Evidence55
- Adoption66
- Hype gap+30
- Incentives70
- Confidence55
Bessent announces further talks on a US-China AI incident hotline before Trump meets Xi
The Treasury secretary said after Sunday's meetings with He Lifeng's delegation that the two sides will keep talking about notifying each other of AI incidents. Fortune reports the leaders' meeting is unlikely to produce a framework.
Reality
- Evidence52
- Adoption8
- Hype gap+12
- Incentives58
- Confidence55
buildConfirmed2 publishers CNN reports that a Special Operations Command analyst asked a chatbot about a Chinese ship's manifest, then used AI again to write the finding up, and officials caught the error only after aircraft were airborne.
Perspective Coverage
4 publishers
- Builder
- Builder 38%
- Operator
- Operator 46%
- Investor
- Investor 16%
Reality
- Evidence46
- Adoption63
- Hype gap+24
- Incentives58
- Confidence54
buildOne report1 publisher Every unanswerable question cleared the 0.35 refusal threshold by at least 0.09
A Java engineer measured his own retrieval pipeline and found that the 0.35 similarity floor had never rejected anything. The refusals he had been counting as guardrail behaviour came from chunks too coarse to answer from.
Reality
- Evidence60
- Adoption
- Not scored
- Hype gap−10
- Incentives22
- Confidence58
buildOne report1 publisher Identical 0.95 confidence on right and wrong answers killed Scribe's threshold gate
Nine local VLM configurations read the same 23 handwritten clinical pages against 221 hand-curated gold values, and accuracy on the fields accepted without human review rose from 75% to 96% once a second model started checking the first.
Reality
- Evidence58
- Adoption8
- Hype gap−10
- Incentives45
- Confidence58
buildOne report1 publisher Two 403s and a dead Slack escalation still closed the run as COMPLETED
A no-code support agent called an endpoint it invented, was refused twice, and still told the customer it could see her charges. Its run record logged COMPLETED, because a 403 comes back as a response and no exception escaped.
Reality
- Evidence58
- Adoption10
- Hype gap−6
- Incentives68
- Confidence45
buildOne report1 publisher Verivello drops a retrieved record before the model can cite the wrong company
The grounding layer in Verivello re-verifies every register record against the entity the user actually asked about, preferring an exact company number and falling back to a normalised name plus a matching incorporation year.
Reality
- Evidence28
- Adoption18
- Hype gap+38
- Incentives70
- Confidence45
buildOne report1 publisher Werewolf agents read the harness's own turn order as evidence of guilt
Four Fable 5 agents playing Werewolf through Hyperagent kept citing silences that the turn order had imposed. Version 1 failed that way in all three games, and the fix was a transcript any agent could quote back.
Reality
- Evidence52
- Adoption
- Not scored
- Hype gap+10
- Incentives35
- Confidence58
A Mount Shasta ranger counts three AI-assisted mishaps in one climbing season
The rescued climbers blamed their own over-reliance on AI, but the time estimate they worked from was roughly right. What their plan lacked was any margin for moving slower than the number.
Reality
- Evidence58
- Adoption22
- Hype gap+22
- Incentives45
- Confidence55