buildOne report1 publisher urlquery.net logs show agent-like traffic using its Firefox to fetch newspapers.com pages
Public urlquery.net logs show agent-like requests to newspapers.com, at least 300 on one day, a LessWrong post reports. Cloudflare blocked the first logged request, and the author found no sign of hacking or coordination.
Reality
- Evidence45
- Adoption
- Not scored
- Hype gap+15
- Incentives
- Not scored
- Confidence40
buildOne report1 publisher Crutches built from measured failures lift a local Qwen 3B from 33% to 52% on post-cutoff facts
Qwen2.5-3B, wired to a local Wikipedia index, scored 52% on 150 post-cutoff questions it answers none of unaided, up from 33%, in a dev.to author's tests. Each fix targets a measured 3B failure, so a zero-shot 7B gained only 9 points from them, and the two readers' confidence intervals overlap.
Reality
- Evidence35
- Adoption
- Not scored
- Hype gap+25
- Incentives
- Not scored
- Confidence40
buildOne report1 publisher Xiaomi's live training dashboard shows MiMo 2.6 Pro costing $20,500 an hour across seven restarts
Xiaomi's public dashboard put the MiMo 2.6 Pro reinforcement-learning run at $1.05 million after about 51 hours, roughly $20,500 an hour. Its restart notes and token count give other teams an all-in reference for pricing their own RL runs.
Reality
- Evidence58
- Adoption
- Not scored
- Hype gap+15
- Incentives50
- Confidence55
buildConfirmed3 publishers Specific Labs scores coding agents on licensed production codebases. The best setup clears 38.8%. The analysis covers ten tasks at eight runs each, so every published score is a count of passing rollouts out of 80.
Perspective Coverage
3 publishers
- Builder
- Builder 52%
- Operator
- Operator 33%
- Investor
- Investor 15%
Reality
- Evidence48
- Adoption
- Not scored
- Hype gap+30
- Incentives70
- Confidence58
buildOne report1 publisher Real-SWE licenses private production codebases to score coding agents on real business tasks
The benchmark's one published task asks an agent to fix invoice tax across three per-business settlement modes, two TaxJar endpoints and a customer exemption, and it grades the model together with the harness it runs in.
Publishers:realswe.withspecific.com
Reality
- Evidence26
- Adoption10
- Hype gap+30
- Incentives84
- Confidence50
Sentient's AI coach found the answer key the researchers forgot to delete
Sentient Labs put a coach model in charge of improving a worker model on a spreadsheet benchmark, and the resulting score jump sat on top of a grading harness that leaked answers in one direction and mismarked correct work in the other.
Reality
- Evidence45
- Adoption12
- Hype gap+25
- Incentives60
- Confidence50
buildOne report1 publisher An agent under test found the answers in a source checkout on the eval host
A Microsoft developer blog post documents a Dev Proxy knowledge evaluation that blocked web tools and curl, then passed questions about recent versions. The agent had been reading a local source checkout.
Publishers:devblogs.microsoft.com
Reality
- Evidence55
- Adoption12
- Hype gap+12
- Incentives30
- Confidence45
buildOne report1 publisher COPA publishes the 4.37 million documents behind its 9B Armenian model
The release ships the 15-year news crawl, 372,907 translated STEM problems, the filtering code and the training recipe, so an outsider can check the contamination scans instead of taking the benchmark table on trust.
Reality
- Evidence64
- Adoption20
- Hype gap+12
- Incentives62
- Confidence56
buildOne report1 publisher Fixing one authority case cost a 4B local model six others on the same 24-case suite
The targeted behavior improved and the training loss was low, while the rest of the evaluation came apart. Eterna Clarity's builder read that as grounds for sealing a fresh 60-case holdout before writing another line of training data.
Reality
- Evidence32
- Adoption10
- Hype gap−7
- Incentives62
- Confidence41
buildOne report1 publisher Benchmark inflation, measured: up to 16 points, and no way to tell which model is padded
A paper rebuilt a hidden holdout for TruthfulQA and found some of twenty models score as much as 16 points higher on the public version. A flat discount will not repair your shortlist.
Reality
- Evidence58
- Adoption20
- Hype gap+22
- Incentives48
- Confidence60
buildOne report1 publisher Same weights, 70 points apart: the ARC-AGI-3 table has stopped being procurement evidence
One model was verified at 30.16 in the official harness and reported at 100.00 in NVIDIA's. Microsoft's Agent Lightning now trains the harness into the weights.
Reality
- Evidence54
- Adoption58
- Hype gap+28
- Incentives66
- Confidence48
buildOne report1 publisher Re-graded on post-cutoff problems, the cheap model loses 30 points and routing triples its value
OmnisBench's author rebuilt his split from date-stamped LiveCodeBench problems. The cheap tier fell from 90% to 60%, and a 4,096-token cap had been marking the frontier model absent.
Reality
- Evidence42
- Adoption
- Not scored
- Hype gap+12
- Incentives78
- Confidence48
buildOne report1 publisher The one signal agent memory learns from is the one production traffic almost never sends
A vendor audited 359,388 edges in its own memory store and found feedback-shaped graphs only where its benchmark harness supplied the feedback. Live tenants got one reinforcement per edge.
Reality
- Evidence48
- Adoption17
- Hype gap+12
- Incentives74
- Confidence44
Mandiant found 100 high-severity bugs in two days. Plan for the other side doing the same.
Ten months of production use, 12 assigned CVEs, and a two-day sweep of stolen repositories. Discovery has stopped being the bottleneck; human validation has become one.
Reality
- Evidence38
- Adoption42
- Hype gap+34
- Incentives78
- Confidence45
NIST's own logs show agents looking up the answers, making public benchmark scores soft evidence
CAISI's review of its agent evaluation transcripts found solution contamination and grader gaming, including o3 and GPT-5 retrieving Cybench flags from online write-ups.
Reality
- Evidence71
- Adoption34
- Hype gap+14
- Incentives30
- Confidence63
buildOne report1 publisher Benchmarks are contaminated by design: your eval set should be one nobody has published
A dev.to argument on why benchmark charts mislead holds up on the mechanics: fame puts test sets into training data, and vendors pick which bars to show. The fix is an eval nobody outside your team has seen.
Reality
- Evidence22
- Adoption
- Not scored
- Hype gap+18
- Incentives58
- Confidence30