01Environments
A neutral record, measured the same for every lab.
An environment is a task with a checkable outcome, taken from real work. A model is graded step by step against ground truth as it goes. Run the same task and you get the same number, whichever lab is running it.
02Method
One process, from a capability to a graded environment. The same five steps every time.
01Capability
Perceive
Map a capability and its failure modes until the reward is well defined.
02Rubric
Represent
Formalize it into a task distribution with a verifiable rubric.
03No contamination
Build
Stand up environments that separate cleanly from eval and resist contamination.
04Distribution
Scale
Mass-produce variants across the distribution. Early environments become training data.
05pass@k
Choose
Score pass@k by model. Point the next environment at what they fail.
03Domains
Where the method is pointed. In priority order, by stakes.
01Priority
Safety
Alignment and oversight. The first call on everything.
02High-stakes
Defense
High-stakes capability and red-team work.
03Research
Science
Bio, pharma, research automation.
04Live
Commerce
Agentic work on real company operations. Live today.
04Why Idler
Grounded, broad, frontier.
AReal data
Grounded
Environments from real production data, not invented. Less reward hacking, better transfer.
BCoverage
Broad
Coverage across coding, tool use, long-horizon, error recovery.
CFrontier
Frontier
Built for the models clearing the hardest evals, on the work they fail next.
05Contact
Name the capability your models miss. We build the environment, graded against ground truth.