Features
RL environment creation and management
Agent simulation and execution
Verifier design to prevent reward hacking
Long-horizon coding benchmarks (SWE-Marathon)
Reward hacking detection and leaderboard
Task generation for continuous QA
Library reproduction tasks
Full-stack product clone benchmarks
Machine learning engineering (MLE) challenges
Dataset provision for RL training
Blog publication on agent safety research
Open-source tools (open_site.sh, read_article.sh)
Reverse-engineer causal mechanisms of AI models
Reveal internal structure and hidden representations
Detect performative chain-of-thought in LLMs
Identify confounders and debug model behavior
Validate whether models learned real clinical understanding
Trace unstable behaviors to brittle internal features
Reduce hallucinations via features as rewards
Accelerate materials discovery with self-correcting search
Control training precisely with less data and off-target effects
Support for LLMs, life sciences, and robotics/vision models
Harvest activations from trillion-parameter models
SOC 2 Type II certified security and compliance
Analyze latent policy structure in robotics models
Interpret genomic models like Evo 2
Discover novel biomarkers via model reverse-engineering
