Will Brown

Multi-turn open-web research QA environment where the model uses a Serper search tool to answer hard, hop-heavy questions of the BrowseComp / SimpleQA style.

Verifiers env that runs the mini-swe-agent harness inside Prime Sandboxes against real GitHub issues; reward is test-suite pass.

Terminal-Bench tasks wrapped as a Verifiers RL environment - model drives a tmux shell to complete realistic end-to-end terminal jobs (compiling, sysadmin, data science).

Multi-turn math problem-solving environment where the model proposes Python code in a sandbox to compute and verify numerical answers.

Prime Intellect's library for defining RL environments - a task dataset, a tool/sandbox harness, and a reward rubric - usable across training, eval, and synthetic-data workflows.