Competitive training between two models can implicitly grade reasoning quality without process labels or reward models—each model becomes the other's grader, forcing genuine problem-solving improvement rather than just longer outputs.
Agon trains two AI models to compete against each other on reasoning tasks. One model drafts a solution while the other reads it and solves the problem independently—whoever gets the right answer wins. This forces both models to develop better reasoning skills without needing labeled examples of good thinking.