Persistent Hypothesis Tree: The New Approach That Doubles the Performance of AI Coding Agents
A team of data scientists has developed Arbor, a 'persistent hypothesis tree' that enables AI coding agents to remember and refine learnings over long research sessions. In practical tests, this technique doubled performance compared to conventional agents without increasing the budget.



