🛠 Bean: A Tool for Reliable AI Agent Performance
Bean has been introduced—a tool designed to ensure the reliability of AI agents (such as Claude Code and Codex) through a recursive convergence loop mechanism. Instead of relying on an agent's claim that a task is complete, Bean forces it to go through stages of research, recording proofs in a typed ledger, and compiling results.
🌍 Bean solves the problem of "silent false completion," where an agent provides an incorrect result. This represents a transition to a "work until convergence is proven" model, which is critical for autonomous systems.
👤 This is a new level of control: it is now possible to implement a programmatic mechanism that prevents an agent from "giving up" until it has confirmed its conclusions with facts or tests.
Source 1: https://github.com/grainulation/bean/