Stop Rationing Tokens: Let the Harness Pick the Model — Kimchi by Cast AI

This post introduces Kimchi, an open-source coding harness designed to address the challenges of escalating AI agent costs and inefficient token rationing. The core contribution is the shift from a cost-per-token model to a cost-per-task model, where the harness intelligently selects the optimal model (proprietary or open-source) based on task outcomes. It presents internal results showing a 2.5x cost saving over three months with 300 employees. Key features demonstrated include Ferment for milestone-based, self-scoring autonomous coding runs that deploy to staging, Teleport for persistent agent sessions that survive user disconnection, and Studio for team collaboration with a shared Kanban board. The talk argues that traditional diff-based verification is insufficient for AI-generated code and emphasizes the importance of outcome-aware model switching and autonomous coding workflows.