Own the Loop: A Guide to Agent Harnesses

The most outstanding coding agents recently have taken the form of Model-native pairs optimized for specific models. However, this tight coupling results in locking users into a particular vendor's pricing policies and service ecosystem.

Models are now increasingly becoming a commodity, and an agent's success or failure is determined not by the model but by the Harness. Here, the harness refers to the Loop in which the model repeats the process of editing files, running tests, and fixing errors.

When choosing a harness, the following three criteria should be considered:

• Capability: the degree of coupling between the model and harness, and the level of the tool/integration ecosystem
• Freedom: ease of swapping models and independence of the workflow
• Workflow: whether it is optimized for a specific task or user

Rather than making the user experience seamless, vendors try to lock users into their own platform through features that span browsers and desktop apps. Therefore, to build a sustainable AI workflow, you should choose a highly portable harness that lets you freely swap models and ensures that the rules and settings you've built are not tied to a specific platform.