Meta researchers taught an 8B AI model to match Claude Opus 4.5 — without the frontier price tag

The useful part

The agent cannot rely solely on its internal context window for a job spanning hours and depends on the runtime layer, aka the harness. This harness provides execution feedback, like server logs, to help the agent maintain an accurate understanding of dynamic API connections. It also provides state trackers and control-flow mechanisms to manage completed and pending subgoals, ensuring the agent doesn't skip or duplicate data batches.

How it works

• When unexpected errors occur, such as a database rejecting a batch due to strict API rate limits, the harness provides tools and instructions to help the agent recover.
• The main way to tell an agent how and when to use its tools is to have a human developer write a set of rules and instructions telling it what to do step-by-step.
• For example, a developer might instruct the agent to always search the company wiki before writing an email.
• Because the agent is just following a rigid script, it lacks true autonomy.
• It hasn't been trained to independently weigh the costs and benefits of its actions.