FLARE is a novel dense supervision paradigm for long-horizon coding agents using a Generative Reward Model. It extracts high-fidelity supervision through an offline diagnostic framework called RADAR and uses this model to optimize the agent across its lifecycle, reducing compute overhead and mitigating policy collapse in sparse environments.