Study reveals 'latent programming horizon' allowing coding agents to predict future outcomes
tokenbender · x · 2026-08-16
Research shows that the residual streams of language models within coding agents linearly encode properties of the evolving program. Logistic regression probes on hidden states can decode whether code parses, passes test suites, reduces failing tests, or introduces regressions, achieving up to 0.83 AUC for correctness. More strikingly, these representations run ahead of the agent's own edits: probes trained to predict future outcomes can perform above chance up to roughly 25 steps in advance, a phenomenon termed the agent's 'latent programming horizon'.
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