Equation 20 · Why Coding Agents Fail: Long-Horizon Reliability in OpenAI Codex
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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.
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Symbol d_i
is one of the signed contributions combined to compute the quantity on the left.
Symbol c_i
is one of the signed contributions combined to compute the quantity on the left.
Symbol r_i
the probability repair succeeds without creating another material defect.
=
The expressions on both sides represent the same quantity under the stated assumptions.
See an illustrated explanation →subscript
The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.
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What the article says around this equation
An agent can recover only if the system generates a discriminating observation. Let stage i have direct success probability . If failure occurs, let be the probability it is detected, the probability the cause is diagnosed correctly, and the probability repair succeeds without creating another material defect. A simplified effective stage reliability is . The formula is intentionally conservative and incomplete. Multiple retries, repair costs, correlated defects, and false alarms require richer models. Its value is conceptual: “the agent can iterate” improves reliability only through detection, diagnosis, and repair.
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