Agent Reliability Means Completion
Real tasks contain chains of fragile steps. Reliable agents combine verification, retry, recovery, escalation, and explicit terminal states to turn model quality into completed work.
An agent that succeeds on 95 percent of individual steps has only about a 36 percent chance of completing a twenty-step task without failure. That arithmetic explains why single-turn demonstrations look excellent while real jobs break on authentication, formatting, networks, or interface changes.
Computer-use systems and agent SDKs add tools, handoffs, and tracing, but also create new failure surfaces: timeouts, denied permissions, changed schemas, duplicate side effects, and conflicts with external state. A correct model decision can still produce an incorrect business result.
The evaluation unit must be end-to-end completion with explicit acceptance conditions. Customers buy completion, not average correctness. A file should exist and open, a draft order should be saved without payment, or a code change should pass tests within scope.
Reliable runtimes use checkpoints. Critical actions save inputs, outputs, and external state; retryable operations are idempotent; irreversible steps receive previews or confirmation. Temporary faults, capability gaps, and ambiguous goals require different recovery paths rather than one infinite loop.
Verification is the second control plane: tests for code, constraints for data, state checks for interfaces, and sources or independent review for open text. Unverified completion is only the model's self-report. A failed check should trigger repair, another path, or an honest handoff.
The interface should disclose failure precisely: where work stopped, what was preserved, and what input is required. Low-risk faults can recover automatically; high-impact or repeated failures should stop early enough to prevent compounding side effects and cost.
Teams need a failure taxonomy and metrics for first-pass completion, recovered completion, intervention time, duplicate effects, and unrecoverable states. Every production incident should become a replayable evaluation case so reliability improves through evidence.
The best agent is not one that never errs. Its errors are detectable, contained, and recoverable, and the user receives a trustworthy terminal state. Reliability is organizing uncertain steps into a certain delivery. That is the threshold between an impressive demo and infrastructure.
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