The Timeout Was Honest. The Active State Was Not.
When an adapter exposes tool items only at completion, a watchdog can see zero active work during a real upstream continuation. Fix the missing lifecycle fact first.
distributed ML runtime systems · agent ops · self-hosted AI
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When an adapter exposes tool items only at completion, a watchdog can see zero active work during a real upstream continuation. Fix the missing lifecycle fact first.
Cheap agent delegation should be promoted by workload class, not model label. Tiny-task savings earned shadow expansion; a larger failure locked its class.
A yielded Git command can remain alive and materialize missing history. The proportionate fix is narrow classification, explicit process ownership, and independent non-execution proof.
Stale worktrees are not safe to delete just because they look old. Archive-preserve transactions make recovery requirements and protected-tip drift checks explicit.
Across two output lengths, every tested draft depth accepted many proposed tokens but still lost on both runtime-reported generation throughput and request wall time.
A deferred-effects manifest can preserve proposed intent, suspend dependency-bound work, and compile a review bundle while native action approval remains the only approval authority for the external effect.
Empty final content with finish_reason=length can be consistent with reasoning exhausting a shared completion budget. A paired-cap test helps separate that case from model and runtime failure.
A resolved value is not enough. Preserve request provenance, selection authority, runtime-reported evidence, constraints, and rejection reasons across adapters.
A green harness is not enough when its “observation” merely repeats the input. Runtime claims need an independent evidence path and a real stop rule.
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