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When ReplicatedShardActor applied a remote delta, it first merged the delta into replica_state and then updated the executor from the incoming delta payload. That meant a stale delta could lose the merge in replica_state but still overwrite the executor, so subsequent reads returned the wrong value. Fix this by reloading the merged value from replica_state after apply_remote_delta and projecting that merged value into the executor. This preserves the existing CRDT and LWW merge semantics, keeps read behavior aligned with replicated state, and is safe because it only changes which already-computed value is mirrored into the executor; it does not change message ordering, conflict resolution, or local write generation.
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This is an AI-generated change audited by me (a human). The bug causes a replica to permanently fall out of sync and not converge. I found this while playing with this code after reading this fascinating blog post: https://www.datadoghq.com/blog/ai/harness-first-agents/
AI bug description below:
When ReplicatedShardActor applied a remote delta, it first merged the delta into replica_state and then updated the executor from the incoming delta payload. That meant a stale delta could lose the merge in replica_state but still overwrite the executor, so subsequent reads returned the wrong value.
Fix this by reloading the merged value from replica_state after apply_remote_delta and projecting that merged value into the executor. This preserves the existing CRDT and LWW merge semantics, keeps read behavior aligned with replicated state, and is safe because it only changes which already-computed value is mirrored into the executor; it does not change message ordering, conflict resolution, or local write generation.