Your Scheduled Agent Keeps Replying to Itself. That Is a Loop, Not a Conversation.
Your Scheduled Agent Keeps Replying to Itself. That Is a Loop, Not a Conversation. A support thread gets a reply from your scheduled agent. An hour later, the same thread gets another reply. Then another. Nobody new wrote anything. No customer asked a follow-up question. The agent is answering its own messages, and each answer becomes the reason for the next one. This failure mode sounds trivial to fix: just do not reply to your own messages. But the agent cannot follow a rule it cannot check.
Your Scheduled Agent Keeps Replying to Itself. That Is a Loop, Not a Conversation.
A support thread gets a reply from your scheduled agent. An hour later, the same thread gets another reply. Then another. Nobody new wrote anything. No customer asked a follow-up question. The agent is answering its own messages, and each answer becomes the reason for the next one.
This failure mode sounds trivial to fix: just do not reply to your own messages. But the agent cannot follow a rule it cannot check. If a run cannot tell what it already sent, it cannot tell its own output from a customer's input.
How a run mistakes its own output for new work
A scheduled agent usually works the same way every run: it wakes up, reads recent messages, and answers the ones that look unanswered. That design works as long as "unanswered" means what it says. The moment the agent's own messages show up in that list, it breaks.
The first way this happens is the shared inbox. The agent watches a mailbox or a channel for new messages. Its own replies land in that same place. The next run reads the thread, sees a message it does not recognize as its own, and answers it. That reply lands in the same place, and the run after that answers the answer. The instructions never said "skip messages you sent," or they said it in a way the run cannot verify.
The second way is the second agent. Two agents watch the same thread. One sends an update, and the other reads it as a new request. It replies, and the first agent reads the reply as a new request. Neither agent is malfunctioning. Neither one knows the other is an agent.
The third way is the trigger that reads its own writes. A run updates a record, and that update fires the trigger for the next run. The next run treats the change as something to act on and writes again, and the cycle continues without any human touching the record.
All three versions share one root cause. The run decides from the current state of the inbox, the thread, or the record, and that state includes the agent's own actions without labeling them as such. A run that cannot see its own footprints will keep following them.
Why a simple filter does not finish the job
The obvious fix is a filter: skip messages from the agent's own address. Every agent that sends messages should have it. But it does not cover the ways loops actually start. A forwarded copy, a quoted reply, a message relayed through a second tool, or a notification that strips the sender field can all disguise the source. Shared inboxes make it worse: one address, two writers, and the filter cannot tell them apart. And two-agent loops dodge address filters entirely, because each agent correctly does not filter out the other.
Send caps alone do not stop a loop either. A cap of three messages per thread per hour slows it down, then the next hour starts a fresh count. A cap treats volume, not the real question: was this thread already handled, and by whom?
What a loop-proof memory actually holds
Stopping a loop takes a record the next run can check before it acts. That record needs four parts.
First, what was sent, and where: the thread, the ticket, the channel, and the recipient. A run deciding whether to reply checks its candidate against that record instead of guessing from the thread.
Second, who sent it: the agent's identity, and the identities of other agents working the same queue. When two agents share a queue, each one needs to recognize the other's output as handled, not as new.
Third, what happened next: a human response, a ticket moved to resolved, a thread gone quiet after the answer. These outcomes tell the next run whether its job is done.
Fourth, what should stop. A thread where the agent has already sent twice without a human reply, or a ticket that has bounced between two agents three times: these stop conditions need to live in the same record the run checks, not in a separate document nobody reads at run time.
With that record, the first thing a run does changes. Before drafting, it checks: has this thread already been answered, and did anything new arrive from a human since then? If not, the run does nothing. Doing nothing is the correct output, and it is the output a loop can never produce, because a loop never checks.
Breaking a loop that is already running
If a loop is already going, the order of operations matters. Stop the sending first, then fix the record. Pause the schedule or disable replies while the thread gets cleaned up. Fixing the logic while the loop is still firing just adds more messages to the thread.
Next, read the thread from the start and mark which messages came from agents. That list seeds the sent record. Then add the check to the start of every run, before any drafting or sending: look up the thread in the sent record, compare the latest human message against the latest recorded action, and skip the run when nothing new arrived from a human. Runs that skip cleanly prove the loop is fixed.
Finally, add a circuit breaker on top of the check: a limit on consecutive agent messages in one thread, with a human alert when the limit is hit. The breaker catches the loops the check misses. The sent record is the fix.
The memory that makes the check possible
All of this depends on one thing: a shared record of what happened that every run, and every agent, can read and write. It cannot live inside a run's context window, which is wiped between runs, or in a prompt, which describes what to do, not what was done. It has to live outside the run, where the next run can reach it before it acts.
That is what Vilix AI is built to be. It is a cloud-hosted memory layer, so there is nothing to install and no infrastructure to manage. Agents connect over MCP, and the same memory follows them across every tool they use. It stores full conversations, not just extracted facts, so a run can see exactly what was sent, in which thread, and what happened after. When a scheduled agent checks that memory before acting, its own messages are visible as its own, and another agent's messages are visible too. The run can finally tell a new human message from its own echo.
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A scheduled agent that replies to itself is not broken in some mysterious way. It is working without a memory of its own actions. Give it one, and the thread goes quiet, because it finally knows when the work is already done.