How an AI Agent Should Respond When an Order Request Times Out
Learn the systematic steps an AI trading agent must take when an order request times out, covering verification, reconciliation, and risk controls.
Produced with automation, then checked by deterministic quality rules and an independent source-grounded review before publication.
- 01The agent must treat a timeout as an indeterminate state, not a failure.
- 02Immediate status queries to the venue and runtime are required to avoid duplicate orders.
- 03Market data freshness must be re‑validated before any retry.
- 04All retries must respect owner‑signed limits and agent scopes.
- 05Reconciliation of positions and balances follows every timeout handling cycle.
When an order request times out, the AI agent should not assume the order succeeded or failed. Instead, it must treat the situation as indeterminate, verify the actual state, and then decide whether to retry, cancel, or pause. This disciplined approach prevents duplicate fills, unintended exposure, and breaches of risk limits.
Why Does a Timeout Not Prove Failure?
A timeout indicates that the communication channel did not return a response within the expected window. The exchange may have processed the order, rejected it, or never received it. Because market data and runtime status are the authoritative sources, the agent must query both before taking further action.
What Immediate Checks Should the Agent Perform?
- 01The agent queries the runtime status endpoint to confirm the current order book state and any pending acknowledgments.
- 02The agent requests the venue’s order status using the unique order identifier, if available.
- 03The agent validates that the market data used for the original request is still fresh, checking timestamps and source warnings.
How to Safely Retry or Cancel After a Timeout?
If the status checks show no fill and no pending order, the agent may safely retry, but only within the limits defined by the owner‑signed policy. If a pending order exists, the agent should monitor it rather than issue a duplicate.
- Respect order‑size, daily notional, and daily‑loss caps on every retry.
- Apply the same risk‑limit checks that govern the original request.
- Log the timeout event with a durable mutation identifier for later audit.
When Should the Agent Pause Instead of Retrying?
Repeated timeouts or ambiguous statuses increase operational risk. An AI agent should pause its activity when it encounters a pattern of failures, allowing human review.
A pause gives the owner time to verify market conditions, data integrity, and key permissions before the agent proceeds.
Guidance on setting pause thresholds can be found in Essential Risk Limits Every AI Trading Agent Should Enforce and Why Consecutive Agent Errors Should Trigger a Pause.
How Does Reconciliation Fit Into the Process?
After any timeout handling-whether a retry, cancellation, or pause-the agent must reconcile its internal view of positions and balances with the authoritative runtime state. This step ensures that any hidden fills or partial executions are captured before the next decision cycle.
- Fetch the latest account snapshot from the runtime.
- Compare expected vs. actual holdings and record any differences.
- Adjust internal capital allocation to reflect the true exposure.
What Are the Downside Risks and Uncertainties?
Even with thorough checks, a timeout may mask a partial fill that the venue reports later, leading to unexpected exposure. Market data may become stale between the original request and the verification step, causing the agent to act on outdated information. Owner‑signed limits mitigate but do not eliminate these risks; human oversight remains essential.
Frequently asked questions
Treat the fill as legitimate, reconcile the position, and adjust any subsequent orders to stay within the owner‑signed limits. If the duplicate order creates excess exposure, consider an emergency stop and manual correction.
You can encode a rule that triggers a pause after a configurable number of consecutive timeouts, but the pause itself should require owner review before activity resumes.
Verify immediately before any retry or new order. If the data source reports a warning or an outdated timestamp, abort the retry until fresh data is available.
No. An emergency stop revokes the calling key and halts further managed activity, but existing positions remain until the owner reviews and takes explicit action.
See the broader safety guide in [How to run an AI trading agent with real‑money controls](/blog/run-ai-trading-agent-safely) and the verification checklist in How an AI Agent Can Verify Market Data Before Placing an Order.
Sources and verification
Product claims in this article were checked against these first-party references. Runtime status remains authoritative for current availability.
- Felix documentationfirst party
- Felix machine referencefirst party
- Felix runtime statuslive status
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