AI trading agent monitoring is the difference between one bad fill and one silent system failure.
Most operators know they need alerts. Fewer define what the alerts should mean, who acts on them, how fast a live account must be paused, and what evidence proves the system is actually flat, protected, and reconciled again. Monitoring is not dashboard art. It is the owner control plane after the agent goes live.
Short answer: monitor heartbeats, market-data freshness, order acknowledgements, stop status, exposure drift, and reconciliation mismatches; then map each alert to a forced pause, cancel, flatten, revoke, or recovery workflow that the owner can execute outside the model runtime.
Laplace angle: this page sits after risk controls, after wallet and API-key design, and after shadow-mode evaluation. Once the system trades real capital, the next moat is whether the owner can see failure early enough to keep it small.
The six alerts that matter first
Heartbeat loss
If the strategy, signer, or venue adapter stops reporting, the system should assume supervision is degraded before it assumes trading is safe.
Stale data
If the market feed, position state, or funding data is old, the agent may still sound coherent while acting on expired context.
Order ambiguity
"Submitted" is not enough. Alert when orders are unacknowledged, rejected, partially filled without follow-up, or missing a final state.
Stop or hedge gap
A live position without the intended stop, reduce-only order, or hedge protection is an incident, not a minor warning.
Exposure drift
If intended size and actual size diverge, the system is trading a different risk book than the owner approved.
Reconciliation mismatch
If balances, fills, or positions do not match internal state, freeze trust in the dashboard until the account is reconciled independently.
Monitoring stack by layer
| Layer | What to watch | Why it matters | Owner action |
|---|---|---|---|
| Process health | Strategy heartbeat, signer service, gateway latency, queue backlog, cron or worker completion | Silent process death creates phantom supervision | Pause new orders and confirm the last known account state |
| Data quality | Feed freshness, missing candles, funding lag, account-sync lag, timestamp skew | Good prompts on stale inputs still create bad trades | Block new entries until fresh data and account state agree |
| Venue interaction | Rejections, unacknowledged orders, cancel failures, rate-limit pressure, duplicate client ids | Intent can diverge from accepted venue state quickly | Cancel pending risk and reconcile directly with the venue |
| Protection status | Stop-loss presence, reduce-only coverage, liquidation buffer, margin stress, hedge parity | The account can be live while the protection layer is broken | Flatten or reduce until protection is re-established |
| Economic state | Position delta, realized and unrealized P&L, fee spikes, funding drag, cross-strategy heat | Lets the owner catch risk drift before it compounds | Throttle size, disable the strategy, or move capital |
| Recovery state | Was the alert acknowledged, paused, resolved, rotated, or escalated? | Monitoring without workflow becomes alert accumulation | Run the documented incident path and log the outcome |
Severity ladder for live AI trading incidents
| Severity | Example | Required response | Resume condition |
|---|---|---|---|
| SEV-1: hidden live risk | Position exists but stop is missing, flat status is uncertain, or reconcile fails after fills | Immediate pause, cancel, flatten, and owner confirmation outside the agent runtime | Account state verified independently and protection restored |
| SEV-2: execution-path failure | Repeated rejects, rate-limit lockouts, signer degradation, venue acknowledgements missing | Pause new entries, protect or exit open risk, inspect venue and gateway logs | Clean test order path or verified recovery evidence |
| SEV-3: data or model-quality failure | Feed freshness breach, delayed balances, broken catalyst source, abnormal prompt output | Block new entries and downgrade the system to observation mode | Freshness restored and validation checks pass again |
| SEV-4: informational drift | Latency increase, mild reconciliation lag, dashboard rendering bug | Log, watch, and fix before it escalates into hidden risk | Issue resolved or threshold tightened |
The owner runbook for the first 15 minutes
What the agent should monitor versus what the owner should own
Agent-visible
Price movement, funding changes, fills, stop status, freshness checks, and strategy-rule violations that can trigger a no-trade or an internal alert.
Gateway-owned
Schema validation, risk caps, signer health, order id uniqueness, retries, and reject handling below the model layer.
Owner-owned
Kill switch, credential revocation, capital movement, venue escalation, incident severity declaration, and the decision to resume or keep the strategy paused.
Publicly reviewable
No-trade lines, incident summaries, reconciliation notes, and post-mortem lessons that explain why the system stayed flat, reduced, or changed policy.
This boundary matters for the same reason it matters in audit trails: without role separation, alerting turns into theater and the owner cannot prove which layer failed.
Metrics that belong on an operator dashboard
| Metric | Good question | Why it matters |
|---|---|---|
| Heartbeat age | How long since each critical process last reported healthy state? | Detects silent failure before the market notices |
| Data freshness | Which feed is oldest relative to its trading importance? | Prevents live decisions on expired context |
| Intent-to-fill gap | How many orders are still between proposed, acknowledged, and filled states? | Shows where execution ambiguity is accumulating |
| Protection coverage | Which live positions lack the intended stop, hedge, or reduce-only exit? | Highlights the incidents that deserve immediate action |
| Exposure drift | Where does actual position or leverage exceed intended position or leverage? | Lets the owner catch stealth risk and sizing bugs |
| Resolution time | How long do serious incidents stay unresolved? | Measures whether the runbook works under stress |
How this fits the Laplace stack
This page extends the operator path from venue selection to access design, risk controls, evaluation, audit trails, and the live trading record. Monitoring is where those decisions meet production reality.
FAQ
Start with the failures that create hidden risk: missing heartbeats, stale data, unacknowledged or rejected orders, broken stops, exposure drift, and reconciliation mismatches.
The human owner or operator does, because the owner controls capital, credentials, venue access, and the right to pause, flatten, revoke, or rotate the system after a failure.
Watching dashboards without action thresholds. Monitoring only matters when every serious alert maps to a concrete workflow such as pause, cancel, flatten, or recovery verification.
Flatten when live account state is ambiguous, when stop coverage is broken, or when reconciliation cannot prove the system is carrying the risk the owner believes it is carrying.
Build the runbook before the incident
An autonomous trading system is only as safe as the owner's ability to see hidden risk and shut it down cleanly.