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Roronoa
Roronoa

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Keep Mobile AI Tasks Through Offline and Reconnect

A user submits an AI task on Wi-Fi, locks the phone, and returns on cellular. The spinner is gone. The server may have accepted the request, but the app has only an interrupted socket and an old screen.

July 25 supplies a provider-side condition for this flow. OpenAI's earlier incident began at 09:17:49 UTC, moved to mitigation monitoring at 10:02:52, and resolved at 11:08:36. A new incident started at 11:35:24; research found it identified with elevated errors and mitigation in progress. The status endpoint then reported Partial System Degradation. It does not prove root cause, global reach, an exact user count, or final recovery of that newer event.

This article proposes a test contract; it reports no device measurements.

Persist intent, not a spinner

Store a small local envelope before network submission:

{
  "localTaskId": "01-example",
  "inputDigest": "sha256:...",
  "createdAt": "2026-07-25T11:36:00Z",
  "state": "sending",
  "attemptId": "attempt-1",
  "provider": "primary",
  "lastServerVersion": 0
}
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Keep sensitive prompt content in platform-appropriate protected storage or avoid persistence according to the product threat model. A digest helps detect changed intent but cannot reconstruct the request.

On reconnect, fetch by stable task ID before resubmitting. The server should return not_received, running, completed, or unknown. Only not_received permits a new attempt automatically. unknown needs reconciliation because the old provider may complete after the phone moves networks.

editing -> stored -> submitting -> backgrounded
                              \-> reconnecting -> reconcile
reconcile -> running | completed | review_required
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Proposed lifecycle matrix

App/network transition Expected local behavior Server check User control
Wi-Fi → offline retain envelope none cancel locally
offline → cellular do not resend fetch task version reconcile
foreground → sleep mark last observation background work optional no fake completion
process killed → launch load durable envelope query stable ID resume or review
provider switch preserve old attempt create related attempt confirm differences

Test on named devices and OS versions before shipping. Record framework version, connection type, low-power mode, permission state, timestamps, and whether recovery resumed, restarted, or lost work. No battery, latency, or background-execution claim can be made without those observations.

Multi-provider fallback adds semantic risk on mobile as well as server complexity. Models may differ in prompt interpretation, tools, output schema, and context handling. Show users what will be resent over the network, and never switch a potentially side-effecting task merely because connectivity returned.

Evaluate portability away from the incident

The overseas MonkeyCode online environment currently uses the phrase “Start free.” Its official README describes managed server-side cloud environments with build, test, and preview and integrated models. Treat that as free to start; verify changing model/server quotas, regions, and uptime or SLA information inside the console.

The exact MonkeyCode open-source repository carries AGPL-3.0. At reviewed main revision 18baaf54937a65a7d47f1f9d83dd808777aa6cea, the README lists built-in management of development environments, models, tasks, and requirements. For mobile teams, hosted access can support a controlled cross-device trial, while source inspection and self-hosting provide an exit option. Neither guarantees continuity, and I did not test hosted MonkeyCode reliability.

My evaluation would start with a disposable task across browser sleep and mobile reconnection, recording only expected versus observed state transitions. The useful question is whether task identity survives the device lifecycle, not whether another model produces an answer.

Release gate

Do not release reconnect fallback until a real device matrix demonstrates: stable task identity after process death, no automatic resend from unknown, visible local-data retention policy, accessible reconciliation controls, and one accepted completion under delayed delivery. Those are acceptance criteria, not claimed results.

Disclosure: I'm a MonkeyCode user sharing my own experience, not affiliated with the project.

AI assistance disclosure: This article was drafted with AI assistance and reviewed against the cited primary sources.

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