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First, check the chatbot provider’s official status page for the specific product or feature you need. Then preserve your inputs and draft outside the chat, decide which parts of the task can safely continue without AI, and monitor the incident before retrying. A service outage may affect only one feature, and a green status indicator cannot confirm that an individual unsaved request was preserved.
What to do first when your AI chatbot stops working
When a chatbot fails in the middle of a task, separate two questions: is the service having an incident, and what work can you safely preserve or continue while it is unavailable? A few deliberate checks are more useful than repeatedly resending the same prompt or refreshing without a plan.
- Check the official status page. Find the product and component related to your task—such as chat, sign-in, file uploads, or an API feature—rather than relying on a general outage headline.
- Identify what failed. Note whether you cannot sign in, send a prompt, upload a file, or use a particular model or feature. That detail will help you decide whether the outage affects your task.
- Protect the work you still have. Save local copies of source material and drafts, and record the last completed step and the next action somewhere independent of the chatbot.
- Choose a safe fallback. Continue the parts of the task that do not require generated output; pause any step that depends on the unavailable feature.
- Follow incident updates, then verify recovery. Check the relevant component again before resuming, and inspect the conversation and your local work for anything missing.
These steps help you manage the work; they do not repair the provider’s service or guarantee that a feature will return on a particular schedule.
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How to tell whether the chatbot or just one feature is down
An error in one part of a chatbot does not establish that every part is unavailable. Sign-in trouble, prompt errors, upload failures, and model-specific problems can have different causes and may be affected differently during the same incident. Start with the symptom you observed, then compare it with the component named on the provider’s status page.
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Match the symptom to the component
- You cannot sign in: Look for a sign-in or authentication component, if the provider lists one. A working status for chat does not by itself confirm that sign-in is working for you.
- A prompt will not send or complete: Check the chat or model-related component that matches the product you were using. If the page reports an incident, avoid treating repeated retries as a recovery strategy.
- A file will not upload or process: Look for an upload or file-handling component where available. If it is affected, consider whether you can continue using material you already have locally.
- Only a particular model or API feature fails: Check for the closest matching model or API component. Do not infer that another model, account tier, or API feature has the same availability.
OpenAI’s status page lists ChatGPT and API components separately and cautions that its availability metrics are aggregate: an individual’s tier, model, or API feature may differ. Anthropic’s incident history likewise shows that several features can be affected differently within one event. The practical implication is to check the component that your task depends on, not just the overall headline.
Status pages are snapshots, not a guarantee about what is happening on your particular account at this moment. Recheck them before describing a service as currently down or recovered. The provider incident records reviewed for this article were captured on October 13, 2026; status information can change after that date.
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How to protect your prompt, files, and task context
Do not assume a message was saved simply because you clicked Send or saw it appear to go through. Anthropic reported that some messages sent during its September 29, 2026 incident might not have been saved. That is a reason to verify your own work, not evidence that every message is lost during every outage.
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Put a brief checkpoint somewhere that does not rely on the affected chatbot. It should be enough for you—or a colleague—to continue without reconstructing the task from memory.
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- Task: What outcome are you working toward?
- Inputs: Where are the source files, reference links, notes, and instructions stored?
- Completed: What work is finished and what have you checked?
- Next: What is the next action, and does it require chatbot output?
- Unverified: Which response, upload, or result do you still need to confirm?
Keep original source material and locally available drafts distinct from generated output. If the chatbot becomes available again, this makes it easier to tell what the service actually retained from what you saved independently.
How to keep working without creating rework
A useful fallback continues the underlying task; it does not pretend to replace a down service. Whether to proceed depends on the cost of doing the work manually, the risk of proceeding without generated output, and how much of the context you can preserve. The options below are practical planning choices, not a formal provider comparison.
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| Fallback | Can the task proceed safely without generated output? | Does it preserve source material and context? | Does it depend on the same unavailable chatbot? | Reconciliation after recovery |
|---|---|---|---|---|
| Continue research from sources already open | Often, if the next step is reading, collecting, or organizing source material rather than asking the chatbot to interpret it. | Yes, if you keep the source links and your notes outside the chat. | No, for work done directly in your browser or local notes. | Compare your notes with any chatbot-assisted analysis you later resume; do not treat unfinished interpretation as completed. |
| Draft or outline manually | Yes, when a rough draft is useful and does not need to be represented as AI-generated or final. | Yes, if the draft and its inputs are saved locally or in an independent workspace. | No, if the writing is done without the affected service. | Mark which portions are yours and which still need review or AI-assisted work. |
| Ask a colleague to review or take ownership | Sometimes; it depends on whether the person has the needed context and whether sharing the material is appropriate. | Potentially, if you provide the relevant files, notes, and next action through an available channel. | Not necessarily; it depends on the colleague’s tools and the channel used. | Record what was reviewed or changed so it is not duplicated after the chatbot returns. |
| Pause the AI-dependent step and switch tasks | No for the blocked step, but other independent work may continue. | Yes, if you preserve the step’s inputs and checkpoint before switching. | No, while you work on an unrelated task. | Resume from the recorded next action and verify whether the blocked request or output exists. |
Choose the smallest safe fallback. If the task requires an AI-generated answer, do not quietly substitute an unreviewed manual guess for it. Preserve the inputs and move to a separate task, or make a clearly labeled manual draft if that is acceptable for your purpose. If a colleague takes over, share only material they are authorized to see.
How to follow the outage and retry deliberately
Use the provider’s incident updates rather than guessing from a single error message. OpenAI says its status page includes current and historic uptime information and allows subscriptions to status changes. Anthropic offers incident email and/or text notifications. These can reduce the need to repeatedly check manually; they do not guarantee a notification at a particular time or that your individual account is working.
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- Open the relevant official status page and identify the affected product or component.
- Read the incident update for the reported impact and any stated workaround. Google’s Workspace Gemini incident history includes incidents that explicitly said no workaround was available, so do not assume there is a user-side fix.
- Subscribe to available status notifications if you need to track recovery and the provider offers them.
- Revisit the page when an update appears, and check the affected component rather than relying only on an overall status label.
- When the component is reported recovered, make one careful attempt to resume the task and verify the result before repeating work.
If the provider reports no workaround, focus on preserving context and choosing other work. Trying many account, browser, or prompt changes without evidence that they address the reported incident can consume time without resolving the service problem.
What to check before resuming after recovery
A provider’s recovery notice is a useful signal, but it does not establish that a particular unsaved request survived or that every feature is healthy for every account. Reconcile your local checkpoint with what is visible in the conversation before continuing.
- Confirm the relevant component’s status. Check the feature your task uses, not just the provider’s general status.
- Inspect the conversation. Look for the last completed exchange and compare it with your continuity record. Treat a missing or incomplete request as unverified.
- Review local files and drafts. Confirm which source material and manual work are already saved, so you do not overwrite or duplicate them.
- Resume from the next action. If the prior request is missing, resend only after confirming the inputs and instructions you need. If it is present, continue from the next unfinished step.
- Check the new result before relying on it. A successful response shows that this attempt completed; it does not retroactively confirm that an earlier request was saved.
Prepare a fallback for recurring, important work
For work that regularly depends on a chatbot, keep a short fallback note with the manual next step, the location of source material, who can take ownership, and what to check before resuming AI-assisted work. This is a continuity recommendation based on the kinds of interruptions reflected in provider incident records, not a provider-mandated standard.
Keep the note proportional to the task: a few lines can be enough if the source files and decision history are easy to find. Review it when the workflow changes, especially if its inputs move or the person responsible changes. The purpose is not to predict outages; it is to make the first safe action clear if one occurs.
Official incident records provide useful examples of why this preparation matters: OpenAI’s status and incident pages, Anthropic’s Claude Status history, and Google Workspace’s Gemini incident history describe incidents affecting services or features. Those records do not establish a universal outage frequency or guarantee how a future incident will behave. Use them as examples of possible disruption, not a forecast for your own account.
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