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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesWhen an AI agent API call fails, first identify the status and exact error code; for a 429, distinguish a temporary rate limit from a billing or usage limit. Then check Retry-After, account for retries already performed by your SDK, and retry only transient failures within both an attempt limit and an overall deadline. For a timeout or lost connection, check whether the agent operation or its external actions already completed before submitting it again.
Start with this decision tree
- Capture the failure. Record the provider, API endpoint, model or agent configuration, SDK and version, attempt number, timestamp with timezone, elapsed time, status, exact error details, request ID, and relevant response headers.
- Classify the status and error. A 429 can indicate temporary request or token throttling, but it can also signal exhausted credit or an organization usage limit. A 504, connection failure, cancellation, or deadline expiry calls for a different investigation.
- For a temporary 429, inspect
Retry-After. If the response provides a valid delay, wait at least that long. If it does not, use exponential backoff with jitter. - Check the installed SDK’s retry behavior. It may already retry eligible responses. Avoid stacking an application retry loop on top without accounting for those attempts.
- Retry within limits. Bound both the number of attempts and the total time allowed for the operation. Do not retry a billing, usage, credential, or request-correction problem as if it were a transient throttle.
- Before repeating agent work, inspect its outcome. A request that timed out at the client may still have created a turn or performed an external action.
This sequence prevents two common mistakes: sending more traffic into a limit that will not clear through waiting, and duplicating agent work after an ambiguous failure. It also gives you a consistent order of operations: identify the failure, establish whether it is recoverable, then decide whether a retry is safe and useful.
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Capture enough evidence to diagnose the failure
Logs that say only “429” or “timeout” are rarely enough to distinguish a rate-limit event from a configuration or account problem. Save the details for each attempt, not just the final result. OpenAI’s troubleshooting guidance calls out the exact error, code, request IDs, time with timezone, and relevant limit information. Its API overview describes response headers as a source of unique request IDs and rate-limit details (OpenAI rate-limit troubleshooting; OpenAI API overview).
- Request context: provider, endpoint or API surface, model or agent configuration, and the SDK name and installed version.
- Attempt context: attempt number, when it began, elapsed time, and whether a cancellation or overall deadline occurred.
- Response context: HTTP status, exact error type, code and message, request ID, and relevant response and rate-limit headers.
- Operation context: whether a session or turn was created, whether it is still active or completed, and whether any external actions were performed.
Keep the original error and header values rather than replacing them with a generic application message. A request ID and timestamp with timezone make it easier to correlate a failure with provider-side logs or a support investigation. Avoid recording secrets or sensitive prompt content in diagnostic logs; retain the identifiers and metadata needed to trace the event.
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Make sure the evidence is tied to an individual attempt. If the application retries, a single operation can produce several different request IDs and statuses; retaining only the last response can hide the first cause or make the retry sequence impossible to reconstruct. Record whether the response was received at all, and distinguish an HTTP response from a local timeout or cancellation. Keep header values with their associated request rather than treating a later response’s headers as representative of the whole operation.
For a persistent provider issue, the request ID is particularly useful when contacting support. For an internal incident, the timestamp, timezone, endpoint, client version, and attempt number help establish whether failures cluster around a specific request path or retry behavior. These records should explain what happened without exposing credentials or unnecessarily retaining sensitive input.
Classify a 429 before retrying
A 429 is a response status, not a complete diagnosis. In OpenAI’s documented cases, temporary request or token rate limits are distinct from credit_balance_exhausted and organization_usage_limit_exceeded. The error code and message tell you whether to wait and retry or resolve an account condition first (OpenAI troubleshooting API rate limits and 429 errors).
Temporary request or token throttling
A temporary limit means requests are arriving beyond a current request or token allowance. Check the response details and headers, then follow a valid Retry-After value if one is present. If token pressure is indicated, inspect both the prompt size and the maximum output-token allowance: long prompts and unnecessarily large output allowances can contribute to token-rate errors. If requests are arriving in a burst, reduce burstiness or concurrency rather than immediately resubmitting the same workload.
Think about what the evidence says is under pressure. A request-rate problem points toward how quickly calls are arriving; a token-rate problem points toward the amount of input and potential output being requested. The appropriate adjustment is different: reducing concurrency or smoothing bursts addresses request arrival patterns, while shortening unnecessary prompt content or setting a more appropriate output allowance can address token volume. Avoid changing both indiscriminately if the response identifies one kind of limit, since targeted changes make it easier to tell whether the problem improved.
Credit or organization usage limits
credit_balance_exhausted and organization_usage_limit_exceeded describe account or usage conditions, not a short-lived throttle that an exponential retry loop can fix. Check the applicable billing, credit, or organization usage condition and correct it before resuming requests. Repeated retries in this situation add noise without addressing the cause.
In other words, more waiting is not the fix for every 429. If the error identifies exhausted credit or an organization usage ceiling, stop the automatic retry path and make the account or usage correction first. Treating all 429s as interchangeable can create a stream of failed calls while leaving the underlying condition unchanged.
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Do not infer a universal quota from one response
Rate limits depend on the provider, endpoint, model, account or organization, and current configuration. Do not hard-code a single limit number as if it applies to every agent deployment. Use the actual response information and the provider documentation for the endpoint and account in question. Limits are not a static contract shared across providers, so a number that seems to work in one deployment should not be used as a substitute for parsing the actual error and response metadata.
Choose a bounded retry policy
Retry only when the failure is plausibly transient. For temporary rate limiting, a valid server-provided Retry-After is the minimum wait, not a suggestion to retry sooner. If that header is absent or invalid, use exponential backoff with jitter: increase the wait after each unsuccessful attempt and add randomness so multiple clients do not all retry together. OpenAI describes the principle this way: “Exponential backoff means waiting briefly after an unsuccessful request, then increasing the delay after each unsuccessful retry.” (OpenAI rate limits.)
Jitter matters when many requests fail around the same time. If every client waits for the same fixed interval and then retries together, the recovery attempt can create another burst. Random variation spreads retries out instead of synchronizing them. When a valid server delay is present, however, the client should not use jitter to retry sooner than that minimum.
A robust policy needs two separate bounds:
- Attempt limit: cap how many retries one operation may make. Count SDK retries as well as retries in your application.
- Total operation budget: cap elapsed time for all attempts and waits combined. Stop when the operation’s deadline is reached, even if a retry remains.
Keep the policy provider-aware. The status and error parsing for one provider should not silently be applied to another provider’s API. The retry count and treatment of long server delays can also vary by SDK and version, so verify the behavior of the client actually installed.
What to retry—and what not to
- Consider retrying: a temporary rate limit or another documented transient failure, provided the operation remains within its attempt and time budgets.
- Do not keep retrying: credit exhaustion, organization usage limits, credential problems, or a malformed request that needs correction.
- Reduce pressure when indicated: lower burst or concurrent traffic for request pressure; reduce prompt or output-token volume for token pressure.
- Stop on cancellation or deadline expiry: these are operation-control outcomes, not merely another 429 to resubmit.
Unsuccessful requests can count toward per-minute limits. An immediate retry loop can therefore worsen the pressure that triggered the response. Backoff, bounded concurrency, and a total deadline are safeguards against turning one transient failure into a sustained burst. Retry limits should apply to the whole operation, not just to each individual helper or layer that happens to make a request.
Before retrying, make the policy’s decision explicit: is the error transient, is the server’s minimum delay satisfied, is there enough operation time left, and is it safe to repeat the work? If any answer is no, stop or route the error for correction rather than sending another call. This avoids a retry policy that technically has a maximum attempt count but still repeats errors that cannot be fixed by another attempt.
Account for retries inside the SDK
Before adding application-level retries, inspect the installed SDK’s documentation and configuration. Official clients may automatically retry eligible 429, 503, connection, or other transient failures. If an SDK makes retries and your application independently retries the whole call, the number of network attempts can multiply, and the operation can outlast the deadline you intended.
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Choose one clear policy: either let the SDK own retries and configure its limits, or disable or constrain SDK retries while applying a deliberate application policy. If both layers are needed, document and calculate the combined maximum attempts and ensure the outer operation deadline covers the full behavior. Do not assume a setting or default from a different language client or older SDK version applies to your deployment.
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Do not confuse a configured number of application retries with the number of requests that can reach the provider. If the SDK retries inside each application attempt, a single top-level call may represent several network attempts. Conversely, disabling one layer without checking the other can remove behavior you expected. Verify the actual configuration and observe the attempt sequence in logs before deciding that your retry policy is behaving as intended.
Separate an attempt timeout from the operation deadline
A per-attempt timeout limits how long one network request may wait. An overall deadline limits the whole agent operation, including all requests, retries, and backoff waits. A timeout on each attempt does not automatically impose a deadline on the complete operation: several attempts and delays can take much longer than any one attempt’s timeout. OpenAI’s rate-limit guidance specifically distinguishes these controls (OpenAI rate limits).
Set both controls deliberately. Before starting an attempt, determine whether enough of the overall budget remains for the request and any required wait. When cancellation or the deadline stops the operation, report that outcome separately from an HTTP response. Cancellation or deadline expiry can end retries without returning a 429, so treating every unsuccessful call as a rate-limit response obscures what actually happened.
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When a request times out at the provider
Anthropic documents 504 timeout_error for a request that timed out while processing. For long-running requests, it suggests considering the streaming Messages API. Streaming changes how completion must be detected: an SSE error can arrive after the API has already returned HTTP 200. A successful HTTP status alone therefore does not establish that the stream completed successfully; the client must process stream events and handle errors surfaced during the stream (Anthropic Claude API errors).
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Streaming is not a guarantee that a long request cannot fail. It changes the response pattern, so stream consumers need to watch events through completion and distinguish a completed stream from an error reported after the initial status. If the stream ends unexpectedly or yields an error event, preserve that detail alongside the HTTP status rather than marking the operation successful just because the connection began with HTTP 200.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Check whether an agent operation already happened
A timeout or lost connection tells you that the client did not receive a usable completion response; it does not, by itself, prove that the provider did no work. Before resubmitting, establish whether the session or turn was created, whether it remains active or has completed, and whether it performed external actions. OpenAI’s agent error-recovery guidance calls for checking the operation outcome and completed actions before retrying, because a repeated operation can duplicate effects (OpenAI errors and recovery).
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This distinction matters most when an agent can trigger an action outside the model call. If the first attempt may have sent a message, modified a record, or otherwise acted, blindly replaying the whole operation can do that work twice. Use the provider’s available operation or session state to reconcile what happened; retry only the work that is still known to be incomplete. The exact recovery mechanism depends on the API surface and the actions your application exposes, so do not treat a client timeout as proof of safe replay.
When the state is uncertain, pause before replaying. First check what the API surface exposes about the session or turn, then compare that state with the actions your application tracks. If the turn completed or an external action already occurred, repeating the entire agent request may be the wrong recovery. If it is still active, account for that before starting another operation. The key is to retry a known incomplete unit of work rather than assume that a missing response means no work happened.
Provider behavior: useful examples, not a shared contract
| Diagnostic area | OpenAI guidance | Anthropic guidance |
|---|---|---|
| 429 interpretation | Temporary request or token rate limits must be distinguished from credit exhaustion and organization usage limits. Use a valid Retry-After; otherwise use bounded exponential backoff with jitter. Rate limits; 429 troubleshooting. |
A 429 can reflect rate-limit or spend/usage conditions; inspect the error details and follow the provider’s retry guidance. Claude API errors. |
| SDK retries | Official SDKs retry eligible 429 and 503 responses; handling of long server delays varies by SDK version and configuration. TypeScript and JavaScript API Library. | Official SDKs retry transient failures, including connection errors, rate limits, and 5xx errors, with exponential backoff. The error documentation states two retries by default and honoring retry-after when present; verify the installed version. Claude API errors. |
| Timeouts and overload | Agent recovery guidance covers connection failures, request timeouts, and service errors; check operation outcome before retrying. Errors and recovery. | 504 is documented as timeout_error, and 529 as overloaded_error. Streaming can report an error after HTTP 200. Claude API errors. |
| Diagnostic identifiers | Inspect response headers for unique request IDs and rate-limit details. API overview. | The error documentation describes request IDs and advises including the ID when contacting support about persistent failures. Claude API errors. |
These are provider-specific examples, not a universal HTTP status-code contract. Keep error parsing isolated by provider and verify it against the current documentation for the endpoint and SDK version in use.
Use the comparison as a reminder to verify details, not as a static implementation recipe. Providers may use the same HTTP status for conditions that require different handling, and SDK retry behavior can change across language clients or versions. Keep parsing and retry decisions close to the provider-specific integration, while exposing a clear result to the rest of your application: retryable transient error, account or request correction needed, timeout or cancellation, or uncertain operation outcome.
A practical incident checklist
- Did you preserve the exact status, error type, code, message, request ID, headers, timestamp with timezone, and elapsed time?
- For a 429, does the code indicate a temporary request/token limit, or a credit or organization usage condition?
- If temporary, did you honor a valid
Retry-Afteras a minimum wait? - If no valid server delay was supplied, are retries using exponential backoff with jitter and bounded attempts?
- Have you checked retry defaults and configuration for the exact installed SDK and accounted for all retry layers?
- Does the operation have both a per-attempt timeout and a total deadline that includes backoff?
- Did cancellation or deadline expiry occur without an HTTP 429?
- For a timeout or lost connection, have you checked session, turn, and action state before replaying work?
- If requests are still failing, have you reduced burst/concurrent traffic or token volume where the error points to that pressure?
For follow-up, attach the request ID, timestamp with timezone, exact error and code, endpoint, SDK version, and relevant headers. Keep the retry timeline as well: how many attempts occurred, whether the SDK retried, how long each wait lasted, and whether the operation deadline or cancellation stopped further work. This makes it possible to distinguish a provider response from behavior introduced by the client.
Frequently Asked Questions
Should I retry every 429 from an AI API?
No. First inspect the error code and message. A temporary request or token rate limit may be retriable; credit exhaustion or an organization usage limit requires an account or usage correction, not repeated calls.
What should I do when a 429 includes Retry-After?
Treat a valid Retry-After value as the minimum delay before retrying. If the header is absent or invalid, use exponential backoff with jitter, and bound both retry attempts and total operation time.
How do I avoid retrying twice when my SDK already retries?
Check the retry configuration for the exact installed SDK and version. Decide which layer owns retries, or calculate the combined maximum attempts if both the SDK and application retry. Include all attempts and waits in the operation deadline.
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Does a client timeout mean my agent request failed without doing anything?
Not necessarily. The provider may have created a session or turn, completed it, or performed an external action before the client lost the response. Check available operation state and completed actions before replaying the work.
Is HTTP 200 proof that a streaming request completed successfully?
No. Anthropic documents that an SSE error can occur after HTTP 200. Process the stream events and verify completion rather than treating the initial status alone as success.
The Bottom Line
Debug in order: preserve the exact response and request ID, distinguish a transient 429 from an account limit, honor Retry-After or use bounded backoff with jitter, and account for SDK retries under one operation deadline. For timeouts or lost connections, reconcile session, turn, and action state before replaying work.
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