Making Your Model API Pleasant to Integrate Against

• Error messages that don't distinguish causes: a generic failure response makes a caller guess whether to retry, back off, or give up, so most just retry blindly.
• Inconsistent streaming behavior across endpoints, forcing every client team to write its own parsing logic instead of reusing one approach.
• Undocumented timeouts and retries on your side, which surprise callers who built their own retry logic on top of yours and end up double-retrying.
• No sandbox or local mode, forcing every integration test to hit a real, billed model endpoint.

Each of these pushes engineering effort onto every client instead of solving the problem once, centrally.

A mode that returns realistic, deterministic responses without calling a real model lets client teams write and run integration tests without cost or latency, and without depending on a live endpoint being up during their own test runs.

It doesn't need to be sophisticated: canned responses keyed by request pattern are enough for most integration testing. The value isn't realism, it's determinism and speed, letting a client team catch its own bugs without waiting on network calls to a real model.

Distinguish, in both the error code and the message, between: a request that will never succeed as written, fix the request; a transient failure worth retrying, rate limited, back off and retry; and a failure that needs a human, not a retry, the model is down or the account is misconfigured.

A caller that can't tell these apart from your error response ends up either retrying everything, which wastes cost and delays real fixes, or retrying nothing, which turns transient blips into visible outages for their users.

For example, a caller who receives a rate limit response should see a clear code, a plain sentence saying the request was rate limited, and a hint about how long to wait before trying again. A caller who submits a malformed request should see which field failed and why. A caller whose account is misconfigured should see a message pointing to a person or a settings page. Each of these takes only a few lines on the server, and together they remove most of the guesswork that otherwise turns into a support question or a blind retry loop in every client.

A maintained SDK removes a lot of ergonomics problems by construction: consistent error handling, built-in retry logic with backoff, streaming parsing done once instead of by every client. The cost is maintaining it, which is real ongoing work, not a one-time project.

If you can't commit to maintaining an SDK, invest instead in unusually clear documentation with runnable examples for every error case, not just the happy path. A well-documented raw HTTP API beats a neglected SDK that's drifted from what the API actually does.

Publish your actual rate limits, timeouts, and retry behavior in the same place as your request and response schema, not buried in a separate operations page nobody reads until something breaks. A caller who knows your timeout is shorter than they assumed can design around it; one who finds out through a failed request in production can't.

This is cheap to document and expensive to leave undocumented, since every client team that hits the undocumented behavior ends up filing the same support question independently, one at a time, over the following weeks.

• Publishing an API specification that doesn't match the actual behavior, which is worse than no specification because it looks authoritative.
• Changing rate-limit or timeout behavior without updating docs, so every client team rediscovers the new behavior through failed requests.
• Assuming internal teams will just ask in chat when something's unclear, which doesn't scale past a handful of integrations.

Each of these looks like a documentation problem and is actually a support-load problem waiting to happen.