Totally agree, that “what actually hit the wire?” view is critical once things go async.

ModelRiver already has this covered via request logs. Every request captures the full lifecycle, the exact payload sent to the provider, streaming chunks as they arrive, partial responses, errors, retries, and the final outcome. Even if a stream fails midway, you can still inspect what was sent and what came back before the failure.

So you can clearly tell whether the issue is payload shape, provider throttling, or a mid stream failure, before any retry or failover logic kicks in. That wire level visibility is core to how we approach debugging async AI requests.