Rivet

Based on the available evidence, Rivet looks promising enough to track closely, but capability judgments should still be conservative. The adoption signal is moderately positive: the project repeatedly presents self-hosting, managed compute, BYOC, local development, and “give agents an operating system as a library,” which suggests it is targeting runtime and deployment problems rather than simple model calling. Still, most evidence here comes from the official account and founder posts on X, so attention is proven more clearly than production maturity.

In practice, Rivet appears closer to a backend runtime and state layer for agents. The evidence repeatedly frames Rivet Actors as an open-source Durable Objects alternative, with stateful execution, schedules, workflows, multiplayer patterns, and SQL, plus the idea that the same agent code can run on Vercel or Rivet. That means it is not a chatbot builder, not just a prompt tool, and not merely a generic workflow orchestrator. A more accurate analogy is “a stateful application runtime plus deployment abstraction for AI agents.” If your output is a long-running, schedulable, self-hostable agent service, the positioning makes sense.