Do production agents need their own kind of PaaS?

Traditional PaaS made it easier to deploy web apps. You pushed code. The platform handled hosting, scaling, logs, deploys, env vars, rollbacks. But production AI agents seem to need a different kind of platform layer. The hard parts are not just where the agent runs. They are things like: where the agent state lives how tool calls are authorized how risky actions get approved how side effects are recorded how retries avoid duplicate writes how failed runs are resumed or rolled back how traces become eval cases how policies are versioned and replayed how humans intervene without breaking the workflow A normal app platform assumes the application logic is mostly deterministic. An agent platform has to assume the planner is non-deterministic, but the execution layer still needs to be deterministic enough to audit, recover, and trust. That feels like a different abstraction. Maybe the platform should not just provide compute. Maybe it should provide: durable execution tool gateways permission envelopes approval checkpoints idempotency keys execution receipts recovery records eval feedback loops policy traces In other words, not “hosting for agents,” but an operational control plane around agents. Curious how others see this. Are production agents just another workload for existing PaaS/workflow platforms, or do they need a new platform category?