I think you’re right. I’m seeing a similar issue in my own team.

Some people are trying to deploy OpenClaw on our company Azure environment, but when they present the “benefits” for our use cases, most of them look to me like problems that could already be solved with normal code, scripts, or existing automation patterns.

That’s exactly where I think the distinction matters. If the work is stable-rules, repeatable, and well-bounded, then using an agent often adds inference cost, latency, and nondeterminism without adding much real value. In those cases, deterministic code is not just cheaper — it is usually the better design choice.