Considering you have built them all in last few weeks, it should not be that difficult and no reason other systems won't reuse same.

How hard do you think it would be for ai to generate all those for some alternative?

I've been digging into how Heartbeat works in Openclaw to bring directly into Vibetunnel, another of Peter's projects

That’s missing the point. OpenClaw is just one of many apps in its class. It, too, will fall out of favor as the next big thing arrives.

It's definitely not right now. What else has the feature list and docs even resembling it?

Not sure. I mean the tech yes definitely.

But the community not.

This is the underrated risk that nobody talks about enough. We've already seen it play out with the Codex deprecation, the GPT-4 behavior drift saga, and every time Anthropic bumps a model version.

The practical workaround most teams land on is treating the model as a swappable component behind a thick abstraction layer. Pin to a specific model version, run evals on every new release, and only upgrade when your test suite passes. But that's expensive engineering overhead that shouldn't be necessary.

What's missing is something like semantic versioning for model behavior. If a provider could guarantee "this model will produce outputs within X similarity threshold of the previous version for your use case," you could actually build with confidence. Instead we get "we improved the model" and your carefully tuned prompts break in ways you discover from user complaints three days later.