Observability From First Principles
by Mitch Radhuber
Observability tools are designed to be maximally information-rich, which is reasonable when you assume that an engineer will need that information to debug something, but this assumption no longer holds.
"Observable" implies that someone's doing the observing. We don't reject the premise that systems need to be observed, we just think the observer shouldn't be human. Today's tooling needs to be overhauled and redesigned for the post-AI world.
Our thesis is simple: humans should only care about raw observability data insofar as they need it to verify the work of AI agents. This is the post-AI observability workflow, where the interface to your production systems is the curated output of agents, not noisy logs, metrics, and alerts.
There are orders of magnitude more leverage out there yet to be captured for engineering teams, and retrofitting a mature platform designed around an antiquated workflow won't suffice. Corelayer is our attempt to help you answer the question: how much more could you achieve if you never had to worry about production support and maintenance?
Put this into production.
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