Because agents retry steps, re-plan tasks, and run asynchronously, the same action can sometimes execute more than once.
In production systems this can cause duplicate payouts, repeated mutations, or inconsistent state.
Kybernis is a reliability layer that sits at the execution boundary of agent systems.
When an agent calls a tool:
1. execution intent is captured 2. the action is recorded in an execution ledger 3. idempotency guarantees are attached 4. the mutation commits exactly once
Retries become safe.
Kybernis is framework-neutral and works with agent frameworks like LangGraph, AutoGen, CrewAI, or custom systems.
I built this after repeatedly seeing reliability failures when AI agents interacted with production APIs.
Would love feedback from anyone building agent systems.