Kybernis – Prevent AI agents from executing the same action twice
AI agents increasingly execute real system actions: issuing refunds, modifying databases, deploying infrastructure, calling external APIs. 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.…
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AI agents increasingly execute real system actions: issuing refunds, modifying databases, deploying infrastructure, calling external APIs. 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.
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