"This is exactly the reliability gap we've been building around too. ARU (aru-runtime.com) approaches it from the certification angle — validating agent outputs against a contract before execution rather than after. Kybernis handles the idempotency problem at the execution boundary, ARU handles the output validity problem upstream. These could be complementary layers. Have you thought about pre-execution validation as part of the stack?"
Hi HN – I'm the founder of Kybernis.
The core problem we’re exploring is that AI agents are non-deterministic systems operating inside deterministic infrastructure.
Traditional systems assume actions run once.
Agents retry steps, re-plan tasks, and execute asynchronously.
That combination makes duplicate execution surprisingly easy.
Kybernis focuses on the execution boundary where agents trigger real mutations (payments, infrastructure changes, APIs).
Curious if others deploying agents have run into similar reliability issues.
"This is exactly the reliability gap we've been building around too. ARU (aru-runtime.com) approaches it from the certification angle — validating agent outputs against a contract before execution rather than after. Kybernis handles the idempotency problem at the execution boundary, ARU handles the output validity problem upstream. These could be complementary layers. Have you thought about pre-execution validation as part of the stack?"