This resonates with real pain I’ve seen once agent systems leave the demo phase. Most failures aren’t model quality issues — they are retries with side effects, partial execution failures, and lack of visibility/control once things are running live. The idea of a lightweight, inline control plane that doesn’t replace the orchestrator but governs execution step-by-step feels like a pragmatic way to tackle that.
I especially liked the ability to start in observe-only mode and progressively enforce policies, and the focus on auditability and permissions per step. That’s the kind of thing teams usually end up building ad-hoc once compliance or reliability becomes non-optional.
A couple of things I’m curious about (and would love your thoughts on):
1. How you think about debugging or replay for long-running/stateful workflows when enforcement decisions affect downstream steps
2. What you’re seeing in practice around latency overhead at scale when AxonFlow is fully in the hot path
Overall, this feels like it’s aimed at the right stage of maturity — not early demos, but teams already feeling production constraints.
I especially liked the ability to start in observe-only mode and progressively enforce policies, and the focus on auditability and permissions per step. That’s the kind of thing teams usually end up building ad-hoc once compliance or reliability becomes non-optional.
A couple of things I’m curious about (and would love your thoughts on): 1. How you think about debugging or replay for long-running/stateful workflows when enforcement decisions affect downstream steps
2. What you’re seeing in practice around latency overhead at scale when AxonFlow is fully in the hot path
Overall, this feels like it’s aimed at the right stage of maturity — not early demos, but teams already feeling production constraints.