At first, sub-2-second proofs sounded like a pure performance milestone… but something feels slightly off about looking at the number by itself.
But then I started wondering… what does being that fast actually change once the proof becomes part of the workflow?
It starts to look like:
confidential computation → client-side proof generation → fast verification → enterprise workflow → repeat
That loop matters because confidential systems usually face a tradeoff: stronger privacy can introduce more computation, more latency, and eventually more friction for the user.
If @dusk can push proof generation below two seconds for real enterprise workflows, maybe the conversation shifts from “can private computation work?” to “can it fit into normal operational timing?”
And that distinction feels pretty important.
This only works if the sub-2-second experience holds beyond controlled benchmarks — especially as workloads become more complex, proofs get heavier, and multiple users hit the system at once.
Maybe I’m wrong, but this feels less like a raw speed race and more like an adoption constraint being removed.
Maybe that’s where the infra conversation is shifting too — less fascination with big performance numbers, more attention on what actually holds up when usage gets real.
Still curious whether the speed stays this clean under pressure.
Because fast in a demo is one thing.
Fast enough to become invisible in an enterprise workflow is another.#dusk $DUSK @Dusk
But then I started wondering… what does being that fast actually change once the proof becomes part of the workflow?
It starts to look like:
confidential computation → client-side proof generation → fast verification → enterprise workflow → repeat
That loop matters because confidential systems usually face a tradeoff: stronger privacy can introduce more computation, more latency, and eventually more friction for the user.
If @dusk can push proof generation below two seconds for real enterprise workflows, maybe the conversation shifts from “can private computation work?” to “can it fit into normal operational timing?”
And that distinction feels pretty important.
This only works if the sub-2-second experience holds beyond controlled benchmarks — especially as workloads become more complex, proofs get heavier, and multiple users hit the system at once.
Maybe I’m wrong, but this feels less like a raw speed race and more like an adoption constraint being removed.
Maybe that’s where the infra conversation is shifting too — less fascination with big performance numbers, more attention on what actually holds up when usage gets real.
Still curious whether the speed stays this clean under pressure.
Because fast in a demo is one thing.
Fast enough to become invisible in an enterprise workflow is another.#dusk $DUSK @Dusk