Thanks JB_5000 — really appreciate you putting it that way. You're spot on: the whole point is constraints over intelligence. Guardrails (DSL, schema, deterministic replay, boring hybrid) are what actually make it production-usable.
On scaling: so far it's handling ~3k trial users + growing paid base with low four-digit RMB yearly infra (queue-driven scale-to-zero, Redis cache, R2 for artifacts). The real bottleneck is still alignment quality (good artifacts + human gates), not the constraint overhead itself. Haven't hit hard walls yet, but I'm sure 10x–100x load will expose new ones.
How about you? Have you seen constrained agents / deterministic layers scale well (or break) at larger sizes? Any guardrails that worked surprisingly well for you?
Thanks again!
On scaling: so far it's handling ~3k trial users + growing paid base with low four-digit RMB yearly infra (queue-driven scale-to-zero, Redis cache, R2 for artifacts). The real bottleneck is still alignment quality (good artifacts + human gates), not the constraint overhead itself. Haven't hit hard walls yet, but I'm sure 10x–100x load will expose new ones.
How about you? Have you seen constrained agents / deterministic layers scale well (or break) at larger sizes? Any guardrails that worked surprisingly well for you?
Thanks again!