Always-on agents run production without the on-call tax

Official Schedule Context

Most production teams have the same problem. The work that keeps systems healthy- deployment checks,

on-call handoffs, anomaly reviews- never makes it into a sprint. It falls to whoever has bandwidth,

gets done inconsistently, and disappears when people are stretched thin. Background agents fix this

by running that work on a schedule, using the same production context a senior engineer would,

without waiting for someone to initiate it. Justin Smith, Founding Engineer at Resolve AI, walks

through the architecture behind always-on agents, the use cases teams are starting with today, and

what we have learned from running them in our production environment.

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

Pending transcript synthesis when an official recording or confirmed matching video is available.