AI Models Adopt Continuous Updates With Canary Rollouts

Evidence from creators highlights that AI deployments will transition from discrete major launches to seamless continuous updates. Current model weights function as deployment artifacts but lack the observability and safety features standard in software engineering. Practices such as canary rollouts, shadow traffic, and instant rollback are cited as proven solutions already applied elsewhere. Separate commentary notes that pretrained systems overshoot human capabilities by skipping ongoing trial-and-error adaptation, with real intelligence tied instead to continual learning that adjusts to environments in real time.