When components fail, the system adapts. When they recover, work resumes.
Every critical path has a fallback. If the primary cloud model is unavailable, a secondary model takes over. If cloud access is entirely down, local models handle what they can and queue complex tasks for later. The system degrades gracefully rather than failing completely.
Your context, task state, and pending workflows are preserved across failures. If the system goes down mid-task, it picks up where it left off when it comes back — you don't need to re-explain or restart.
The system continuously monitors component health. When a failed component recovers, queued work is processed automatically. You're notified of any delays, but you don't need to take action to resume operations.