Auto Reconnect matters because long-running AI coding tasks do not always stay inside a perfect connection window. Spectra treats reconnect behavior as part of session continuity, so users have a cleaner path back into active work instead of reconstructing context by hand every time something drops.
Last updated: 2026-03-30
Reconnect matters because long-running AI work is often more fragile than the task itself.
Reconnect works best when visibility, recovery, and control actions are aligned.
Users need to know what is active before a reconnect path can feel trustworthy.
It should live alongside session recovery instead of becoming a separate troubleshooting ritual.
Resume, pause, and delete actions should still be clear when the session path is interrupted.
The more often sessions outlive a stable connection, the more valuable reconnect becomes.
You need the workflow to survive normal drops instead of restarting mentally from zero.
You want continuity to still work when you are not sitting at the primary machine.
You want fewer interruptions to turn into support questions.
You care about keeping work in motion, not just launching new tasks.
Because long-running AI workflows often survive the task itself but not the connection. Reconnect reduces that gap.
Not exactly. Reconnect helps preserve continuity when the connection drops, while session recovery handles the broader path back into work.
Users and teams that routinely leave tasks running long enough for interruptions to matter.
These pages continue from reconnect into the broader continuity model that keeps work recoverable over time.