Failed Deploy Fix
Your users are back on the last good build before debugging starts. Then PandaOS reads the log, finds the broken line and ships the fix.

The problem
A failed deploy blocks everything behind it: the release is stuck, the next push could make it worse, and the cause sits somewhere in a long build log, usually above a line like "npm run build exited with 1", in a different tool from your code. So you choose between rushing a fix and digging through dashboards to roll back by hand.
Every step shows in the chat, and the rollback waits for your OK.
The last deploy failed. Roll back, then fix it.
PandaOS opens the failed deployment in the Vercel app, right beside the chat.
Ask in the chat. PandaOS asks before it touches production, then rolls back to the previous deployment, the last good build.
With production safe, it reads the log and pulls out the error that stopped the build.
It traces the error to the file in your repo and patches it.
It pushes the fix through your existing Git and Vercel flow.
The new build is Ready, and the Jira ticket gets the cause and moves to Done, once you allow it.
When the fix is small but finding it is not.
The classic Module not found or type error: it worked locally, the Vercel build disagrees.
A package bump that breaks the build, traced and fixed from the log.
Errors that only appear on the build server, read straight from its output.
Get production back without opening three dashboards.
The parts of PandaOS this workflow runs on, each worth a look on its own.
Keep the deployment, the log and the code in one workspace, and let PandaOS carry the fix from error to live.
Vercel is the supported integration shown here, with deployments, build logs and domains in the app. With other hosts, PandaOS can still read build output in the terminal and push fixes through Git.
Only if you let it. Pushing and deploying are actions you control: let them run, have PandaOS ask first, or keep them off.
A rollback pins your domain to the last good build, so nothing else is promoted to production while the fix is made. The fix can then ship without pressure.
PandaOS explains what it found and asks before making a change that goes beyond the fix, such as upgrading a dependency.
PandaOS works on the project folder on your own machine, the same files you edit. You decide which AI provider and keys it uses.