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An AI pilot also needs to handle incomplete documents, exceptions and errors. Prepare the process for everyday use, with people able to review and correct the results.

When a tool does not quite fit, decide whether to adapt it, connect it or build something new. Compare the options against your team's actual work.

Your Django application works locally, passes tests, and the team wants to deploy it to production. But between "it works on my machine" and "it runs stably on a server" lies a territory full of decisions that are rarely well explained. Kamal fits right into that in-between space: when manual scripts no longer scale, but Kubernetes is still more than you need.

Production security isn't just a list of enabled tools. It's a set of safeguards your team can verify. If you can't explain who has access, what's exposed, and what happens when something goes wrong, your system isn't ready.

Deployment is just the beginning. If your app isn't monitored, your users will discover every problem before you do. What you need isn't pretty dashboards or alerts for everything. You need to know what to watch, what to ignore, and when to take action.

There are teams that don't test anything and pray before every deployment. And there are teams that aim for 100% coverage and don't deliver on time. Both have a testing problem. The question isn't whether to test, but how much, where, and why.