Running AI agents on your local machine is a security headache and a validation trap. While local isolation works for simple coding tasks, it falls apart when you need to see how an agent handles real systems and production data.
Here is why the local approach is failing your workflow:
- Agents execute real commands that require real infrastructure.
- Local containers lack the environment depth needed for proper validation.
- Testing without production data means you are not seeing the full picture.
The solution is moving to cloud sandboxes. Using preview environments gives you a full stack sandbox with access to real data. It allows you to use the Git workflow as a safety net. This approach ensures your agent workflows are safe and your systems remain secure.
Read the full article for a deeper look at agent security and cloud sandboxing:
Why AI agents need cloud sandboxes - Upsun Developer
AI agents run real commands on real systems. Learn why cloud sandboxes with production data beat local isolation for safe AI agent workflows.
developer.upsun.com
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