How to run autonomous research agents at scale

Autonomous research agents independently conduct multi-step workflows involving web searches, document retrieval, code execution, data analysis, and synthesis into reports or other structured outputs, but operating many concurrent sessions creates challenges involving isolation, controlled web access, long-running task reliability, credential handling, and cost management. The material argues that each session should run in a separate environment to prevent interference or exposure of files, processes, credentials, and confidential information, while network policies should limit access to potentially sensitive services and mitigate risks such as prompt-injection-driven data exfiltration. It presents Northflank as an infrastructure platform for these workloads, offering microVM-based Sandboxes with isolated filesystems and networking, API-managed lifecycle controls, persistent or ephemeral storage, centrally managed secrets, scalable CPU and GPU capacity, governance features such as RBAC, SSO, and audit logs, and deployment through managed infrastructure or bring-your-own-cloud environments.

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