What is an Agent Runtime?
An agent runtime is the execution environment that actually runs an AI agent's process — managing its sandbox, its available compute, its access to tools and credentials, and its lifecycle — as distinct from the agent's reasoning logic itself.
The runtime is the infrastructure layer underneath the agent framework: while the framework defines how the agent's reasoning loop and tool-calling logic work, the runtime is what actually provisions the container or process the agent executes in, enforces isolation between one tenant's agent and another's, injects credentials at the boundary rather than into the agent's own context, and tears the environment down cleanly when the task ends.
Runtime design choices have real security and reliability consequences: sandboxing an agent's execution limits the blast radius if it's tricked into a harmful action, lazy container creation (only spinning up an environment when an agent actually runs) saves resources but introduces timing gaps that credential-sync logic has to account for, and per-tenant isolation at the runtime level is what makes it structurally impossible for one tenant's agent to access another's data, rather than relying on the agent's own good behavior.
In practice with Neotask
Neotask runs each tenant's agent inside its own sandboxed container created lazily on first use; because the container doesn't exist until the agent's first run, the platform has explicit post-run credential-sync logic to catch the case where auth tokens were saved before that container ever existed.
Related terms
- agent-framework
- agent-loop
- agent-identity
- tenant-isolation
- agent-permissions
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