What is a persistent sandbox for AI agents?
One agent, one computer, any harness. A persistent sandbox keeps the Spinup Agent's machine intact between runs: files, package installs, generated artifacts, secrets, and harness configuration carry forward instead of being rebuilt from scratch. The agent is the durable identity above the sandbox; the active machine is replaceable capacity; the harness inside it can be swapped without losing the setup.
Why Persistence Matters
Some agent workloads degrade when the environment resets every time
Browser sessions, data pipelines, heavy toolchains, and iterative tasks all improve when the environment preserves state intentionally instead of forcing a full rebuild on every run.
Stateful workflows stay coherent
Browsers, downloaded files, generated artifacts, and temporary working state stay manageable when the runtime is not purely ephemeral.
Agent Chat cost drops
Package installs and toolchains are expensive to rebuild on every run, especially for heavier runs.
Persistence is about semantics, not idle servers
Persistence does not mean the live compute instance runs forever. It means the runtime preserves the right state between runs.
Deliberate beats drift
Persistence is deliberate, not the slow drift of a hand-maintained pet machine. The runtime decides what stays (files, packages, artifacts, harness config) and what is rebuilt cleanly.
Where the Term Helps
Persistent sandbox names one capability, not the whole runtime
Teams already search for this term. Spinup uses it as an entry point, then explains the larger runtime model around persistence, isolation, and the ability to swap the harness without rebuilding the environment.
Matches existing search language
The term matches what buyers search for when they need sandbox persistence and secure execution.
The runtime model stays visible
The phrase should not flatten Spinup into a generic code sandbox. The agent model and control plane above it are what matter.
Persistence unlocks more than storage
Persistence connects to managed lifecycle and harness portability: the capabilities that make a sandbox operationally useful.
FAQ
Persistent sandbox questions for AI agent teams
What does persistent mean if the sandbox is not running 24/7?+
Persistence refers to runtime semantics, not uptime. The compute does not need to be running for the environment to stay coherent: files, installed packages, generated artifacts, secrets, and harness configuration carry between runs instead of being rebuilt from scratch.
How is a persistent sandbox different from a regular sandbox?+
A regular sandbox runs code in isolation and resets when the run ends. A persistent sandbox preserves useful state between runs: installed packages, written files, cached data, and environment configuration. The result is a durable computer, not a disposable function.
What kinds of state can be persisted between agent runs?+
The runtime persists filesystem contents such as generated files, downloaded data, and working directories. It also preserves installed packages, toolchains, environment configuration, projected secrets, and any artifacts the agent produces during a run.
Does persistence create security risks from stale state?+
Persistence is deliberate, not unlimited. The runtime persists the surfaces that make agents productive: files, packages, artifacts, harness config. Isolation between agents stays intact. That is safer than leaving a long-running container to drift on its own.
Persistent Sandboxes in the Spinup Runtime
The runtime preserves useful state and keeps agents portable
A persistent sandbox helps when agents need durable files, packages, and artifacts. The broader product is the runtime and control plane that make that state usable, scoped per agent, and portable across harnesses.
Early access
Persist the runtime state that matters. Keep the agent portable.
Request access if this is the runtime shape your team has been missing.