Everything an agent needs to do real work.

Each autonomous worker gets a dedicated execution boundary with its own filesystem, processes, resources, configuration and state rather than sharing an uncontrolled host environment.

Give autonomous systems a real workspace where they can create directories, clone repositories, manipulate documents, generate artifacts and preserve outputs across multiple reasoning turns.

A long-running agent shouldn't lose its working environment because a model turn ended. Preserve the files, processes and workspace state required to continue the job later.

Pause inactive spaces while preserving the environment needed to continue. When work returns, resume from the existing state instead of reconstructing everything from scratch.

Capture a runtime space at a known point so agents can experiment, recover, reproduce execution or create new environments from a proven state.

Clone an existing space and let multiple agents explore different approaches from the same starting point—without corrupting the original environment.

Separate autonomous execution from trusted control infrastructure so commands, packages and generated code run inside a defined environment rather than directly against critical host systems.

Define outbound access according to the job. A coding agent might reach package registries and Git repositories; a sensitive analysis environment might operate without open internet access.

Broker credentials at the execution boundary so agents can use approved services without requiring durable secrets to be embedded directly into prompts, repositories or generated code.

Create spaces from reusable environments containing the languages, libraries, browsers, CLIs, repositories and utilities a particular agent requires.

Start development servers, APIs, notebooks, previews and other long-lived processes inside the space so autonomous builders can test the systems they create.

Expose selected services through controlled preview endpoints so humans or other agents can inspect a generated application before it is promoted outside the runtime space.

Give specialized agents independent spaces while letting the control plane coordinate artifacts, messages and approved resources between them.

For disposable execution, provision a fresh environment, complete the task, export the required artifacts and remove the space when its work is finished.

Long-lived assistants, development agents and operational workers can retain an environment across many jobs, accumulating approved tools, working files and project state over time.

Store durable notes, project knowledge, generated artifacts and execution history alongside the work itself so future runs can reconnect to an existing operational context.

Track commands, processes, resource use, files, network activity and lifecycle events so operators understand what autonomous workers are actually doing.

Define reusable environment templates containing dependencies, configuration and starting files so repeated agent runs begin from a known execution state.

Create repeatable execution environments for evaluations, reinforcement learning and agent experimentation where each rollout begins from a controlled starting state.

Give agent frameworks a simple abstraction for creating, connecting to, pausing, snapshotting, forking and destroying execution environments.

The runtime can treat execution space as a portable concept regardless of whether the underlying environment is local, containerized, virtualized, cloud-hosted or deployed at the edge.

Place execution environments according to compute needs, data locality, geography, hardware availability, policy and cost while preserving the same agent-facing workspace abstraction.

Agent workloads often alternate between active execution and waiting on models, humans or external systems. RuntimeSpace can align compute lifecycle with that stop-and-start pattern.

Separate reasoning from execution. The model decides what to do; the runtime governs how work proceeds; the space provides the concrete environment in which files change, commands execute and artifacts are produced.

A programmable environment layer where autonomous software can execute, build, persist, branch and collaborate without sharing an uncontrolled machine.