A coding agent workspace is the environment in which an Agent can see project files, run tools, and leave work for the next step. Before choosing one, ask two questions: where does the task actually run, and what remains when it ends? A browser tab is not proof of cloud execution, and a large model context window is not a durable project filesystem.
This guide compares three practical setups—your own machine, a vendor's cloud task environment, and a shared cloud project Workspace. It is a decision checklist, not a claim that one setup is universally safer, cheaper, or better at coding. Product behavior was checked against OpenAI's Codex cloud documentation, Anthropic's Claude Code platform guide, and Agent.Space's Workspace description on September 20, 2026.
A Workspace is the environment, not the model or Agent harness
The model supplies reasoning and generation. The Agent harness organizes context, tools, permissions, and the execution loop. The Workspace is the project environment around that work: files, processes, access, and the state someone can inspect later. The Agent harness vs model guide separates those layers in more detail.
This distinction changes what a purchase or installation solves. Paying for model access does not automatically provide a shared project environment. Installing a coding Agent locally does not automatically preserve a running process when your laptop sleeps. A remote interface may control a process on your own machine rather than move it into a cloud Runtime.
Three common execution setups
These are patterns, not rigid product categories. One vendor can offer multiple surfaces. For example, Codex cloud runs tasks in isolated cloud environments configured for a repository, with dependencies, variables, and secrets set up before a task; it returns a summary and diff for review. Claude Code's platform guide distinguishes its cloud-based Web tasks from Remote Control, which steers a Session still running on your own machine. Neither example means that every browser-based coding Agent has the same execution host or persistence model.
Six checks before committing a project
1. What state survives?
Test files, configuration, uncommitted changes, logs, and decisions separately. A finished task may preserve a diff but not a live server. A saved file may survive a Runtime restart while an in-memory process does not. Ask what must be committed, exported, backed up, or restarted.
2. Who can see and change the project?
Identify the owner of the Workspace, repository connection, credentials, and invite permissions. A teammate who can view a result may not be allowed to edit files or start an Agent. An Agent that can read a repository should not automatically receive every secret or external service permission. For a deeper checklist, see coding Agent Workspace security.
3. Can another Agent continue without pretending to share private context?
The reliable handoff is explicit project state: current files, a short decision note, test results, and open risks. Separate Agent Sessions do not silently share hidden reasoning. If a product promises continuity, verify exactly what the second Session can inspect and whether it starts from the same current files.
4. How are parallel changes reviewed?
Two Agents editing the same working tree can conflict. Separate environments or branches can reduce collision, but someone still has to compare the results and integrate them. Ask whether the product creates isolated tasks, shared-file Sessions, or both, and where the final diff and approval happen.
5. Which bill pays for each request?
Separate the Workspace fee or plan from model inference, Agent subscriptions, API usage, and optional cloud resources. Verify the actual authentication and model route before estimating cost. A familiar Agent name does not mean a separate product inherits the Agent vendor's subscription or quota. Evaluate the current Agent.Space pricing only for the Agent.Space route, not as a substitute for an OpenAI or Anthropic quote.
6. How do you leave?
Export ordinary project files and record the dependencies needed to run them elsewhere. Check what happens to the repository connection, secrets, Session history, and Preview URLs. An exit path matters even when you expect to keep using the platform.
Run one bounded trial before deciding
Choose a small task with a clear acceptance check, such as changing one page and running its relevant build. Start from the same repository state in each setup. Record the execution host, setup time, credentials required, files changed, checks run, review surface, and what survives after closing and reopening the environment.
Then ask a second person or Agent to continue from the saved result without a verbal recap. This tests the actual handoff rather than the marketing promise. Do not call the result a model benchmark: the environment, tools, permissions, and selected model may all differ.
When Agent.Space fits
Agent.Space's cloud Workspace is designed for supported Agents such as Codex and Claude Code to work in separate Sessions against saved project files, with Previews and teammate access around the same project. That can fit a team that wants to change Agents or people without reconstructing the project. How Agent.Space works explains the exact Session and Workspace boundary.
It is an independent product, not an official OpenAI or Anthropic service, a shared upstream login, or a way to refill an upstream allowance. It does not make every Agent/model pairing available, keep every process running indefinitely, or automatically merge simultaneous edits. Check the live Agent and model selectors, the permission controls, and the current bill before relying on it for a project. If that setup fits, start a Workspace with one bounded task and evaluate the result against your own acceptance checks.