# Cloud Coding Agents

Replicas is a cloud coding agent platform for delegating software tasks from GitHub, Linear, Slack, or the dashboard to isolated workspaces.

- Canonical: https://tryreplicas.com/cloud-coding-agents
- Get started: https://tryreplicas.com/auth?mode=signup
- Pricing: https://tryreplicas.com/pricing
- Docs: https://docs.tryreplicas.com/features/workspaces/overview

## What is a cloud coding agent?

A cloud coding agent is an AI coding agent that runs outside your laptop in a remote development workspace. It can clone a repository, inspect code, install dependencies, run commands, make changes, run tests, and prepare a pull request when code changes are needed.

## How Replicas works

- **Delegate work:** Start from a GitHub issue, Linear ticket, Slack request, or dashboard prompt.
- **Run in the cloud:** Replicas creates an isolated workspace with repository context and development tools.
- **Review the output:** Inspect the session output, file changes, test results, or pull request when the task is done.

## Why teams use cloud coding agents

- **Async by default:** Assign work and keep moving while the agent works in a remote development workspace.
- **Familiar agent harnesses:** Use cloud workspaces with coding agents your team already uses locally, including Claude Code and Codex.
- **Isolated compute:** Each task runs away from your laptop in a sandboxed environment built for code changes.
- **Team-visible work:** The task, workspace, files, session output, test results, and pull request stay inspectable.
- **Workflow-native inputs:** Start work from the places engineering teams already use: GitHub, Linear, Slack, and the dashboard.

## Use cases

- Turn GitHub issues into pull requests
- Assign Linear tickets to coding agents
- Delegate bug fixes from Slack
- Implement small product changes
- Run extensive end-to-end tests
- Investigate flaky failures and summarize findings
- Follow up on code review comments
- Clean up engineering backlog items

## Outputs

Pull requests are the standard output for implementation work, but cloud coding agents can also return test runs, investigation notes, reproduction steps, setup validation, and other engineering results.

- **Pull requests:** The standard output for implementation work: changed files, commits, and a reviewable branch.
- **Test runs:** Long-running verification work such as browser E2E tests, local reproduction steps, or release checks.
- **Investigation notes:** A trace of what the agent inspected, commands it ran, failures it found, and recommended next steps.
- **Operational tasks:** Repository maintenance, dependency checks, setup validation, or other engineering work that does not always need a code change.

## Evaluation checklist

The most important evaluation criteria are whether the platform runs trusted agent harnesses and whether it lets teams control inference economics instead of bundling every cost into one opaque agent.

- **Trust:** Can the platform run the coding agent harnesses your engineers already trust, instead of forcing every team onto a new agent experience?
- **Inference control:** Can your team use existing provider subscriptions, API keys, credits, or enterprise agreements where the underlying agent supports them?
- **Infrastructure separation:** Is the platform charging for the cloud workspace, orchestration, and collaboration layer separately from model inference?
- **Reviewability:** Can people inspect the session, commands, test logs, file changes, and final output before trusting the result?

- Does it run tasks in isolated cloud workspaces?
- Does it support the agent harnesses engineers already use locally?
- Can teams bring their own inference path through supported subscriptions, API keys, credits, or enterprise agreements?
- Can it connect to GitHub and open reviewable pull requests when code changes are needed?
- Can work start from Linear, Slack, GitHub, or a dashboard?
- Can humans inspect session output, file changes, test logs, and final notes?
- Can teams configure environments, secrets, and repository access?

## Background work

Cloud describes where the agent runs: remote compute with the repository, environment, terminal, files, and tools needed to make progress. Background describes the delegation model: a task can continue asynchronously after a developer assigns it. In Replicas, that workflow still keeps people in the loop to inspect sessions, steer work, review changes, and decide what ships.

## FAQ

### What is a cloud coding agent?
A cloud coding agent is an AI coding agent that runs in a remote development workspace instead of only inside a local editor. It can clone a repository, inspect code, make changes, run commands, run tests, summarize findings, and prepare a pull request when code changes are needed.

### How is a cloud coding agent different from an IDE assistant?
An IDE assistant helps while a developer is actively editing code. A cloud coding agent can take delegated work and continue in an isolated remote workspace while the developer does something else.

### Can cloud coding agents work in the background?
Yes. Cloud describes where the agent runs, and background describes how a delegated task can continue asynchronously. Replicas supports that workflow while keeping people in the loop to inspect sessions, steer work, review changes, and decide what ships.

### Does Replicas store my code?
No. Replicas connects to your repository and runs work in isolated workspaces. Code is not stored in Replicas databases. Inactive workspaces sleep after 1 hour, archive after 7 days sleeping, and archived workspaces are automatically deleted after 30 days with no activity.

### Which coding agents can Replicas run?
Replicas supports Claude Code, Codex, Cursor, and Opencode so teams can use cloud workspaces with the coding agents they already trust.

### Can teams use existing AI subscriptions or credits with Replicas?
Replicas is built around bringing your own coding agent and inference path where the underlying agent supports it. That lets teams use existing subscriptions, API keys, provider credits, or enterprise agreements while paying Replicas for the cloud workspace and orchestration layer.

### Does every cloud coding agent task need to end in a pull request?
No. Pull requests are the standard output for implementation work, but cloud coding agents can also run E2E tests, reproduce bugs, inspect logs, verify setup, or return investigation notes when the useful output is not a code change.

## Related docs

- [Best cloud coding agents](https://tryreplicas.com/best-cloud-coding-agents): Compare cloud coding agent platforms by workflow fit, trust, cost, and orchestration model.
- [AI coding agents](https://tryreplicas.com/ai-coding-agents): Learn how AI coding agents differ from autocomplete, chat assistants, and local IDE tools.
- [Background coding agents](https://tryreplicas.com/background-coding-agents): Understand asynchronous delegated coding work and how it relates to cloud workspaces.
- [AI code review agent](https://tryreplicas.com/use-cases/ai-code-review-agent): See how Replicas turns PR reviews, CI failures, and automated checks into follow-up work.
- [Automated code review](https://tryreplicas.com/use-cases/automated-code-review): Learn how automated review findings can become action, not just comments.
- [Workspaces docs](https://docs.tryreplicas.com/features/workspaces/overview): Learn how Replicas workspaces run coding tasks in isolated development environments.
- [GitHub integration](https://docs.tryreplicas.com/features/github): Connect repositories and trigger Replicas from GitHub workflows.
- [Linear integration](https://docs.tryreplicas.com/features/linear): Assign Linear issues to Replicas and turn planned work into pull requests.
- [Slack integration](https://docs.tryreplicas.com/features/slack): Delegate engineering work from Slack conversations.