Background coding agents

A background coding agent is an AI coding agent that continues working after a developer delegates a task. It can inspect a repository, run commands, edit files, run tests, and return output without requiring the developer to keep an editor session open.

Background does not mean unsupervised. The useful version of the workflow keeps humans in the loop through session visibility, comments, CI results, file diffs, and pull request review.

Background agents are strongest when the task has enough context to start, a clear definition of done, and a reviewable output.

Small implementation tasks

UI fixes, product tweaks, integration changes, and backlog items that can be scoped from an issue or prompt.

Follow-up work

Review comments, failing CI checks, static analysis findings, and cleanup tasks that already identify the problem.

Long-running verification

E2E test runs, flaky test investigation, dependency checks, or setup validation that benefits from isolated compute.

Investigation tasks

Reproducing a bug, tracing a failure, summarizing affected files, or returning notes when a code change is not the right output.

Background work needs somewhere to run. A cloud workspace gives the agent a repository checkout, terminal, files, environment variables, and enough compute to continue while a developer is elsewhere.

That is why background and cloud are closely related. Cloud describes the runtime. Background describes the delegation model.

• The task can continue while a laptop is closed.
• Multiple agents can work in parallel on separate branches.
• Commands, test logs, files, and final outputs remain inspectable.
• Teams can standardize environment setup instead of relying on every developer machine.

Replicas focuses on running familiar coding agent harnesses in cloud workspaces. Teams that already trust Claude Code, Codex, Cursor, or Opencode can use those workflows without moving every task back to a local machine.

The platform is also designed around workflow entry points: GitHub, Linear, Slack, the dashboard, and automation loops that react to CI and review feedback.

Trusted harnesses

Use the coding agents engineers already understand instead of forcing every team into a single proprietary agent experience.

Bring your own inference path

Where the underlying agent supports it, teams can use existing subscriptions, API keys, credits, or enterprise agreements.

Reviewable sessions

Inspect the workspace, commands, file changes, test results, and final output before deciding what ships.

Automation-ready

Turn repeated engineering signals into delegated work instead of one-off chat prompts.

A useful evaluation is less about a single demo and more about whether the platform can safely absorb recurring engineering work.

• Can it run in isolated cloud workspaces?
• Can humans inspect and steer work while it is running?
• Can it return outputs beyond pull requests, such as test logs or investigation notes?
• Can it start from GitHub, Linear, Slack, or automation triggers?
• Can your team control model access, credentials, and repository permissions?

• Cloud coding agents

  Learn the broader cloud runtime category for delegated software engineering work.

• AI coding agents

  Understand how coding agents differ from autocomplete and chat-based coding assistants.

• Best cloud coding agents

  Compare cloud coding agent platforms by workflow fit and team needs.