Isolation isn't enough. AI coding agents need real dev environments.

Spin up safe, ephemeral workspaces designed for coding, not just containment—with everything coding agents and developers need to do real work together.

Bring your favorite coding agents
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The challenge

You can’t scale what you can’t control

No safe place to work

Agents can break local environments, leak credentials, or access things they shouldn’t.

No way to scale consistently

You can’t efficiently or consistently spin up bespoke infrastructure for every agent.

No control of costs

Left unchecked, agents can burn through tokens, compute, and time.

Meet Coder

Safely deploy AI coding agents at enterprise scale

Isolated and self-hosted

Every agent runs inside its own ephemeral workspace with access controls, secrets management, and logging—on your infra.

Infrastructure as code

Quickly provision thousands of agent-optimized environments with Terraform, across any cloud or on-prem infrastructure.

Governance and cost guardrails

Set resource quotas, enable workspace logging, and restrict what agents can see or do relative to their human partners in development.

It felt like pair-programming with a junior engineer who can execute directions 100x faster than a human.Check out our agentic AI experiments
Features

Boundaries, context, and oversight for every stage of development

Flexible workspace boundaries for AI

Tighten what tools, code, and permissions your AI agents have in Coder workspaces relative to their human peers. It’s all tracked, reproducible, and designed for enterprise-scale oversight and governance.

Rectangular prism with the Claude logo, enclosed within a larger rectangular prism

Context and collaboration, built in

Provide agents the context they need to be useful. Connected to GitHub, running in real dev environments, and integrated into developer IDEs, agents get the structure to contribute like teammates—not just isolated tools.

One-to-many mapping showing Coder's connections to Cursor, Backstage, GitHub, and VS Code

Workflows developers already know

Working with AI agents should feel like working with another developer. Assign tasks to agents in GitHub, deliver feedback via pull requests, and get notified when agents are stuck and need help.

Series of 3 GitHub comments. First, by @bpmct, posted 4 hours ago: `Let’s fix the horizontal scroll issue when users visit this page on mobile...`. Second, by @sreya, posted now: `@coder start working on this`. Third, by @coder: `Starting a Coder workspace. You can track the progress here.`

Human in the loop with every task

Give your developers a single comprehensive view of their active agents, the tasks they’re solving, feedback they’re awaiting, and how much time and budget they’re spending.

Series of 3 AI agent tasks. First task, given to Claude, is labeled `Add Unit Test for API`. Its last log entry says `10s ago: Identify target API endpoint...`. Status: Agent Working. Second task, given to OpenAI, is labeled `Update Dependencies`. Its last log entry says `55s ago: Scanning for outdated packages...`. Status: Agent Working. Third task, given to Claude, is labeled `Fix Mobile Layout Bug`. Its last log entry says `16m ago: Preview ready...`. Status: `Needs Feedback`
AI coding agents in action

Further reading

Agentic AI and Coder shaking hands

Blog: Why Coder was always built for agentic AI

Coder isn’t chasing the agentic AI wave. We built the foundation for it. Learn how Coder is a natural fit for adopting AI agents at scale.

Read more
Coder, Claude, and GitHub logos with dashed lines connecting each other

Blog: We gave Claude Code real GitHub issues

We like to tinker, too. Check out what happened and what we learned when we gave Claude real Coder backlog issues.

Read more
Next steps

Explore how Coder helps you deploy AI coding agents at scale

Frequently asked questions

AI coding agents in Coder perform development tasks—like writing code, fixing bugs, or updating dependencies—inside secure, ephemeral workspaces.
Unlike Copilot, which augments a developer in their IDE, Coder's agents work independently to complete assigned tasks, generate pull requests, and request feedback—more like a teammate than a tool.
You can prompt them to pick up backlog issues, make code changes, test them, and open pull requests with minimal human input, all inside a secure workspace. They're ideal for smaller tasks so developers can focus on solving more meaningful problems.
Yes. Agents run in isolated, ephemeral workspaces with tightly controlled permissions, logging, and no default access to sensitive data.
Yes. You can bring your own model or agent framework and run it inside Coder workspaces with custom tooling, languages, and access policies.
You just need to provision a workspace template with your preferred model and agent logic—Coder handles the environment and provisioning.
Absolutely. You can define what files, commands, networks, and secrets an agent can access, separately from what human users can do.
Well-scoped, repetitive, or boilerplate-heavy tasks like dependency updates, bug fixes, and simple feature changes are great first candidates.