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docs(docs/ai-coder): replace Coder Tasks references with Coder Agents (#24929)
Updates `docs/ai-coder/index.md`, `docs/ai-coder/best-practices.md`, and `docs/ai-coder/ai-governance.md` to point readers at Coder Agents and the AI Governance Add-On instead of Coder Tasks and Agent Firewall (CODAGT-157). ## Changes - `docs/ai-coder/index.md`: - Rename `## Agents with Coder Tasks` to `## Coder Agents`. Drop the Devin / ChatGPT Codex name-drops and the Tasks pitch. New copy points at `./agents/index.md`, names the agent loop in the control plane, and notes that workspaces can be completely network isolated. Image swapped from `tasks-ui.png` to `agents-hero-image.png` (the hero shot added in #24915). - Replace the `## Secure Your Workflows with Agent Firewall` section with `## Govern AI activity with the AI Governance Add-On`. The new section opens with adoption-first framing (visibility, guardrails, cost) and links to `./ai-governance.md`, with bulleted callouts for AI Gateway, Agent Firewall, and the expanded Agent Workspace Build allowance the add-on bundles. - `docs/ai-coder/best-practices.md`: - In the use-case table, swap `[Tasks](./tasks.md)` to `[Coder Agents](./agents/index.md)` for the developer-led-investigation and prototyping rows, and swap the "Tasks API *(in development)*" cell to `[Coder Agents API](./agents/chats-api.md)` for the background-jobs row. Retitle the Security section link from "securing agents with Coder Tasks" to "securing AI agents" since `security.md` does not actually mention Tasks. Re-ran `markdown-table-formatter` to repad column widths. - In `## Provide Agents with Proper Context`, add a paragraph describing how context is provided in Coder Agents (admin-configured system prompts, centrally registered MCP servers, and skills shipped from repos or templates under `.agents/skills/`), with a transition line clarifying that the existing Memory and Tools subsections cover BYO-agent patterns. - `docs/ai-coder/ai-governance.md`: drop the "Additional Tasks Use (via Agent Workspace Builds)" bullet from the intro feature list and the "Expanding the use of Coder Tasks for AI-driven background work" bullet from the audience list. The `## How Coder Tasks usage is measured` section and the rest of the Tasks-related prose on this page are intentionally left for a follow-up PR. ## Notes for the reviewer - The `[Coder Agents API](./agents/chats-api.md)` link in `best-practices.md` will need to be retargeted if #24830 (which replaces `agents/chats-api.md` with auto-generated `reference/api/chats.md`) lands first. - This is the first slice of the Tasks-references audit. Remaining files (`tasks-core-principles.md`, `tasks-lifecycle.md`, `tasks-migration.md`, `cli.md`, `github-to-tasks.md`, `agent-compatibility.md`, the rest of `ai-governance.md`, `custom-agents.md`, `ai-gateway/clients/claude-code.md`, `manifest.json`, `reference/api/tasks.md`, the `task*` CLI references, the ESR upgrade guide, `feature-stages.md`, `workspace-scheduling.md`, `shared-workspaces.md`) will land in follow-up PRs against the same Linear ticket. Open PRs #24831, #24833, and #24841 cover separate slices and do not touch any file in this PR. - Validation: `markdownlint-cli2`, `markdown-table-formatter`, `scripts/check_emdash.sh`, and `make pre-commit-light` all pass. PR generated with Coder Agents.
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@@ -14,9 +14,6 @@ that help organizations safely roll out AI tooling at scale:
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MCP server management, and policy enforcement
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- [Agent Firewall](./agent-firewall/index.md): Process-level firewalls for
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agents, restricting which domains can be accessed by AI agents
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- [Additional Tasks Use (via Agent Workspace Builds)](#how-coder-tasks-usage-is-measured):
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Additional allowance of Agent Workspace Builds for continued use of Coder
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Tasks.
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## Who should use the AI Governance Add-On
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@@ -30,7 +27,6 @@ It's a good fit if you're:
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- Looking to centrally observe, audit, and govern AI activity in Coder
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Workspaces
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- Managing AI workflows against sensitive or regulated codebases
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- Expanding the use of Coder Tasks for AI-driven background work
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If you already use other AI Governance tools, such as third-party LLM gateways
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or vendor-managed policies, you can continue using them. Coder Workspaces can
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@@ -8,18 +8,22 @@ To successfully implement AI coding agents, identify 3-5 practical use cases whe
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Below are common scenarios where AI coding agents provide the most impact, along with the right tools for each use case:
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| Scenario | Description | Examples | Tools |
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|------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|
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| **Automating actions in the IDE** | Supplement tedious development with agents | Small refactors, generating unit tests, writing inline documentation, code search and navigation | [IDE Agents](./ide-agents.md) in Workspaces |
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| **Developer-led investigation and setup** | Developers delegate research and initial implementation to AI, then take over in their preferred IDE to complete the work | Bug triage and analysis, exploring technical approaches, understanding legacy code, creating starter implementations | [Tasks](./tasks.md), to a full IDE with [Workspaces](../user-guides/workspace-access/index.md) |
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| **Prototyping & Business Applications** | User-friendly interface for engineers and non-technical users to build and prototype within new or existing codebases | Creating dashboards, building simple web apps, data analysis workflows, proof-of-concept development | [Tasks](./tasks.md) |
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| **Full background jobs & long-running agents** | Agents that run independently without user interaction for extended periods of time | Automated code reviews, scheduled data processing, continuous integration tasks, monitoring and alerting | [Tasks](./tasks.md) API *(in development)* |
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| **External agents and chat clients** | External AI agents and chat clients that need access to Coder workspaces for development environments and code sandboxing | ChatGPT, Claude Desktop, custom enterprise agents running tests, performing development tasks, code analysis | [MCP Server](./mcp-server.md) |
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| Scenario | Description | Examples | Tools |
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|------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|
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| **Automating actions in the IDE** | Supplement tedious development with agents | Small refactors, generating unit tests, writing inline documentation, code search and navigation | [IDE Agents](./ide-agents.md) in Workspaces |
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| **Developer-led investigation and setup** | Developers delegate research and initial implementation to AI, then take over in their preferred IDE to complete the work | Bug triage and analysis, exploring technical approaches, understanding legacy code, creating starter implementations | [Coder Agents](./agents/index.md), to a full IDE with [Workspaces](../user-guides/workspace-access/index.md) |
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| **Prototyping & Business Applications** | User-friendly interface for engineers and non-technical users to build and prototype within new or existing codebases | Creating dashboards, building simple web apps, data analysis workflows, proof-of-concept development | [Coder Agents](./agents/index.md) |
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| **Full background jobs & long-running agents** | Agents that run independently without user interaction for extended periods of time | Automated code reviews, scheduled data processing, continuous integration tasks, monitoring and alerting | [Coder Agents API](./agents/chats-api.md) |
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| **External agents and chat clients** | External AI agents and chat clients that need access to Coder workspaces for development environments and code sandboxing | ChatGPT, Claude Desktop, custom enterprise agents running tests, performing development tasks, code analysis | [MCP Server](./mcp-server.md) |
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## Provide Agents with Proper Context
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While LLMs are trained on general knowledge, it's important to provide additional context to help agents understand your codebase and organization.
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For [Coder Agents](./agents/index.md), context comes from a few complementary places. Platform admins configure a [system prompt](./agents/platform-controls/index.md) that applies to every chat and register [MCP servers](./agents/platform-controls/mcp-servers.md) once for the whole deployment. Repos and workspace templates can ship reusable [skills](./agents/extending-agents.md) under `.agents/skills/`, which the agent discovers automatically when it attaches to the workspace. Developers don't need to manage memory files or wire up tools themselves.
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The rest of this section covers patterns for agents you run yourself inside a workspace, such as Claude Code or Codex.
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### Memory
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Coding Agents like Claude Code often refer to a [memory file](https://docs.anthropic.com/en/docs/claude-code/memory) in order to gain context about your repository or organization.
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@@ -46,7 +50,7 @@ In internal testing, we have seen significant improvements in agent performance
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LLMs and agents can be dangerous if not run with proper boundaries. Be sure not to give agents full permissions on behalf of a user, and instead use separate identities with limited scope whenever interacting autonomously.
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[Learn more about securing agents with Coder Tasks](./security.md)
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[Learn more about securing AI agents](./security.md)
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## Keep it Simple
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+32
-24
@@ -14,35 +14,43 @@ for agents such as GitHub Copilot and Roo Code.
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These agents work well inside existing Coder workspaces as they can simply be
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enabled via an extension or are built-into the editor.
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## Agents with Coder Tasks
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## Coder Agents
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In cases where the IDE is secondary, such as prototyping or long-running
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background jobs, agents like Claude Code or Aider are better for the job and new
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SaaS interfaces like [Devin](https://devin.ai) and
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[ChatGPT Codex](https://openai.com/index/introducing-codex/) are emerging.
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In cases where the IDE is secondary, such as prototyping, research, or
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long-running background jobs, [Coder Agents](./agents/index.md) is the
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recommended way to delegate development work to coding agents in your Coder
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deployment.
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[Coder Tasks](./tasks.md) is an interface inside Coder to run and manage coding
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agents with a chat-based UI. Unlike SaaS-based products, Coder Tasks is
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self-hosted (included in your Coder deployment) and allows you to run any
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terminal-based agent such as Claude Code or Codex's Open Source CLI.
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Coder Agents is a native AI coding agent built into Coder. The agent loop runs
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in the Coder control plane on your infrastructure rather than inside the
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workspace, so workspaces can be completely network isolated. Developers
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interact with agents through the web UI, the CLI (`coder agents`), or the
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REST API.
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[Learn more about Coder Tasks](./tasks.md) for best practices and how to get
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started.
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[Learn more about Coder Agents](./agents/index.md) for architecture details,
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supported LLM providers, and how to get started.
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## Secure Your Workflows with Agent Firewall
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## Govern AI activity with the AI Governance Add-On
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AI agents can be powerful teammates, but must be treated as untrusted and
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unpredictable interns as opposed to tools. Without the right controls, they can
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go rogue.
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AI coding tools are quickly becoming core to how engineering teams ship
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software. As adoption grows, platform teams want a clear picture of how AI is
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being used, consistent guardrails across teams, and predictable cost controls
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so they can confidently scale AI tooling to the whole organization.
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[Agent Firewall](./agent-firewall/index.md) is a new tool that offers
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process-level safeguards that detect and prevent destructive actions. Unlike
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traditional mitigation methods like firewalls, service meshes, and RBAC systems,
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Agent Firewall is an agent-aware, centralized control point that can either be
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embedded in the same secure Coder Workspaces that enterprises already trust, or
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used through an open source CLI.
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The [AI Governance Add-On](./ai-governance.md) is a per-user license that adds
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observability, management, and policy controls for AI tooling across your
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Coder deployment. It includes:
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To learn more about features, implementation details, and how to get started,
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check out the [Agent Firewall documentation](./agent-firewall/index.md).
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- [AI Gateway](./ai-gateway/index.md) for centralized authentication, audit
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trails of prompts and tool invocations, and policy enforcement against
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upstream LLM providers.
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- [Agent Firewall](./agent-firewall/index.md) for process-level network and
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command policies that restrict what agents can reach and do inside a
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workspace.
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- Expanded Agent Workspace Build allowances for teams running AI-driven
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background work at scale.
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[Learn more about the AI Governance Add-On](./ai-governance.md) for use cases,
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entitlements, and how to enable it in your deployment.
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