This guide walks you through creating your first AI coding task on Whim, explaining the key concepts as you go.Documentation Index
Fetch the complete documentation index at: https://docs.whim.run/llms.txt
Use this file to discover all available pages before exploring further.
Prerequisites: A GitHub account and a repository you want to work on.
1. Sign up with GitHub
Go to whim.run and click Start Building. Sign in with GitHub — no credit card required. After signing in, you’ll fill out a short profile (name, email, role) so Whim can tailor your experience.2. Install the GitHub App
Whim uses a GitHub App to clone and push to your repositories.3. Create a workspace
A workspace is your project home in Whim — it maps to a GitHub repository. Pick the repo you want to work on from your list of available repositories. Whim creates the workspace and syncs your code. You can also create a brand-new GitHub repo from this screen if you’re starting fresh.You can have multiple workspaces, each linked to a different repo. Switch between them from the workspace selector.
4. Choose your AI provider
Whim supports multiple AI providers, each running their native CLI inside task containers:| Provider | Description |
|---|---|
| Claude (Anthropic) | Native Claude Code CLI. Use Whim’s built-in compute or bring your own Claude Pro/Team subscription. |
| Codex (OpenAI) | Native Codex CLI. Requires your own OpenAI API key. |
| OpenRouter | Access 10+ models (GPT, Gemini, Grok, DeepSeek, and more) through a single API key. Coming soon for alpha users. |
OpenRouter/CCR is coming soon for alpha users. Today, Whim supports Claude and Codex.
Configure your workspace
After choosing a provider, you can optionally configure:Model and permissions
Model and permissions
Pick a default model (e.g., Claude Opus, Sonnet, GPT-4o) and set the agent’s permission mode — how much autonomy it has over file edits and shell commands.
Instructions
Instructions
Write agent instructions that every task in this workspace will receive — coding standards, project context, or architectural guidelines.
Environment variables, MCP servers, skills, and more
Environment variables, MCP servers, skills, and more
Inject env vars, connect MCP servers for external tools, define reusable skills (slash commands), add plugins, and set init scripts. All optional — you can configure these later.
5. Launch your first task
Now for the exciting part. A task is a single AI agent session running in its own isolated cloud container.Write your prompt
Describe what you want the AI agent to do. Be specific: “Add a dark mode toggle to the settings page” works better than “improve the UI.”
What just happened?
Behind the scenes, Whim:- Provisioned a container — a sandboxed Ubuntu environment on Fly.io, dedicated to this task
- Cloned your repo and checked out a new branch (named
whim-<workspace>-<task-id>) - Injected your configuration — instructions, env vars, MCP servers, skills, and plugins
- Started the AI agent (Claude Code or Codex) with your prompt
- Began streaming the agent’s terminal output to your browser in real time
6. Watch it work
Once launched, you’ll see the agent’s terminal streaming live. You can:- Watch the terminal — see every command and file edit as it happens
- Open additional panes — add a shell terminal, file browser, or live preview
- Send follow-up prompts — guide the agent if it needs course correction
7. Review the results
When the agent finishes, you’ll have:- A git branch with all the changes, ready for review
- A pull request (if the agent created one) linked from the task
- Full conversation history showing the agent’s reasoning and every action
Key concepts recap
| Concept | What it is |
|---|---|
| Workspace | Your project home — linked to a GitHub repo. Contains all tasks, config, and team collaboration. |
| Task | A single AI agent session in its own isolated container with its own git branch. |
| Todo | A planned task in your backlog. Doesn’t run until you launch it — useful for queuing work. |
| Provider | The AI runtime powering your agents (Claude or Codex today; OpenRouter coming soon). |
| Compute Units (CUs) | How Whim measures usage — a blend of container runtime and AI token consumption. Your plan includes a weekly CU allocation. |
Task states
Tasks move through a simple lifecycle:| State | What’s happening |
|---|---|
| Running | The agent is actively working. |
| Waiting | The container is up but the agent is idle or needs input. |
| Sleeping | Container suspended to save CUs. Resumes instantly on interaction. |
| Completed | Work is done. Branch and results are preserved. |
How Agents Work
Deep dive into what runs inside a task container.
Orchestrator Mode
Coordinate multiple agents on complex tasks.

