Google Jules AI: Complete Guide & How to Use It (2026)
Everything you need to know about Google's AI coding assistant
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Google Jules AI: Complete Guide & How to Use It in 2026
Google Jules is Google's AI-powered coding assistant designed to handle asynchronous coding tasks like bug fixes, dependency updates, and test writing directly inside your GitHub workflow. Unlike inline copilots that suggest code as you type, Jules operates as an autonomous agent that takes a GitHub issue, creates a plan, writes code on a virtual machine, and delivers a ready-to-review pull request.
This guide covers everything you need to know about Jules in 2026: what it does, how to set it up, its pricing, and how it compares to alternatives like GitHub Copilot, Cursor, and Claude Code.
What Is Google Jules?
Jules is built on Google's Gemini 2.5 Pro model and runs inside a sandboxed cloud environment. When you assign a task to Jules, it:
- Reads the relevant codebase and issue context
- Creates a step-by-step plan for you to review
- Executes the plan on a cloud VM with a full development environment
- Generates a diff or pull request with the changes
- Waits for your review before merging
Jules integrates natively with GitHub. You trigger it from the Jules dashboard or directly from GitHub issues using labels or commands.
Key Features
| Feature | Description |
|---|---|
| Asynchronous tasks | Handles work in the background while you focus on other things |
| GitHub integration | Creates branches, commits, and pull requests automatically |
| Multi-file editing | Understands and modifies multiple files across a repository |
| Plan review | Shows you a plan before making changes so you stay in control |
| Gemini 2.5 Pro | Powered by Google's most capable reasoning model |
| Sandboxed execution | Runs code in isolated VMs for security |
| Dependency updates | Automates package upgrades and migration tasks |
How to Set Up Google Jules
Step 1: Access Jules
Navigate to the Jules platform at jules.google.com and sign in with your Google account. Jules is available to users with a Google One AI Premium plan or through Google Cloud.
Step 2: Connect Your GitHub Repository
- Click Connect Repository in the Jules dashboard.
- Authorize the Jules GitHub App when prompted.
- Select the repositories you want Jules to access.
- Jules will index your codebase to understand the project structure.
Step 3: Assign Your First Task
You can assign tasks to Jules in two ways:
From the Jules Dashboard:
- Click New Task.
- Select the repository and describe what you want done.
- Review the plan Jules generates.
- Click Execute to let Jules write the code.
From GitHub Issues:
- Add the
juleslabel to any GitHub issue. - Jules picks up the issue, reads the description, and creates a plan.
- Review the plan in the Jules dashboard or GitHub comment.
- Approve to generate a pull request.
Step 4: Review and Merge
Once Jules finishes, it opens a pull request with:
- A clear description of all changes made
- Inline comments explaining non-obvious modifications
- Test results if the project has CI configured
Review the PR as you would any human-authored code, then merge.
Jules Pricing in 2026
| Plan | Price | Tasks/Month | Best For |
|---|---|---|---|
| Free | $0 | 5 tasks | Trying it out |
| Google One AI Premium | $19.99/mo | Included with subscription | Individual developers |
| Google Cloud | Usage-based | Pay per task | Teams and enterprises |
The free tier gives you five tasks per month, which is enough to evaluate the tool. Power users will want the Google One AI Premium subscription or a Google Cloud billing account for unlimited usage.
Code Example: Triggering Jules via GitHub
You can also interact with Jules programmatically. Here is an example of creating an issue that Jules will automatically pick up:
# Create a GitHub issue with the jules label
gh issue create \
--title "Update axios to v2.x and fix breaking changes" \
--body "Upgrade axios from v1.7 to v2.x across the project. Fix any breaking API changes in the HTTP client layer." \
--label "jules"
Jules will read the issue, analyze the dependency tree, and produce a pull request with all necessary changes.
Google Jules vs. Alternatives
| Feature | Google Jules | GitHub Copilot | Cursor AI | Claude Code |
|---|---|---|---|---|
| Type | Async agent | Inline copilot + agent | IDE with AI | CLI agent |
| Model | Gemini 2.5 Pro | GPT-4o / Claude | Multiple | Claude Sonnet/Opus |
| GitHub PR creation | Native | Via Copilot Workspace | Manual | Manual |
| Works offline | No | No | With local models | With local models |
| Multi-file edits | Yes | Yes | Yes | Yes |
| Plan before execute | Yes | Yes (Workspace) | No | Yes |
| Free tier | 5 tasks/mo | Limited | 50 requests/mo | Limited |
| Best for | Async bug fixes, upgrades | Real-time coding | Interactive development | Terminal-based development |
When to Use Jules
Jules excels at well-defined, self-contained tasks where you can describe the problem clearly and walk away. Examples include:
- Fixing a specific bug reported in a GitHub issue
- Upgrading a dependency across the codebase
- Adding unit tests for existing functions
- Refactoring code to follow a style guide
- Migrating from one API version to another
When to Use Something Else
For interactive development where you are actively writing new features and need real-time suggestions, tools like Cursor or GitHub Copilot are more appropriate. For complex architectural decisions that require conversation and iteration, Claude Code or a chat-based assistant is a better fit.
Tips for Getting the Best Results from Jules
Write clear issue descriptions. Jules performs best when the task is well-defined. Include the expected behavior, current behavior, and relevant file paths.
Keep tasks focused. Instead of "refactor the entire auth system," break it into smaller issues like "extract JWT validation into a utility function."
Provide context in the issue body. Mention specific files, function names, or error messages. The more context Jules has, the better its plan will be.
Review the plan carefully. Jules shows you its plan before executing. If the plan looks wrong, edit it or provide feedback rather than letting it run.
Use CI checks. If your repository has automated tests and linting, Jules will run them and fix failures before submitting the PR.
Frequently Asked Questions
Is Google Jules free? Yes, there is a free tier with 5 tasks per month. For heavier usage, you need a Google One AI Premium subscription or Google Cloud billing.
Does Jules work with private repositories? Yes, Jules supports private GitHub repositories. Your code is processed in isolated sandboxed environments and is not used to train models.
What languages does Jules support? Jules supports all major programming languages including Python, JavaScript, TypeScript, Java, Go, Rust, C++, and more. It performs best on languages well-represented in Gemini's training data.
Can Jules run tests? Yes, Jules can run your project's existing test suite in its sandboxed VM. If tests fail after its changes, it will attempt to fix them before submitting the PR.
How does Jules compare to Devin? Both are autonomous coding agents, but Jules is tightly integrated with GitHub and powered by Gemini. Devin operates as a more general-purpose software engineer with its own IDE and browser environment.
Wrapping Up
Google Jules represents a shift toward asynchronous AI development, where you assign tasks and review results rather than pair-programming with an AI in real time. For teams that manage large codebases with frequent bug fixes, dependency updates, and maintenance tasks, Jules can save significant developer time.
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