Google Jules Tutorial: Real Examples & Implementation

Have you ever wished you could just hand off a boring coding task, walk away, and come back to find it done? Google Jules makes that possible. This Google Jules tutorial will walk you through everything from what it is to how to use it with real examples. Jules is an AI coding agent that works directly inside your GitHub repository, completes entire tasks on its own, and delivers a pull request for you to review.

In this tutorial, you will learn what Google Jules is, how to set it up, and how to use it with real examples that are easy to follow even if you are just getting started.

Quick Answer

This Google Jules tutorial covers an autonomous AI coding agent by Google, powered by Gemini 2.5 Pro. You assign it a task in plain English, it creates a plan, you approve it, and it delivers a finished pull request. It is free to use at jules.google.com.

What Is Google Jules

If you have been searching for a Google Jules tutorial to understand what this tool actually does, here is the short answer. Google Jules is an autonomous AI coding agent built by Google and powered by Gemini 2.5 Pro. You go to jules.google.com, connect your GitHub repository, describe a task in plain English, and Jules handles it entirely on its own inside a secure cloud environment. When it is done, it creates a pull request on GitHub for you to review and merge. You are never locked out of the process, but you also never have to do the execution yourself.

Think of it like hiring a driver instead of using GPS. You tell them the destination, sit back, and they handle the route. The destination is still your call. The execution is theirs.

Here is something to think about: what are the three coding tasks you keep pushing to the bottom of your to-do list? Keep those in mind as you go through this tutorial.

Do check out HCL GUVI’s Artificial Intelligence and Machine Learning Course if you want to move beyond tutorials like Google Jules and learn how real AI systems are built and deployed. The course helps you understand core concepts such as machine learning workflows, model training, and practical AI implementation through hands-on projects and structured learning.

How Google Jules Works

Jules is not a chat tool or a line by line suggestion engine. It is a full task agent that follows a clear internal process every time you assign it work. Understanding this process helps you use Jules more effectively and know exactly what to expect at each stage.

1. The Asynchronous Working Model

Google Jules works asynchronously, meaning it does not need you to stay in the conversation while it runs. You assign a task, close the tab, and come back when Jules is done. When you submit a task, Jules spins up a secure Google Cloud virtual machine, clones your repository, reads every file, makes the changes, and creates a pull request. No babysitting required.

• Asynchronous means Google Jules works in the background while you focus on something else entirely
• Virtual machine means your local files are never touched or at risk during the process
• Pull request means you always review and approve before anything gets merged into your code
• Notification tells you when Jules is done so you can come back and review at your own pace

2. How Google Jules Reads Your Code

Google Jules does not just look at the one file you mention. It clones your entire GitHub repository, reads your folder structure, checks your dependencies, and understands your naming conventions before writing a single line. It also looks for a file called AGENTS.md in the root of your repository. If you create this file and describe your project, key folders, and coding conventions, Jules uses it as a reference every single time.

• Full repository scan means Jules sees the big picture, not just the one file you mention
• AGENTS.md is your way of giving Jules a project briefing upfront
• Dependency awareness means Jules knows what libraries and versions your project uses
• Convention following means Jules writes code that actually fits your existing style

3. The Plan and Approve Workflow

Before Google Jules changes anything, it shows you a detailed plan. This is the most important feature for beginners because it means you are always in control. Jules never makes changes to your codebase without your knowledge. After you submit a task, Jules generates a step by step breakdown of what it intends to do, which files it will change, and what logic it will apply. You read it, adjust it, and only then approve.

• Plan generation happens before any code is written, not after
• Feedback loop lets you course correct Jules before it starts executing
• Approval gate means you have full control over what actually gets executed
• Pull request delivery is how Jules hands you the finished work for your final review

4. How Google Jules Delivers the Final Output

Once Google Jules finishes executing the plan, it packages all the changes into a GitHub pull request and notifies you. The pull request includes every file that was modified, a summary of what changed, and the reasoning behind the changes. You open it exactly like any other pull request, review the diff, leave comments if needed, and merge when you are satisfied.

• Pull request creation is automatic once Jules finishes executing the approved plan
• Change summary tells you what Jules did and why, so reviewing is fast and clear
• Diff view shows every line that was added, changed, or removed across all files
• Merge control always stays with you, Jules cannot push to your main branch on its own

How to Set Up Google Jules

Setting up Google Jules takes under ten minutes and needs nothing more than a Google account and a GitHub repository. There is no software to install. Jules runs entirely in your browser at jules.google.com and works the same on Windows, Mac, and Linux.

The setup has three stages: creating your account, connecting your GitHub repository, and writing your first task. Once you do it once, every future task takes under a minute to kick off.

1. Creating Your Account and Connecting GitHub

Go to jules.google.com and sign in with your Google account. You land on the Jules dashboard, which is clean and minimal by design. From there, click Connect Repository and authorize Jules to access your GitHub. You can choose to give access to all repositories or only specific ones.

• Google sign in is all you need, no new account to create
• GitHub OAuth is how Jules gets access to clone your repositories
• Selective access lets you limit Jules to only the repos you want
• Dashboard view is where all your tasks and their statuses appear

2. Writing a Strong Task Prompt

The quality of Google Jules output depends directly on the quality of your prompt. You do not need to write paragraphs, but you do need to be specific. A weak prompt: fix the login bug. A strong prompt: the login function in auth.js throws a TypeError when the email field is left empty. Fix the validation to handle empty strings and null values before the API call, and show an error message for both cases.

• File name tells Jules exactly where to look in your project
• Error description gives Jules the exact problem to solve
• Expected outcome tells Jules what done actually looks like
• Scenario context helps Jules reproduce the issue in its environment

3. Reviewing the Plan

Once you submit your prompt, Google Jules reads your code and returns a plan within seconds or a few minutes depending on complexity. Read it. This is not a step to skip. If something looks off, type your feedback inline. Jules revises the plan before starting. Only approve when you are genuinely satisfied.

• Plan review is your first line of defense against unwanted changes
• Inline feedback lets you redirect Jules without starting the task over
• Approval button is what actually triggers Jules to begin writing code
• Revision cycles are built in because Jules expects you to push back if needed

4. Reviewing and Merging the Pull Request

When Google Jules finishes, it creates a GitHub pull request with all changes organized and labeled. Open it, check the diff, run your tests, leave comments, and merge when you are satisfied. Jules never pushes directly to your main branch. That step always stays with you.

• Pull request format means changes go through your team’s normal review process
• Diff view shows you exactly what lines were added, changed, or removed
• Merge control stays with you, Jules cannot merge its own pull requests
• Comment support means you can leave feedback on specific lines just like any code review

Think about this: how much time do you spend every week on tasks that follow a predictable, repeatable pattern? Those are exactly the tasks Jules was designed to take off your plate.

What Can You Do With Google Jules in Real Projects

Understanding Jules in theory is one thing. Seeing it applied to real scenarios is what makes it click. Each example below includes the kind of prompt you would actually write and what Jules does with it.

1. Fixing a Bug Across Multiple Files

You updated your Node.js project to version 20 and JWT authentication broke. The error spans three files because the auth logic is split across a middleware file, a user controller, and a route handler. Your prompt: after updating to Node.js 20 the JWT token verification throws an invalid signature error. The issue is likely in the auth middleware and the token generation inside userController.js. Fix the token handling to be compatible with Node.js 20 and make sure all three related files are consistent.

• Multi-file awareness means Jules traces the issue across your whole repository, not just one file
• Version research means Jules checks what actually changed in Node.js 20 before writing a fix
• Consistency check means Jules ensures the fix works end to end across every file it touches
• Time saved on a task like this is typically two to four hours of manual debugging

2. Writing Unit Tests for Existing Functions

Writing tests is one of those tasks every developer knows is important but keeps skipping. Jules is strong at this because it reads your actual functions and writes tests that reflect real logic, not generic boilerplate. Your prompt: write unit tests for all functions in the payments folder using Jest. Cover the main success case and at least three edge cases per function including empty inputs, null values, and invalid types.

• Function reading means Jules understands what each function actually does before writing any test
• Edge case coverage means the tests go beyond the happy path and cover real failure scenarios
• Framework matching means Jules uses the testing library you already have installed
• Test file placement follows the folder conventions already in your project

3. Upgrading a Library to a New Version

Dependency updates are painful. You need to find every place the old API is used, understand what changed in the new version, rewrite each usage, and make sure nothing breaks. Jules handles this entire chain. Your prompt: upgrade axios from version 0.27 to version 1.6. Update all API calls in the services folder to use the new syntax and make sure the error handling matches the updated error format in version 1.6.

• Old API detection means Jules finds every usage of the deprecated syntax in your project
• Changelog awareness means Jules checks what actually changed between the two versions
• Rewrite accuracy means each usage is updated to correctly match the new pattern
• Test validation means Jules runs your existing tests to confirm nothing broke after the update

Can You Use Google Jules From the Terminal

Yes, Jules is not limited to the browser. Google released Jules Tools, a command line interface that lets you assign and manage Jules tasks directly from your terminal. To install it, run npm install -g @google/jules-tools in your terminal. Once installed, you get a set of commands that connect to the same Jules backend as the browser.

Core CLI Commands

Run jules remote list to see all connected repositories. Run jules remote new to create a new task. Run jules remote status to check what Jules is currently working on. A full task creation looks like this: jules remote new –repo yourusername/yourrepo –session “write unit tests for the auth module” and Jules begins immediately.

• jules remote list shows all repositories Jules currently has access to
• jules remote new creates a new task with a repository and your prompt
• jules remote status shows the current state of every active task
• GitHub issue piping lets you feed open issues directly to Jules as tasks

If you are also exploring other AI coding tools, check out our guide on AutoGen Tutorial to see how these tools compare and complement Jules in a modern AI development workflow.

Tips for Getting Better Results With Jules

• Be specific in every prompt: Include the file name, function name, the exact error message, and what done looks like. Vague prompts produce vague plans.
• Start with small tasks: Your first Jules tasks should be contained and clear. One bugfix, one test file, one dependency update. Build confidence before going bigger.
• Create an AGENTS.md file: Place it in your repository root and describe your project structure, key folders, and coding conventions. Jules reads it every time.
• Always read the plan: Before approving, spend 60 seconds reading what Jules intends to do. This is your most important checkpoint.
• Use Jules for backlog tasks: Tests, documentation, linting fixes, dependency updates. These low-priority tasks that pile up are exactly where Jules saves the most time.
• Push back on the plan: If something looks off, give feedback before approving. Jules revises well and expects you to correct it.

Conclusion

This Google Jules tutorial has shown you that Jules is not another AI tool that sits beside you making suggestions. It is an autonomous coding agent that takes real tasks off your plate, shows you a plan you can review, and delivers finished code through a pull request you control. The workflow is simple: write a clear prompt, review the plan, approve it, and return to a completed pull request.

The best way to make this real is to open jules.google.com right now, connect one repository, and assign one small task. A test file you have been avoiding, a dependency update sitting in your backlog, a bug you understand well. Go through the full loop once and everything in this tutorial will click into place.

FAQs

1. Is this Google Jules tutorial relevant for beginners or only experienced developers?

This Google Jules tutorial is written for complete beginners but works equally well for experienced developers. Jules itself is free to use as of early 2026 with usage limits on the free tier, generous enough for individuals and small projects to get real value.

2. Does Jules push code directly to my main branch?

No. Jules always creates a pull request and never pushes directly to any branch. You review the changes exactly as you would with any team member and merge only when satisfied.

3. What programming languages does Jules support?

Jules supports Python, JavaScript, TypeScript, Java, Go, Ruby, and more. Its strongest support is for JavaScript and TypeScript ecosystems including Node.js and popular frontend frameworks.

4. How is Jules different from GitHub Copilot? 

Copilot works inline as you type and suggests completions in real time. Jules works asynchronously on complete tasks while you do something else entirely. They serve different purposes and many developers use both.

5. Can Jules access my private GitHub repositories?

Yes. Jules accesses private repositories through standard GitHub OAuth authorization. You choose which repositories Jules can see during setup and you can revoke access anytime from your GitHub settings.