Overview
Hey everyone 👋
If you've been following the AI coding tools space lately, you've probably noticed things are getting wild. We went from "whoa, AI can autocomplete my code!" to "wait, AI can literally build entire features while I grab coffee?" in what feels like about five minutes.
Today I want to talk about two tools that represent this evolution: GitHub Copilot and Google Antigravity. I've used both extensively, and after recently completing a major refactoring project with Antigravity (which I wrote about here), I have some thoughts on how they compare and why one has completely changed how I work.
Spoiler alert: I'm firmly in Team Antigravity now, but it's not because Copilot is bad, it's because they're solving fundamentally different problems. Let me break it down.
Let's start! 🤙
The Fundamental Difference: Assistant vs. Agent 🤔
Before we get into features and comparisons, let's establish what we're actually talking about here, because calling both of these "AI coding tools" is like calling a bicycle and a self-driving car both "transportation."
GitHub Copilot: Your Smart Coding Assistant
Think of Copilot as the world's most capable autocomplete system. It's like having a really talented developer sitting next to you who can predict what you're about to type and suggest completions. It watches what you're doing, understands the context of your code, and offers suggestions in real-time.
The workflow looks like this:
- You start typing a function
- Copilot suggests how to complete it
- You press Tab to accept (or keep typing to ignore)
- Repeat
It's reactive, it's fast, and it's incredibly good at what it does. Copilot accelerates your existing workflow without fundamentally changing it. You're still the one driving, Copilot just makes the driving smoother and faster.
Google Antigravity: Your Autonomous Development Partner
Antigravity is completely different. It's not trying to predict your next line of code, it's trying to handle entire tasks for you. You don't give it hints about what to write; you give it goals about what to achieve.
The workflow looks like this:
- You describe a task: "Refactor all string utilities to use modern ES6 syntax"
- The agent creates a plan breaking down the task into steps
- You review and approve the plan
- The agent executes: editing multiple files, updating tests, running validations
- You review the results and provide feedback
- The agent iterates until the task is complete
This is proactive autonomy. You're not coding line-by-line anymore, you're architecting solutions and delegating implementation to AI agents. It's less "pair programming" and more "managing a really fast junior developer."
The key insight: Copilot makes you code faster. Antigravity makes you code less. These are fundamentally different value propositions.
Breaking Down the Key Differences 💡
Let's get into the specifics of how these tools differ across various dimensions.
1. Autonomy Level
Copilot: reactive autonomy. It suggests code based on what you're actively working on, but you make all the decisions. Every suggestion requires your approval (via Tab). It never makes changes without explicit confirmation.
Antigravity: proactive autonomy. Agents can work independently on tasks, making decisions about file edits, command execution, and implementation approach. You set the goal; the agent figures out how to achieve it. You can configure different autonomy levels (review-driven, agent-assisted, agent-driven), but even in the most conservative mode, it's doing more than Copilot ever attempts.
My take: for simple coding tasks where you know exactly what you want, Copilot's reactive approach is faster. For complex refactoring or feature implementation where the "how" is tedious but the "what" is clear, Antigravity's autonomy is game-changing.
2. Multi-File Operations
Copilot: works primarily on the file you have open. It can reference other files in your workspace for context, but it doesn't autonomously edit multiple files at once. If you need to refactor something across 20 files, you're opening each one and letting Copilot help with each individually.
Antigravity: designed for multi-file operations. An agent can read your entire codebase, identify all the files that need changes, and propose modifications across all of them in a single workflow. It maintains consistency and applies patterns across your entire project.
My take: this is where Antigravity absolutely crushes Copilot. When I refactored Easy Kit Utils, the agent touched dozens of files, utility functions, tests, documentation, type definitions, maintaining consistency throughout. Doing this with Copilot would have meant manually opening each file and repeating similar instructions. With Antigravity, I described the goal once and reviewed the results.
3. Planning and Context
Copilot: understands the immediate context of what you're writing. It's excellent at learning patterns and suggesting code that fits your style. But it doesn't "plan" in the traditional sense, it predicts the next logical tokens based on what came before.
Antigravity: actually creates plans. Before making changes, agents break down complex tasks into steps, show you the approach, and let you approve or adjust. This planning phase is huge, it means you can course correct before any code is written.
My take: the planning capability makes Antigravity feel less like a tool and more like a collaborator. When the agent proposed its refactoring plan for Easy Kit Utils, I could immediately see it had understood the scope and could suggest adjustments before any work began. This saves tons of time compared to discovering implementation issues after the fact.
4. Browser Integration and Testing
Copilot: doesn't interact with browsers or test your code's visual output. It's purely code-focused.
Antigravity: includes an integrated browser where agents can actually test web applications, interact with DOM elements, and verify functionality. The agent doesn't just write code, it validates that the code works correctly by actually running it.
My take: this is wild and something I didn't appreciate until I used it. The agent can spin up a test environment, interact with UI elements, catch bugs visually, and iterate on fixes. It's like having a QA engineer and a developer in one.
5. Multi-Agent Workflows
Copilot: single-threaded. One suggestion at a time, one task at a time.
Antigravity: multi-agent orchestration. You can have multiple agents working on different parts of your codebase simultaneously. One agent refactors utilities while another updates documentation and a third improves test coverage all in parallel.
My take: I haven't fully explored this yet, but the potential is obvious. For large projects, being able to parallelize different work streams with AI agents is powerful. It's like having a team instead of a single assistant.
6. Integration and Ecosystem
Copilot: deep integration with GitHub's ecosystem. Pull request summaries, issue analysis, commit message generation if you live in GitHub, Copilot fits seamlessly. Also works with VS Code, JetBrains, Vim, Neovim, and more. Massive extension ecosystem.
Antigravity: built on VS Code's foundation, so the interface is familiar, but it's a standalone IDE rather than an extension. This means you lose access to some VS Code extensions, but you gain Antigravity's agent-first architecture. Works with any Git repository, not just GitHub.
My take: if you're heavily invested in the VS Code extension ecosystem or need specific IDE features, losing that might hurt. But Antigravity's agent capabilities more than compensate for me. The trade-off is worth it for the kinds of tasks I'm tackling.
7. Learning Curve
Copilot: almost zero learning curve. Install it, and it just starts working. The ghost text appears, you press Tab, done. You're productive immediately.
Antigravity: steeper learning curve. You need to understand different autonomy modes, how to structure prompts for agents, how the Agent Manager works, and how to effectively review multi-file changes. There's more to learn before you're using it optimally.
My take: this is Copilot's biggest advantage it's dead simple. Antigravity requires investment to master. But once you get over that initial hump, the productivity gains are substantial.
8. Speed and Latency
Copilot: extremely fast. Suggestions appear almost instantly. The inline experience feels native and responsive.
Antigravity: slower by nature. Agents need to plan, reason, execute, and validate. Even simple tasks take more time than Copilot's instant suggestions. You're trading immediacy for thoroughness.
My take: for quick edits and rapid development, Copilot wins on speed. But for complex tasks that would take you an hour to do manually, waiting 5 minutes for an agent to handle it is a massive time savings. Different use cases.
9. Enterprise Readiness
Copilot: SOC 2 certified, ISO 27001 compliant, IP indemnification, zero-data-retention guarantees, audit logs, admin controls. It's enterprise-ready with proper governance.
Antigravity: in public preview. Documentation on enterprise security controls, data handling, compliance certifications, and privacy policies is limited or incomplete. Not ready for enterprise procurement yet.
My take: if you work at a large company with strict compliance requirements, Copilot is currently the only viable option. Antigravity needs to mature in this area before enterprises can adopt it seriously.
Where Copilot Still Wins 🏆
Let me be clear: GitHub Copilot is an incredible tool, and there are scenarios where it's still the better choice:
Everyday Coding Velocity
For normal day-to-day development writing functions, adding features, fixing bugs Copilot is faster and more efficient. The inline suggestions are instant, the context is always right, and it doesn't interrupt your flow.
If you're building a feature and you know exactly how to implement it, Copilot accelerates the mechanical work of typing without adding overhead.
IDE Flexibility
Copilot works in VS Code, JetBrains IDEs, Vim, Neovim, Visual Studio, Xcode basically everywhere. If you're not willing to switch IDEs or you rely on specific tools, Copilot fits into your existing setup.
Antigravity requires using Google's IDE, which might not be acceptable if you have a customized development environment you love.
Learning Resources and Community
Copilot has been around longer and has a massive community. If you run into issues, there are tons of Stack Overflow answers, Reddit threads, and YouTube tutorials. The documentation is comprehensive.
Antigravity is new, so the community is smaller and resources are limited. You're more likely to encounter undocumented behavior or hit edge cases that no one has solved yet.
Enterprise Compliance
As mentioned earlier, if you need SOC 2 certification, audit trails, IP guarantees, and established data privacy policies, Copilot is the mature choice. Antigravity will get there eventually, but it's not there yet.
Specific GitHub Integration
If you heavily use GitHub-specific features like having Copilot generate commit messages from GitHub's API, summarize pull requests, or analyze issues Copilot's tight integration is valuable.
Antigravity works with Git but doesn't have these GitHub native features.
Why I Prefer Antigravity Now 💪
So with all those advantages Copilot has, why did I switch to Antigravity? Here's my honest reasoning:
The Nature of My Work Changed
I spend a lot of time maintaining open source libraries like Easy Kit Utils. This involves large-scale refactoring, updating documentation across multiple files, modernizing syntax patterns, and ensuring consistency throughout the codebase.
These tasks are perfect for Antigravity's agent-driven approach. I don't need suggestions for the next line of code I need entire sections of the codebase refactored according to modern best practices.
With Copilot, I'd open file after file, manually applying similar changes and hoping I maintained consistency. With Antigravity, I describe the goal, review the plan, and let the agent handle the tedious execution across dozens of files.
I Value Thinking Over Typing
Here's something I realized while using Antigravity: I don't enjoy typing code. I enjoy solving problems and architecting solutions. The actual mechanical work of writing syntax is the least interesting part of development for me.
Antigravity lets me operate at a higher level of abstraction. I think about what the code should do, not how to type it out. This feels more aligned with how I want to work as a developer.
Multi-File Consistency Is Crucial
When you're maintaining libraries, consistency is everything. If you refactor one utility function to use modern syntax, you need to refactor all of them the same way. If you update one test file's structure, you should update all test files similarly.
Antigravity's ability to understand patterns and apply them across an entire codebase is invaluable. It doesn't just make changes it makes consistent changes that follow the established patterns.
The Planning Phase Saves Massive Time
I can't overstate how useful the planning phase is. When I asked Antigravity to refactor Easy Kit Utils, the agent created a detailed plan showing exactly what it would change and why. I could review this plan, suggest adjustments, and ensure we were aligned before any code was touched.
This is so much better than discovering issues after the fact. It's like having code reviews before the code is even written.
Browser-Based Validation Is a Game Changer
Being able to have the agent actually test changes in a browser environment is wild. For documentation examples and test cases, the agent would render the page, verify functionality, and catch issues I would have missed.
This closed-loop development write code, test it, validate it, fix issues all happening autonomously is powerful. It means higher quality output with less manual QA.
I'm Willing to Trade Speed for Quality
Yes, Antigravity is slower than Copilot for simple tasks. But the output quality is often higher because the agent is thinking through the problem, planning the approach, and validating the results.
I'd rather wait 5 minutes for a thoroughly planned and tested solution than get instant suggestions that require significant manual cleanup and testing.
The Future Is Agentic
This is the big one: I believe agent-based development is the future. Right now, Antigravity is early and rough around the edges, but the paradigm it represents delegating complex tasks to autonomous AI agents is where we're heading.
By investing time in learning Antigravity now, I'm positioning myself for the next era of development. Copilot represents the peak of the "AI assistant" paradigm, but agents are the next evolution.
My Real-World Experience: The Easy Kit Utils Refactoring 🔧
I detailed this extensively in my previous article, but here's the short version:
I used Antigravity to completely refactor Easy Kit Utils, a JavaScript utility library. The project needed modernization: updating to ES6+ syntax, adding TypeScript definitions, improving test coverage, and cleaning up accumulated technical debt.
With Copilot, this would have looked like:
- Open each utility file individually
- Manually refactor each function while Copilot suggests completions
- Open each test file and update tests with Copilot's help
- Open documentation files and update examples
- Hope I maintained consistency across all changes
Estimated time: 1-2 weeks of focused work
With Antigravity, it looked like:
- Describe the overall refactoring goals to the agent
- Review the comprehensive plan the agent created
- Approve execution and watch it refactor across dozens of files
- Review the changes, provide feedback, iterate as needed
- Verify the updated tests and documentation
Actual time: 2-3 days, with most of that being review rather than coding
The agent maintained consistency, learned the patterns I preferred, and applied them uniformly across the codebase. It handled the tedious mechanical work while I focused on architecture and validation.
This isn't to say it was perfect I had to roll back some changes, fix edge cases the agent missed, and adjust implementations to match my style. But the overall productivity gain was massive.
The bottom line: For this kind of large-scale refactoring work, Antigravity was transformative. Copilot would have made each individual file easier to update, but Antigravity handled the entire project coherently.
They're Not Really Competitors 🤝
Here's the thing: framing this as "Antigravity vs. Copilot" is kind of misleading. They're not really competing for the same use case.
It's more accurate to say:
- Copilot is the best tool for daily coding, inline suggestions, and accelerating your normal workflow
- Antigravity is the best tool for complex multi-file tasks, large refactoring, and delegating entire features
You could actually use both:
- Use Copilot in VS Code for your everyday development
- Use Antigravity when you have a complex project that needs significant work
They complement each other rather than replace each other.
That said, I've personally decided to go all-in on Antigravity because:
- Most of my work lately is the kind of complex tasks Antigravity excels at
- I want to get better at agent-driven development workflows
- The future is heading in this direction anyway
But I totally understand developers who stick with Copilot, or who use both tools for different scenarios.
What About the Other Players? 👀
Copilot and Antigravity aren't the only AI coding tools out there. How do they fit into the broader ecosystem?
Cursor
Cursor is probably the closest to Antigravity in terms of agent-like capabilities. It's also building an agent-first IDE with autonomous task execution. The main difference is Cursor is a commercial product with established pricing ($20/month), while Antigravity is currently free in preview.
Many developers love Cursor, and it's a solid alternative to Antigravity. The choice between them often comes down to preference for Google's or Cursor's approach.
Windsurf
Another emerging player in the agentic IDE space. Similar agent-driven development paradigm to Antigravity and Cursor. Still relatively new, so less proven in production.
Cody (by Sourcegraph)
Focuses heavily on codebase context and search. Great for understanding large codebases and navigating unfamiliar projects. Different value proposition from Antigravity's autonomous execution.
Claude Code
Anthropic's command-line tool for agentic coding. Delegate tasks directly from the terminal. Interesting approach but more technical than GUI-based tools like Antigravity.
My take: The agentic IDE space is heating up fast. Antigravity, Cursor, and Windsurf are all pushing toward similar visions of AI-native development. Competition is good it'll drive innovation and better tools for everyone.
Should You Make the Switch? 🎯
Ultimately, the decision comes down to your specific needs and work style. Here's my guidance:
Stick with Copilot if:
- You're happy with your current development velocity
- You prefer tools that accelerate your existing workflow without changing it
- You need enterprise compliance and established security guarantees
- You rely heavily on GitHub specific integrations
- You want the lowest learning curve possible
- Your work is mostly straightforward feature development where you know the implementation
Try Antigravity if:
- You spend a lot of time on refactoring and maintenance
- You're maintaining open source libraries or large codebases
- You want to experiment with agent-driven development
- You're comfortable with early-stage tools that might have rough edges
- You enjoy operating at a higher level of abstraction
- You're willing to invest time learning new workflows for long-term productivity gains
- Price is a concern (it's currently free)
Use both if:
- You want Copilot's speed for daily work AND Antigravity's power for complex tasks
- You're exploring different AI development paradigms
- You can afford the time investment to learn both tools
- You work on varied projects with different needs
What I Want to Hear From You 💬
Here's where you come in! I've shared my experience and perspective, but the AI coding tools landscape is evolving so fast that every developer's experience matters.
If you've used Copilot, Antigravity, or both, I want to hear from you in the comments:
- Which tool do you prefer and why?
- What kinds of tasks do you use each for?
- Have you found workflows or use cases I haven't mentioned?
- What are the biggest pain points with each tool?
- How has your productivity changed since adopting AI coding assistants?
- Are you using any other AI coding tools (Cursor, Windsurf, etc.) and how do they compare?
- Do you think agent-driven development is the future, or will assistant-style tools remain dominant?
And if you're new to AI coding tools and trying to decide which to try first, drop your questions below! The community here is great about sharing experiences and helping others navigate these decisions.
Seriously, drop a comment. These tools are all evolving rapidly, and community feedback shapes where they go next. Plus, I genuinely want to know if my experience aligns with others or if I'm an outlier.
Conclusion
The AI coding revolution is happening right now, in real-time. We're witnessing a shift from "AI helps you code" to "AI codes for you," and it's both exciting and a little unnerving.
GitHub Copilot pioneered the first wave making developers more productive by augmenting their coding with intelligent suggestions. It's a mature, reliable, enterprise-ready tool that millions of developers use daily.
Google Antigravity represents the next wave autonomous agents that can handle complex tasks end-to-end with minimal human intervention. It's early, rough, and experimental, but it hints at a future where developers spend more time architecting and less time implementing.
Neither is "better" in an absolute sense. They excel at different things. But for the kind of work I'm doing maintaining open source projects, tackling large refactoring tasks, and building sustainable codebases Antigravity has become my go-to tool.
That might change as the tools evolve. Copilot is getting more agentic features (Copilot Agents), and Antigravity will mature and improve. The competition between these platforms will benefit all of us as developers.
For now, I'm Team Antigravity, but I'm keeping an eye on the whole ecosystem. This is an incredibly exciting time to be a developer. The tools we have access to today would have seemed like science fiction just a few years ago.
So experiment, explore, and find what works for you. And let me know in the comments what you discover!
Happy coding! ✨
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My name is Domenico, software developer passionate of Open Source, I write article about it for share my knowledge and experience.
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Top comments (2)
Great breakdown. This really captures the shift from typing code to delegating outcomes. Copilot accelerates execution, Antigravity changes the abstraction level entirely.
You're right, you summed it up well!