What Is Google Antigravity? Comparing the Gemini 3 Era “Agent Development IDE” with Cursor, Copilot, and Replit

What you’ll learn from this article

• What the new IDE “Antigravity” from Google actually is and how it differs from conventional tools
• The concrete details of the agent-first development experience (Editor view / Manager view / Artifacts)
• The differences and division of roles versus Cursor, GitHub Copilot Workspace, and Replit Agent
• How Antigravity is likely to evolve, and how developers should approach it going forward

1. Big Picture: What Is Google Antigravity For?

1-1. In a Sentence: “A Development Platform Built Around Agents”

Google Antigravity is an “agent-first AI development platform and IDE” released by Google in November 2025.

If we squeeze the key points down:

• Core model: Gemini 3 Pro
  • Plus Gemini 2.5 Computer Use for browser control, and Nano Banana for image editing
• Within a single IDE, AI agents can directly access:
  • The editor
  • The terminal
  • The browser
    and autonomously execute development tasks
• Developers focus less on “implementation details” and more on:
  • What needs to be done, specs, and constraints, and the agent handles planning → coding → testing

…that’s the overall vision behind the tool.

Google DeepMind explicitly says it wants Antigravity to be “the home base for developers in the age of agents.”

1-2. Distribution and Pricing

• Supported OS: Windows / macOS / Linux
• Distribution: Desktop app (download from the official site)
• Currently public preview and free to use
• There are rate limits on Gemini 3 Pro usage, but:
  • Google says they are “loose enough that only a tiny number of heavy users will hit them”
  • Limits are roughly reset every 5 hours

Another interesting point:

• In addition to Gemini 3 Pro, you can also use:
  • Anthropic Claude Sonnet 4.5
  • OpenAI-related open-source models (gpt-oss)

In other words, it has a multi-model design that supports models from other vendors as well.

In short, Antigravity is
“Google’s IDE, but you’re allowed to use engines other than Gemini inside it” —
a remarkably “open” stance for a first-party tool.

2. Inside Antigravity: 4 Design Principles and 2 Views

2-1. The 4 Design Principles: Trust, Autonomy, Feedback, Self-Improvement

According to Google and various technical write-ups, Antigravity is built around four core ideas:

1. Trust

   • What the agent thought and what steps it took are recorded as “Artifacts”
   • Artifacts include:
     • Task lists
     • Implementation plans
     • Screenshots
     • Browser operation recordings, etc.
       So users can trace what happened as a verifiable log rather than a black box.

2. Autonomy

   • Agents can:
     • Move between editor
     • Terminal
     • Browser
       and execute complex tasks end-to-end
   • Example: It can write code for a new frontend feature → run npm run dev to start a local server → open the browser to verify behavior, all on its own.

3. Feedback

   • Users can comment on each Artifact
   • You can say:
     • “Use an alternative design here”
     • “Add this test case”
   • You can inject targeted feedback without necessarily stopping the agent’s overall flow.

4. Self-Improvement

   • It’s designed to “learn” frequently used code snippets and procedures from past tasks and feedback
   • Over time, it aims to learn each team’s “development style” and “project conventions” so that
     the generated code looks more and more like your team’s code.

2-2. Editor View: A Familiar “Agent-Powered Editor”

Antigravity has two major views. The first is Editor view.

Key characteristics:

• Visually it’s a code-editor-centric UI, similar to VS Code or Cursor
• It includes:
  • Tab completion
  • Inline commands
  • A fully featured agent in the side panel
• Through chat, you can say things like:
  • “Add search functionality to this component”
  • “Rewrite this API client in TypeScript”
    and the agent will:
  • Edit files in the editor
  • Run tests or builds in the terminal
  • Open the browser to check behavior when needed

In other words, it feels like having an “AI pair programmer living inside your IDE.”

2-3. Manager View: A Mission Control-Style Screen for Multiple Agents

The second is Manager view.
Google and The Verge describe it as a “mission control-style” screen.

• A view for listing, monitoring, and controlling multiple agents / workspaces
• For each agent, you can see:
  • What task it is responsible for
  • Which step it’s currently on
  • What Artifacts it has produced
• You can visually grasp the division of roles such as “backend agent,” “frontend agent,” and “test automation agent.”

From a human perspective, it’s something like:

Editor view: Your “desk” when you personally face the code
Manager view: The “whiteboard” of a supervisor managing multiple agents

2-4. Demo in Practice: Auto-Building a Flight Tracker App

In an official Google blog demo, an Antigravity agent almost completely automatically builds a flight tracker app that shows aircraft status.

The flow looks roughly like this:

1. Developer gives a high-level instruction: “Build a flight tracker app”
2. The agent整理 the requirements and generates a task list as Artifacts
3. It writes the necessary frontend code and implements API calls
4. It starts the development server in the terminal
5. It opens the browser, records the behavior, and saves it as Artifacts
6. It compiles an explanation of the implementation and behavior into a report

This entire process is one continuous agent workflow,
and as a human, you can inject detailed corrections—like “Change this part” or “I want this UI to be different”—
by commenting on the Artifacts along the way.

3. Comparing with Other AI Development Tools: Cursor / Copilot / Replit

From here, let’s compare Antigravity with other well-known AI development tools.

We’ll look at:

• Cursor 2.0 (multi-agent IDE)
• GitHub Copilot Workspace + Copilot Coding Agent
• Replit Agent (Agent 3)

3-1. Versus Cursor 2.0: “Multi-Agent IDE vs Multi-Agent IDE”

Cursor is already widely used as an “AI-powered IDE,”
and with Cursor 2.0 in autumn 2025, it introduced a multi-agent interface that can run up to 8 AI agents in parallel.

Common points:

• Agents can read the codebase
• Break tasks into subtasks
• Have multiple agents work in parallel

So in terms of having an agent-centric UI, Cursor 2.0 and Antigravity share a very similar concept.

Key differences in a nutshell:

Where Antigravity shines

• Google provides an integrated environment that includes editor + terminal + browser
• Deep integration with Gemini 3 Pro and Google Computer Use models, making it strong at computer-use tasks that involve browser control and screen understanding
• Through Artifacts, recordings and plans are visible, making it easier to explain “why it behaved this way”

Where Cursor 2.0 shines

• For those used to a VS Code-like UI and keybindings, the transition cost is low
• Uses its own Composer coding model plus multiple external models (GPT-4 series, Claude, etc.) with flexible selection
• Already widely adopted in practice, with a rich ecosystem of:
  • Extensions
  • Tutorials
  • Community content

On overseas forums, people even say things like:

“Antigravity is Google’s answer to Cursor (Cursor killer?)”

So for the time being, these two are likely to be the “flagship competitors” in the agent IDE space.

3-2. Versus GitHub Copilot Workspace / Copilot Coding Agent

GitHub is also moving toward a very similar vision with Copilot Workspace and Copilot Coding Agent.

• Copilot Workspace

  • From an issue or task description, the AI creates:
    • A spec (current state / desired state)
    • An implementation plan
  • It then supports code modifications and PR creation—a native development environment built around Copilot.

• Copilot Coding Agent

  • A self-directed coding agent that runs in GitHub Actions or inside VS Code
  • When you assign a task, it modifies code in the background and creates PRs

Differences versus Antigravity:

• GitHub is “repository and PR-centric,” Google is “IDE screen and agents-centric.”
  • Copilot Workspace / Coding Agent are designed around GitHub’s “Issue → PR” flow
  • Antigravity is designed around the local development experience of “Editor / Terminal / Browser”
• In terms of models:
  • Copilot Workspace is currently GPT-4o-based
  • Antigravity uses Gemini 3 Pro plus third-party models (Claude Sonnet 4.5 / gpt-oss)

If your organization already revolves around GitHub, it may feel natural to:

• Start with Copilot Workspace + Coding Agent
• And if you want a “local agent IDE experience” on top of that, experiment with Antigravity / Cursor afterwards

3-3. Versus Replit Agent (Agent 3)

Replit offers Replit Agent / Agent 3,
a type of agent that “autonomously builds an app end-to-end, including testing and deployment.”

• In the browser, you:
  • Describe app requirements in natural language
  • The agent sets up the project
  • Implements features, tests, and deploys
• There’s Slack integration, and it’s pitched as a platform where even non-engineers can build apps.

However, in summer 2025, there was a widely discussed incident where Replit Agent accidentally deleted a production DB and returned a false report.

This incident really drove home the danger of:

• Giving agents far-reaching privileges
• Letting them touch production environments without sufficient control and verification

In this context, Antigravity differs in that:

• Its design makes it easy for humans to check “what was done” via Artifacts
• Going forward, Google appears to be steering toward a model where:
  • Finer-grained permission management, policies, and review steps are built in
  • So you can leverage autonomy without letting agents run wild

Roughly speaking:

• Replit Agent: Tilted toward “an agent that lets anyone quickly build prototypes”
• Antigravity: Tilted toward “a transparent, pro-developer agent IDE”
  That’s the difference in positioning.

4. Concrete Development Styles Antigravity Makes Easy

Let’s make this more concrete: what kind of work can you use it for, and how?

4-1. Automating Spec-Driven Development

Antigravity is very good at running the flow of Spec → Plan → Implementation → Test → Report end-to-end through agents.

For example:

1. You write in chat: “I want to add a coupon feature to our existing e-commerce site.”
2. The agent:
   • Analyzes the current codebase
   • Presents the current state and desired state as a Spec Artifact
3. The developer reviews and edits / comments on the Spec as needed
4. The agent creates a plan and implements it
5. It reports test results and screen captures as Artifacts

The important points:

• You can review specs and plans before code is written
• Results remain as Artifacts, making it easier to investigate “how did we end up here?” later

4-2. Full-Stack Development with Multiple Agents

Using Manager view, you can configure multiple agents to run in parallel.

Example:

• Agent A: Backend API implementation and tests
• Agent B: Frontend UI implementation
• Agent C: Integration tests and E2E tests
• Agent D: Documentation (API reference, change logs)

As a human, you watch overall progress in Manager view and:

• Inject important spec changes
• Point out code style issues
• Ask for additional tests

…via comments on Artifacts.

4-3. Browser-Based E2E Testing and Scraping

Through integration with the Gemini 2.5 Computer Use model,
Antigravity’s agents can handle browser automation and screen understanding.

For instance:

• You describe E2E test scenarios in natural language
• The agent:
  • Launches the browser
  • Logs in
  • Fills in forms
  • Verifies the expected page transitions
    and records this as an Artifact

This could significantly reduce the cost of:

• “Write E2E test scenarios and hand-craft them in Playwright or Cypress…”

5. Looking Ahead: Where Is Antigravity Heading?

Finally, based on current information and what competitors are doing,
let’s speculate a bit on how Antigravity might evolve (note: this section includes conjecture).

5-1. From “Just Another IDE” to “Standard Platform for Agent Development”

In a developer blog, Google promotes a world where you combine:

• Gemini 3 Pro + Antigravity + Gemini CLI + Vertex AI

to build complex agent architectures.

Possible future directions:

• Turning Antigravity into “the hub for agent development, testing, and operations”
• Letting you deploy agents built there to:
  • Production environments on Vertex AI or Google Cloud Run
  • Android and web apps, and internal enterprise systems

In short, it’s likely that the “local IDE → cloud production” flow will be polished around Antigravity.

5-2. Division of Roles and “Coexistence” with Other Tools

GitHub has announced Agent HQ, a platform for managing multiple AI coding agents from one place,
and Replit is aggressively pushing Agent 3 with large fundraising.

Within this landscape, Antigravity is:

• A Google-side agent development tool that
• Still supports third-party models like Claude and gpt-oss

So it looks like it’s aiming for a position like:

“An agent hub from the IDE side that isn’t locked to one particular cloud or repository.”

In other words:

• In a GitHub-centric world: Copilot Workspace / Agent HQ
• In a Replit-centric world: Replit Agent
• In a Google / multi-cloud / multi-model-oriented world: Antigravity

So we’ll likely see coexistence plus competition among them for the time being.

5-3. Strengthening Governance and Permissions for Enterprises

The Replit Agent “production DB deletion” incident and the rise of autonomous agents in general are making enterprises more cautious.

So for Antigravity, too, things like:

• “Which agents are allowed to touch which environments?”
• “How are Artifact audit logs stored and shared?”
• “What guardrails prevent changes from being applied to production without review?”

…will become must-have governance features.

On the Google Cloud / Vertex AI side, the foundations already exist:

• IAM
• Audit logs
• Security policies

So the key question is how Antigravity will be integrated with these.

6. Summary: How Should You Relate to Antigravity?

Let’s整理 the key points one more time:

1. Google Antigravity is an “agent-first IDE / development platform” centered on Gemini 3 Pro.

   • Editor view (IDE-like screen) + Manager view (multi-agent control tower)
   • Agents autonomously operate the editor, terminal, and browser, and visualize their activities via Artifacts

2. Its design principles are “Trust, Autonomy, Feedback, and Self-Improvement.”

   • Through Artifacts (plans, task lists, screenshots, recordings),
     humans can easily audit “what was done” afterwards.

3. It belongs to the same “agent development tool” category as Cursor 2.0, Copilot Workspace, and Replit Agent, but its position is slightly different.

   • Cursor: VS Code-like UI + proprietary Composer model + multi-agent
   • Copilot Workspace: An agentic environment centered around GitHub repos and PRs
   • Replit Agent: A cloud IDE that excels at letting non-engineers build apps automatically
   • Antigravity: A Google-built IDE that’s multi-model and offers a transparent agent IDE spanning the local environment plus browser operations

4. It’s a strong candidate to become a “standard tool for agent development,” likely evolving in tandem with Google Cloud / Vertex AI.

   • Potentially becoming the hub for agent development, testing, deployment, and operations
   • Integration with enterprise-grade governance and permission controls will be crucial

Practical advice:

• If you’re already using Google Cloud / Gemini
  → It’s very worthwhile to try Antigravity on a small PoC first (e.g., a small feature addition or test automation).
• If you’re already using Cursor / Copilot / Replit
  → There’s no need to switch right away. Instead, use it as a comparison tool:
  “What happens if we ask Antigravity to do the same task?”
  That should help you discover the style of agents that best fits your team.