Antigravity AI Features 2026: What Google Antigravity Can Do

Antigravity AI Features Overview

Google Antigravity combines coding agents with development tools that cover planning, implementation, testing, research, browser interaction and project review. Developers can use these capabilities individually or combine them into larger agent workflows.

Not every developer needs every feature. A small coding task may only need Tab completions or one agent. Larger projects benefit more from Projects, parallel agents, browser verification, scheduled work and structured review.

What Is Google Antigravity?

Google Antigravity is an agentic development platform built around AI agents that can complete multi step coding and knowledge work.

Agents can inspect project files, execute commands, interact with browser tools, access connected development services, create reviewable outputs and delegate suitable work to other agents.

Antigravity also gives developers several ways to work. The platform includes Antigravity 2.0, IDE integrations, a standalone IDE, a terminal based CLI and an SDK for custom agent development.

Plan limits become more important once you move from exploring features to using Antigravity regularly. Our Antigravity AI pricing guide covers current plan costs and usage limits separately so this article can stay focused on features.

Antigravity 2.0 vs IDE Extensions vs IDE vs CLI vs SDK

Antigravity 2.0 places agents and Projects at the center of the experience. The IDE keeps developers closer to files and editor tools. IDE Extensions bring Antigravity capabilities into environments such as Visual Studio Code, Visual Studio, JetBrains IDEs, Zed and Xcode.

The CLI works better for developers who spend most of their time in terminals or remote environments. The SDK gives developers a programmable foundation when they want to build custom agent systems.

AI Models and Core Coding Features

Antigravity combines agent workflows with selectable reasoning models and everyday coding assistance. Model availability can change as Google updates the platform and some access differences depend on the selected plan.

AI Models Available in Antigravity

Antigravity currently provides several reasoning models through its model selector. The lineup includes Gemini models along with Claude and GPT OSS choices.

The ability to choose a model gives developers more flexibility than a workflow tied to a single reasoning engine. A fast model can make sense for routine work while a stronger reasoning model may fit tasks that require deeper analysis.

The model list can change as Google releases new versions. Developers making an important plan decision should check current availability rather than assuming an older model list will remain permanent.

Developers comparing the broader AI model landscape can also read our ChatGPT vs Claude vs Gemini comparison for a wider look at how these major AI ecosystems differ.

Tab Completions and Editor Assistance

Antigravity also supports real time code completion through Tab. This feature serves a different purpose from autonomous agents.

An agent can take ownership of a larger task. Tab works inside the normal coding flow and helps developers complete code as they type. Developers who prefer hands on editing can use Tab for smaller changes and switch to agents when a task requires planning, tool use or multi step execution.

Current Antigravity plans include unlimited Tab completions. Agent usage follows separate rate limits.

Autonomous Agents and Multi Agent Development

A conventional coding assistant often responds to small requests such as writing a function, explaining an error or refactoring a component. Antigravity agents can work with larger objectives.

An agent can inspect files, understand the surrounding project, create a plan, edit code, run commands, use browser tools and return results for review.

Autonomous Coding Agents

Autonomous agents work best when developers give them a clear objective and enough context to make sensible implementation decisions.

For example a request such as Add a show or hide password control to the existing login flow while preserving the current validation and styling gives an agent a clear objective without prescribing every individual edit.

A broad instruction such as Improve the login system leaves too much open to interpretation. The request could refer to design, accessibility, authentication logic, validation or performance.

Clear scope makes autonomous execution more useful because the agent knows what result the developer expects.

Agent Delegation and Task Execution

Good delegation starts with a defined engineering objective. Developers should identify the expected result, relevant constraints, areas that must remain unchanged, required tests and actions that need approval.

An agent with file, browser and terminal access can act much faster than a chatbot that only suggests code. Clear requirements matter more as the system gains more ability to execute work directly.

Dynamic and Parallel Subagents

Antigravity can divide larger tasks among subagents when the work has clear boundaries.

Imagine a release with three independent issues. The API returns the wrong status code. The account settings interface contains a regression. The deployment build fails for a separate reason.

One agent can investigate the backend. Another can reproduce the interface issue. A separate agent can inspect the build logs. The main workflow can coordinate the results without forcing every investigation to run in sequence.

When Parallel Agents Work Best

Parallel agents make the most sense when each task has a clear owner and limited overlap.

• Testing separate components
• Researching independent dependencies
• Investigating unrelated errors
• Running validation while implementation continues
• Reviewing frontend and backend concerns in separate areas

Several agents editing the same tightly connected files can create extra coordination work. Independent responsibilities usually produce a cleaner multi agent workflow.

Projects and Development Workspaces

Real applications often span more than one folder or repository. A feature can involve a frontend application, an API service, shared packages, documentation and automated tests.

Antigravity Projects

Projects group relevant folders, conversations, settings and permissions around a larger piece of development work.

Developers can give different Projects different levels of access. A local prototype may need a different permission setup from production infrastructure or a repository that contains sensitive configuration.

Project level context also reduces the need to explain the same architecture during every new agent conversation.

Multi Folder Development and Git Worktrees

Multi folder access helps when one feature crosses repository boundaries. A subscription cancellation flow may require changes to the account interface, billing API, validation package and integration tests.

Antigravity Projects also support Git worktrees. Agents can work in isolated background folders instead of sharing one active working directory.

That isolation helps independent tasks stay separate when several agents work against the same repository.

IDE and IDE Extensions

The Antigravity IDE keeps agents close to normal editing, terminal activity and browser based development.

IDE Extensions provide another route for developers who already work in Visual Studio Code, Visual Studio, JetBrains IDEs, Zed or Xcode. They can use Antigravity capabilities without moving every coding task into a different development environment.

Antigravity 2.0 focuses more heavily on orchestration. The IDE experience keeps individual files and direct editing closer to the center of the workflow.

Quick Conversations and Isolated Work

Not every task needs a permanent Project. Developers can use more isolated workflows for research, experiments and smaller tasks that do not need access to a larger development environment.

Artifacts Code Review and Verification

Antigravity Artifacts give developers structured evidence of what an agent planned, changed or verified.

Autonomous execution becomes difficult to review when developers only see a long history of individual tool calls. Artifacts turn important parts of the process into clearer checkpoints.

What Are Antigravity Artifacts?

Artifacts can show the agent’s intended implementation, actual repository changes, visual verification and overall progress.

An Artifact does not prove that every technical decision is correct. It gives the developer better material for review.

What Antigravity Artifacts Can Include

• Implementation plans
• Code diffs
• Architecture diagrams
• Images
• Screenshots
• Browser recordings
• Progress information
• Structured development outputs

Each output answers a different question. A plan shows what the agent intends to do. A diff shows what the agent changed. A browser recording can show how an interface behaves after the change.

Implementation Plans

Implementation Plans become especially useful before large changes.

Suppose an agent proposes an account deletion flow that removes billing records. The organization may need those records for accounting. A developer can correct the plan before the agent changes the code.

Early review saves time because the developer can fix a wrong assumption before it spreads across several files.

Code Diffs and Visual Evidence

An agent summary should not replace repository review for an important change.

A message saying authentication updated successfully does not show whether the agent touched unrelated files, changed dependencies, weakened a test or modified configuration.

The Git diff gives developers a clearer view of the actual implementation.

Artifact Feedback

Developers can also use Artifacts to correct an agent’s direction while the work remains manageable.

If most of a plan looks correct but one database change does not belong in the task, the developer can correct that part before the agent continues.

Browser Terminal Testing and Git Features

Software development involves more than editing source files. A change can compile and still fail inside the browser. A function can look correct and still fail a test. A small fix can also introduce unrelated repository changes.

Antigravity gives agents browser, terminal, testing and version control capabilities so they can work beyond code generation.

Browser Automation

Antigravity agents can interact with web interfaces as part of a task.

• Open pages
• Click controls
• Enter form data
• Move between views
• Check visible output
• Capture screenshots
• Record browser activity

Browser interaction is especially useful for frontend development because reading source code alone cannot confirm that a user flow behaves correctly.

Automated Testing and Verification

Developers still need to define the expected behavior clearly.

For a checkout bug the agent can reproduce the failure, confirm that the application does not create an invalid order, repeat the flow with successful payment initialization and verify that valid orders still work.

The tools execute the checks. The developer defines what counts as a correct result.

Integrated Terminal

Terminal access lets an Antigravity agent perform development work that goes beyond file editing.

• Run test suites
• Start development servers
• Install dependencies
• Execute builds
• Run project scripts
• Inspect logs
• Check Git state

A traditional chatbot can suggest a terminal command. An Antigravity agent can execute the command when the developer has granted the required permission.

Git and Version Control Review

Git tools help developers inspect the actual repository changes created during agent work.

Small scope changes often matter more than dramatic failures. An agent may add an unnecessary configuration file, change a dependency, include a refactor inside a small bug fix or modify formatting across unrelated files.

A clean diff makes these changes easier to identify before the developer accepts them.

Scheduled Tasks and Background Automation

Antigravity Scheduled Tasks let developers configure agent work that runs on a defined schedule.

This feature fits recurring processes that developers would otherwise start manually every time.

When Scheduled Tasks Are Useful

• Recurring repository checks
• Routine test runs
• Maintenance reports
• Scheduled research
• Monitoring work
• Repeated validation

A useful Scheduled Task needs a narrow objective and a clear output. A dependency audit can identify newly reported high severity issues and create a report without automatically changing project packages.

Limits of Background Automation

Automation cannot repair unclear instructions. A vague recurring task simply repeats the same ambiguity on a schedule.

Teams can keep detection separate from sensitive actions. The agent can identify a problem and prepare the findings while the developer approves any high impact change.

Regular automation also consumes more agent capacity than occasional experiments. Our Antigravity AI Free vs Pro comparison explains when the free plan remains enough and when higher usage can justify paid access.

Antigravity CLI SDK Skills MCP Plugins and Hooks

Antigravity works as more than a desktop development application. The CLI, SDK, Skills, Custom Agents, MCP integrations, plugins and hooks let developers adapt agent workflows to different technical environments.

Antigravity CLI

The Antigravity CLI provides a terminal focused way to work with Antigravity agents.

It fits developers who spend much of their time in SSH sessions, terminals or keyboard focused development environments.

CLI workflows can support long builds, documentation searches, codebase analysis, validation, system tests and background agent tasks.

Antigravity SDK

The Antigravity SDK exposes the agent framework programmatically.

Developers can use it when they want to build custom agents or integrate agent capabilities into their own applications.

An internal dependency maintenance agent could inspect packages, identify outdated dependencies, propose upgrades, run tests, create a report and request approval before making sensitive modifications.

Skills and Custom Agents

Skills package reusable instructions and capabilities so developers do not need to rebuild the same process in every prompt.

Custom Agents let developers create specialist agents with their own instructions, model choices, tool access and execution behavior.

A test review agent can follow one testing policy. A migration agent can follow specific database procedures. A documentation agent can work from a consistent publishing checklist.

This type of specialization becomes useful when a project needs repeatable behavior across many development tasks.

MCP Integrations Plugins and Hooks

Antigravity supports the Model Context Protocol known as MCP. MCP connections can give agents access to development tools and services used by a project.

Depending on the current configuration these integrations can connect Antigravity with services such as GitHub, GitLab, Supabase, Postman, Figma, Firebase, PostHog, Stripe and database tools.

Hooks can run local scripts at defined points in an agent workflow. Teams can use them for project specific checks, validation or existing development procedures.

Every additional connection expands what an agent can access. Teams should give each agent only the permissions needed for its assigned work.

Antigravity AI Security and Permission Controls

Antigravity uses permission settings and approval workflows to control what agents can access and execute.

Permission controls matter because agents can perform real actions rather than only suggesting code.

File and Tool Permissions

Developers can control access to areas such as:

• File reading
• File writing
• Terminal commands
• Browser activity
• MCP tools
• Project folders
• Connected services
• Sandbox execution

Antigravity Sandbox adds another isolation layer for agent execution. Developers can use sandboxing when code or commands should not receive unrestricted access to the wider local environment.

A practical permission setup gives the agent enough access to complete the task without giving it unnecessary control over the entire development environment.

Approval Controls

Developers should review sensitive actions before execution when the consequences matter.

A sensible starting point uses narrower permissions. Developers can expand access after they understand how the agent behaves inside a particular project.

What Should Developers Review Closely?

• High impact shell commands
• Package changes
• Dependency changes
• Database migrations
• Authentication logic
• Credentials
• Deployment actions
• Infrastructure changes
• Broad refactors

A command can run successfully and still represent the wrong business decision. Technical review needs to check the purpose of a change as well as whether the code executes correctly.

Remote Control and Live Voice Transcription

Antigravity also includes smaller features that can improve specific development workflows.

Remote Control

Remote Control helps when an agent runs a longer task on one machine and the developer needs to check progress or respond from another device.

The feature has more value for work that continues for a meaningful period than for short tasks that finish immediately.

Live Voice Transcription

Live Voice Transcription lets developers describe tasks conversationally.

Voice input can make a complicated request faster to explain. Developers should still review important constraints and acceptance criteria in written form before an agent starts a significant change.

How Antigravity AI Features Work Together

The strongest Antigravity workflows combine several features rather than relying on one capability alone.

Consider a team adding an account deletion process to an existing application.

1. Project context gives the agent access to the relevant frontend and backend areas.
2. Planning lets the agent inspect the existing system and propose an implementation.
3. Subagents can investigate independent frontend and backend concerns.
4. Terminal and browser tools test the implementation from both technical and user perspectives.
5. Artifacts and Git review give the developer evidence to inspect before accepting the work.

The value comes from the connection between planning, execution, testing and review. Antigravity does not rely on one isolated AI feature to carry the entire development process.

Benefits and Limitations of Antigravity AI

Agentic development changes how developers spend their time. It can reduce repetitive execution while increasing the importance of task definition, permissions and review.

Main Benefits

Larger tasks can move to agents. Developers can delegate a bounded feature, investigation or maintenance task instead of requesting individual functions one at a time.

Parallel agents can reduce sequential work. Independent investigations and validation tasks can run at the same time when their responsibilities do not overlap.

Artifacts improve visibility. Plans, diffs, screenshots, browser recordings and test evidence give developers more useful material than a simple message saying the task is complete.

Reusable workflows improve consistency. Projects, Skills, Custom Agents, MCP connections and Scheduled Tasks can reduce repeated setup across similar development work.

Main Limitations

Human review still matters. Agents can misunderstand requirements, modify unnecessary files, choose an unsuitable design or verify the wrong behavior.

Multi agent work needs clear boundaries. Two agents editing the same module can create conflicts even when each agent makes a reasonable change.

More capability requires tighter permissions. File editing, command execution, browser control and connected services allow agents to perform real actions. Developers should match access to the task.

Antigravity changes quickly. Google continues to update models, integrations, product surfaces and individual features. Stable descriptions remain useful longer than assumptions based on an older screenshot or release.

Developers who want to compare other AI coding workflows can also explore our Best Replit Alternatives guide.

Developers who already know they want paid access can Get Antigravity AI and review the available access setup separately from Google’s direct plan structure.

Frequently Asked Questions About Antigravity AI Features

What are the main features of Antigravity AI?

Antigravity AI includes autonomous agents, dynamic subagents, Projects, Artifacts, browser and terminal tools, Scheduled Tasks, Tab completions, Git review, permission controls, Skills, MCP integrations, a CLI and an SDK. These capabilities help developers delegate multi step development work while keeping important changes reviewable.

What AI models does Antigravity support?

Antigravity currently offers Gemini 3.8 Flash, Gemini 3.7 Flash, Gemini 3.6 Flash, Gemini 3.1 Pro, Claude Sonnet 4.6, Claude Opus 4.6 and GPT OSS 120B as selectable reasoning models. Availability can change as Google updates the platform and plan structure.

What is Antigravity 2.0?

Antigravity 2.0 is Google’s standalone desktop experience for managing AI agents and Projects. It focuses on agent orchestration, parallel work, scheduled activity, browser and terminal operations, Artifacts and permission controls.

What is the difference between Antigravity 2.0 and the Antigravity IDE?

Antigravity 2.0 focuses on coordinating agents and larger Projects. The Antigravity IDE keeps agents closer to direct code editing and normal development tools. IDE Extensions also bring Antigravity into supported development environments that developers may already use.

Can Antigravity use multiple agents at the same time?

Yes. Antigravity supports subagent workflows that can divide independent parts of a larger task. Parallel agents work best when each agent has a clearly separated responsibility.

What are Antigravity Artifacts?

Artifacts are structured outputs that help developers inspect an agent’s work. They can include implementation plans, code diffs, diagrams, screenshots, images and browser recordings. They provide evidence for review rather than replacing technical judgment.

Can Antigravity use browser and terminal tools?

Yes. Antigravity agents can use browser and terminal capabilities when developers grant the required permissions. Agents can use these tools for UI checks, builds, scripts, tests, Git operations and other development work.

What permission controls does Antigravity provide?

Antigravity provides controls for file access, terminal activity, browser tools, Project folders, connected services, MCP tools and sandbox execution. Developers can also use approval workflows for actions that need closer review.

Final Thoughts on Antigravity AI Features

The strongest Antigravity AI features go beyond autocomplete or isolated code generation. Antigravity connects agents with project context, file changes, terminal execution, browser interaction, parallel work, testing, Artifacts and permission controls.

The platform makes the most sense when developers want to delegate larger pieces of well defined work while keeping control over important technical decisions.

Antigravity does not remove the need for engineering judgment. It changes where developers apply that judgment. Instead of supervising every individual edit, developers can spend more time defining the objective, setting clear constraints, reviewing important decisions and verifying the final result.