What OpenCode and Antigravity Actually Do

Think of Antigravity as NASA mission control for coding.

Instead of one astronaut doing everything, you have specialized teams working in parallel. One team handles design. Another builds the backend. A third runs quality checks.

They work together. Fix each other's mistakes. Report back with results.

You're not the developer anymore. You're the director.

OpenCode is the open-source engine that powers this system. It connects to the best AI models—Claude Opus 4.5, Gemini 3 Pro, GPT—and lets you switch between them based on what you need.

One model writes complex logic. Another handles creative interface design. Another runs automated tests.

Together, they build software without writing code manually—producing production-ready applications faster than any human team could.

The Old Way vs. The New Way

Projects that took weeks now take hours. Ideas that stayed in notebooks go live the same day.

This isn't theory. It's happening right now in the world of enterprise AI.

How to Actually Use OpenCode and Antigravity

Step 1: Install the Tools

OpenCode works in your terminal, your IDE, or as a desktop app. It's completely free and open source.

Antigravity is Google's AI-first IDE, built on VS Code. It's in free public preview right now.

Both run on Mac, Windows, and Linux. No complicated setup. No expensive subscriptions.

Step 2: Understand the Two Modes

Antigravity gives you two ways to work:

Editor View: This looks like a normal code editor. Use this when you want to write code yourself or make small tweaks.

Manager View: This is mission control. Here, you don't write code—you assign tasks to AI agents and watch them work in parallel.

Most people waste time in Editor View doing things Manager View handles automatically.

Switch to Manager View. That's where the magic happens when you want to build software without writing code.

Step 3: Give Your First Command

Here's a real example:

opencode run Build a responsive web app for tracking business automation tasks. Model Google/antigravity claudeopus-4.5 thinking high

Then hit Enter.

Within seconds:

• The agents create a project plan
• Install all dependencies
• Write the backend logic
• Design the frontend interface
• Run automated tests
• Capture screenshots to verify everything works

You just watch it unfold.

No syntax errors. No debugging. No context switching between files.

You've built a production-ready web app in minutes.

What's Actually Happening Under the Hood

This is where it gets powerful.

Antigravity runs multiple AI agents simultaneously. Each agent has a specialty:

• The Builder focuses on functionality, logic, and API connections
• The Design Lead handles UI, spacing, colors, responsive layouts
• The Nerd audits for bugs, security issues, performance risks

They collaborate in real time. If one agent encounters an error, another fixes it automatically.

This is called mission control coding—a completely new paradigm where you manage intelligent systems instead of typing code character by character. Learn more about how AI education is evolving to teach these new skills.

The Safety-First Approach

This power requires responsibility.

AI agents can access your files. They can run system commands. They can modify your entire codebase.

Here's how to use them safely:

Always supervise major tasks. Don't walk away during big builds. Watch what the agents are doing.

Back up your work first. Before running large projects, save your current state. One command can save you from disasters.

Review every change. AI-generated code can look perfect and be subtly wrong. Read the diffs. Check the logic.

Use artifacts for transparency. Antigravity generates logs, screenshots, and progress reports for every build. Review them before accepting changes.

Start small. Test the system with simple projects first. Learn how it thinks. Then scale up.

Think of AI agents like power tools. Incredibly useful. Potentially dangerous if misused. Always keep both hands on the wheel.

The Five Essential Features You Need to Know

1. LSP Integration (Language Server Protocol)

OpenCode automatically loads the right language tools for your project. This means the AI gets real-time error checking, code intelligence, and refactoring capabilities.

When you ask it to rename a function, it updates all 379 references across your codebase in 22 seconds. No missed files. No broken code.

2. Planning Mode

Before writing a single line of code, Antigravity enters Planning Mode.

It generates a detailed plan showing:

• Which files it will touch
• What logic it will change
• How it will verify correctness
• What risks exist

You review this plan. Edit it if needed. Approve it when ready.

Then the agents execute.

This prevents the biggest failure mode in AI coding: agents solving the wrong problem really well.

3. Browser Agent

This feature is wild.

Antigravity includes an agent that doesn't just write code—it tests it like a real user.

If you build a login form, the Browser Agent:

• Opens a local server
• Launches a browser
• Clicks the submit button with empty fields
• Verifies the error message appears
• Reports back with screenshots

It catches bugs you wouldn't find until production.

4. MCP (Model Context Protocol)

This connects your AI agents directly to real-world data and tools.

Need to pull data from your company database? MCP handles it.

Want to query your CRM? MCP connects it.

Building a dashboard that needs live analytics? MCP integrates it.

Instead of isolated AI that hallucinates data, you get AI that works with your actual systems—essential for AI enterprise implementations.

5. Multi-Agent Orchestration

Here's where it gets exponential.

You can run five different agents on five different tasks simultaneously.

One agent builds your authentication system. Another creates your dashboard. A third writes documentation. A fourth runs security audits. A fifth deploys to staging.

All happening in parallel. All coordinated. All reporting progress in real time.

This is why projects that took weeks now take hours.

Real-World Example: Build a Todo App in 10 Minutes

Let's walk through an actual project.

Your goal: Build a full-stack todo list app with user authentication, database storage, and a clean interface.

What you do:

1. Open Antigravity Manager View
2. Press Cmd+E to start a new agent task
3. Type: "Create a todo list web app using Python and React. Include user auth, database persistence, and responsive design."
4. Hit Enter

What the agents do:

• Planning Agent creates an implementation plan with file structure
• Builder Agent sets up the Python backend with FastAPI
• Design Agent creates the React frontend with Tailwind CSS
• Database Agent configures PostgreSQL and creates migrations
• Auth Agent implements JWT authentication
• Test Agent writes and runs automated tests
• Browser Agent verifies the UI works correctly

Your job:

Review the artifacts. Check the screenshots. Test the app. Make refinement requests if needed.

Ten minutes later, you have a working app you can demo to clients.

This is how you truly build software without writing code—by orchestrating AI agents that handle the implementation details.

The Mental Shift Required

The hardest part isn't technical. It's mental.

For decades, being a good developer meant being fast at typing code. The best programmers typed the fastest, memorized the most syntax, debugged the quickest.

That skillset is now obsolete.

The new skillset is orchestration. You need to:

• Describe what you want clearly
• Break complex projects into agent-sized tasks
• Review AI output critically
• Identify when to intervene
• Know which model handles which problem best

You're moving from mechanic to architect. From typist to director.

Some developers hate this. They spent 10 years mastering syntax and now it doesn't matter.

Smart developers embrace it. They multiply their output by 10x while competitors argue about semicolons.

Who This Changes Everything For

Founders: Validate ideas in hours instead of months. Build MVPs before your first hire. Ship products while competitors are still writing specs.

Developers: Scale your output without burning out. Handle five projects in the time you used to handle one. Become the AI manager everyone wants on their team.

Teams: Replace weeks of context-switching with coordinated agent workflows. Start Monday with tickets, finish Friday with shipped features.

Non-technical builders: Stop waiting for technical co-founders. Stop outsourcing to dev shops. Build directly with AI and maintain control.

The democratization of software creation is here. The people who move first will dominate their markets.

The Three Mistakes Everyone Makes (And How to Avoid Them)

Mistake #1: Treating AI Like Google

You wouldn't Google "make my app better." That's useless.

Same with AI agents. Vague prompts get vague results.

Instead: Be specific. "Add a dark mode toggle to the navigation bar that persists user preference in localStorage."

Specificity = quality.

Mistake #2: Accepting Output Without Review

AI code can look perfect and be completely wrong. It might use outdated libraries. Ignore edge cases. Create security holes.

Instead: Review every change. Run tests. Check for vulnerabilities. Use tools like Snyk, SonarQube, or Semgrep to catch issues automatically.

The agent is fast. You're the quality control.

Mistake #3: Skipping Backups

One wrong command can overwrite hours of work. AI agents move fast. Mistakes compound quickly.

Instead: Use git. Commit often. Create branches for agent tasks. If something breaks, you can revert in seconds.

Speed without safety is recklessness.

Advanced Patterns for Power Users

Once you've mastered the basics, try these workflows:

Test-Driven Development with AI:

1. Ask the agent to write tests based on requirements
2. Confirm the tests fail (no code exists yet)
3. Ask the agent to write code that passes the tests
4. Iterate until all tests pass

This prevents AI from hallucinating solutions.

Multi-Repository Coordination:

Run agents across different repos simultaneously. One updates your backend API. Another updates the mobile app. A third updates documentation.

All changes coordinate through implementation plans.

Continuous Improvement Loops:

Set up agents to monitor your codebase for technical debt. They refactor automatically, run tests, and submit pull requests for your review.

Your code gets cleaner while you sleep.

The Tools Are Free. The Advantage Isn't.

OpenCode is open source. Antigravity is in free public preview.

The technology is available to everyone right now.

But here's the thing: Most people won't use it. They'll read this tutorial, think "that's cool," and go back to typing code the old way.

The competitive advantage goes to the people who actually implement.

Who build their first project with AI this week. Who practice orchestrating agents instead of writing functions. Who ship products while others are still learning syntax.

The future of coding isn't code. It's collaboration with AI powered by advanced Google Cloud AI and similar platforms.

The question isn't whether this will happen. It's already happening.

The question is: Will you be leading this wave or watching it from the sidelines?

Getting Started Right Now

Don't overthink it. Start small:

1. Install OpenCode from opencode.ai
2. Sign up for Antigravity's free preview at antigravityide.org
3. Pick one small project—a landing page, a calculator, a todo list
4. Use Planning Mode to create an implementation plan
5. Let the agents build it
6. Review the output
7. Ship it

That's it. That's how you start.

Then do it again tomorrow with something harder. And again the day after.

Within a week, you'll build more than you built in the last month.

Within a month, you'll wonder how you ever coded without agents.

Within a year, you'll be the person teaching others how to do this through AI tutorials like this one.

The tools exist. The advantage is execution.

Stop reading. Start building.