I Tried Google Antigravity IDE — And It Feels Different From Traditional Coding Tools

Over the past few months, AI coding tools have been everywhere. Cursor, GitHub Copilot, Windsurf, Codeium — every few weeks there's something new claiming it will completely change how developers write code.

So when I came across Google Antigravity, I was curious. At first I assumed it was just another editor with AI autocomplete built in. But the more I explored it, the more it felt like Google is thinking about development in a slightly different way. And that's what caught my attention.

(Quick context: Antigravity launched in public preview, free for individuals, and runs on macOS, Windows and Linux. It's built around Gemini 3 Pro but also supports Anthropic's Claude Sonnet 4.5 and OpenAI's GPT-OSS.)

It doesn't feel like just another IDE

Most IDEs still work the same way. You open files, write code, run terminal commands, debug something, fix it, repeat. AI usually sits beside that workflow as an assistant — maybe it completes code, maybe it writes a function, maybe it explains an error.

Antigravity feels like it's trying to move AI deeper into the workflow itself. Not just helping with code, but helping with the entire task. That difference sounds small, but the more you read into it, the bigger it gets.

The most interesting part: agent-first development

This is the part that stood out most to me. Google describes Antigravity as agent-first development, and honestly that explains it pretty well. Instead of AI helping with a line of code, the idea feels closer to AI helping with the job you're trying to complete.

For example: creating a new feature, updating multiple files together, debugging a failing implementation, running checks, and reviewing the generated output. There's even a dedicated "Manager" surface where you can spawn and watch several agents work in parallel, each with direct access to the editor, terminal and browser.

It feels less like autocomplete and more like having another developer inside the project with context. That's a pretty interesting direction.

It still feels familiar, which I like

One thing I noticed immediately: Google doesn't seem to be forcing developers into a completely new way of working. And that matters, because most developers already have workflows they're comfortable with — editor, terminal, Git, browser, docs, local environment. That workflow already works.

Antigravity feels more like an extra layer on top of that rather than asking you to replace everything. Personally, I think that makes adoption much easier. Good developer tools usually fit into your workflow. They don't fight against it.

The real test will be production projects

This is where I think every AI coding tool eventually gets tested. Demos always look clean. Real codebases usually aren't.

Production projects are messy. There's old code, temporary fixes, unclear naming, large folders nobody wants to touch, and half-finished documentation. That's where tools like this either become genuinely useful — or become something you open once and never come back to.

What I'm curious about is how Antigravity handles those real-world environments, because that's where developers actually spend their time.

My take after exploring it

I don't think Antigravity is trying to replace developers. And honestly, I don't think that's what most developers want anyway.

What feels more realistic is this: AI handles more of the repetitive movement around coding, and developers spend more time on decisions — architecture, reviewing, thinking through product and implementation. Less context switching, less jumping between tabs, less repetitive setup work. More actual building. That's the part I find interesting.

The short version

• Google Antigravity feels bigger than a normal AI code editor.
• It's focused on agent-first development, not only autocomplete.
• The goal seems to be helping developers complete tasks, not just write code.
• It still feels close to existing workflows, which makes it easier to approach.
• The real test will be how useful it becomes inside real production codebases.

Written by the TechKis team — an AI-first engineering studio. techkis.tech