Google Antigravity
Run and monitor several coding agents at once in an IDE
4.8•16 reviews•1.6K followers
Run and monitor several coding agents at once in an IDE
4.8•16 reviews•1.6K followers
Google Antigravity - Build the new way
This is the 2nd launch from Google Antigravity. View more
Google Antigravity 2.0
Launching today
Google Antigravity 2.0 is a standalone desktop app for orchestrating multiple AI agents in parallel, with scheduled background tasks, subagent workflows, and native integrations with AI Studio, Firebase, and Android.
Built for developers building production apps.
Free Options
Launch Team
Cursor
Claude Code
Google just separated the agent manager from the IDE and shipped it as its own desktop app.
What it is: Antigravity 2.0 is a standalone desktop application built entirely around orchestrating multiple AI agents in parallel, scheduling background tasks, and managing subagent workflows across projects.
Most AI coding tools still make you sit in the loop: prompt, wait, respond, repeat. Antigravity 2.0 breaks that pattern by letting agents run in the background on cron-like schedules, work in parallel across subagents, and carry full project context from AI Studio to your local environment in one click.
Run multiple agents simultaneously across parallelized subagent workflows
Schedule tasks that trigger agents automatically in the background
Export full projects from Google AI Studio to local development with one click
Connect natively with Firebase and Android
Issue voice commands instead of typing prompts
Use the CLI for terminal-native work or the SDK to deploy custom agents on your own infrastructure
If you're a software developer or engineering team that has outgrown one-shot prompting and wants agents running across your build loop without babysitting them, this is built for that workflow.
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Most software abstractions succeed when they hide complexity. Multi-agent systems seem to be doing the opposite, exposing planning, delegation, coordination, and supervision as first-class concepts.
Do you think the future interface is actually a visible org chart of agents, or does that disappear entirely once the system becomes reliable enough?
Scheduled agent work gets interesting the moment a team comes back later and has to decide whether a run is safe to accept or needs review. I would want every scheduled task to leave a small receipt: owner, allowed capability set, files or services touched, stop reason, and whether it completed, paused, or hit a guardrail. Without that, background autonomy can create more context debt than leverage.
The "sit in the loop: prompt, wait, respond, repeat" problem is real. I've been running Claude Code for side projects and the context switching cost is higher than people admit — you context-load the codebase, fire off a task, then either stare at it or switch to something else and lose the mental model entirely.
The cron-like scheduling piece is what I want to understand better. If I schedule a refactor agent to run at 2am, what happens when it hits a decision that needs human judgment — does it pause and queue, or does it guess and commit? The difference between "runs in background" and "runs unattended" is huge for trust.
Also curious about the subagent orchestration — when one agent spawns three parallel workers, how does the parent agent reconcile conflicting outputs? Is it another LLM pass, or is there a deterministic merge strategy?
Never used the IDE version much either. The subagent workflow is where it gets interesting: running parallel agents without babysitting each one is the shift that makes this feel different from Cursor or Claude Code. The background scheduling is a nice touch too. Excited to see how far they push the Firebase and Android integrations.
Parallel agents are powerful, but the monitoring layer is what makes this actually usable. Once multiple agents work at the same time, the hard part becomes catching conflicts, knowing what changed, and deciding what needs human review.
I have used Antigravity IDE Version before to make projects during hackathons, academic projects. What I like about using it, is it's way of interpreting the user's written prompts or instructions in a structured way as it's finishing a to do list one at a time. With the upgrade of 2.0, I am sure the ability of achieving multi tasking through multi agent feature would be a significant update.