By Google launched Antigravity on November 18, 2025 – an agentic development platform that fundamentally redefines the IDE. Unlike traditional AI coding assistants that offer inline suggestions, Antigravity treats the IDE as a control plane for autonomous agents. Developers deploy agents that autonomously plan, execute, and verify complex tasks across their editor, terminal, and browser. Available in public preview today, free for individuals, it represents Google’s strategic bet on asynchronous, multi-agent workflows as the future of software development.
The Control Plane Paradigm
So what makes Antigravity different? Traditional IDEs – even with GitHub Copilot or Cursor – are text editors with smart autocomplete. Antigravity is something else: a control plane for orchestrating autonomous agents.
The platform features two interfaces. The Editor View is familiar: an AI-powered IDE with tab completions and inline commands for synchronous workflows developers already know. The Manager Surface is new: a dedicated interface to spawn, orchestrate, and observe multiple agents working asynchronously across different workspaces. This isn’t about making autocomplete 10% better. It’s about fundamentally changing what developers do all day – from line-by-line implementation to high-level architecture and task delegation.
Multi-Agent Orchestration in Practice
In practice, this architecture enables workflows impossible with traditional assistants. Deploy five different agents on five different bugs simultaneously. The Manager Surface orchestrates parallel execution while each agent works independently. Ask for a “Flask conference site with 8 talks, speaker profiles, and search functionality,” and a single agent handles the entire cycle: planning, implementation, dependency installation, and server launch.
Instead of raw logs, agents generate Artifacts – task lists, implementation plans, screenshots, and browser recordings. You review artifacts asynchronously, leave feedback like commenting on a doc, and agents incorporate your input without stopping execution. One developer described the experience: “It feels just like VS Code, but the AI feels much smarter. I got goosebumps watching the multi-agent system plan a refactor on its own.”
Learning Primitives and Model Optionality
Beyond immediate capabilities, Google’s playing the long game with learning primitives. Agents save useful context and code snippets to a knowledge base, accumulating patterns and architectural decisions over time. Day 1: generic agent. Day 365: deeply customized to your workflow. This creates switching costs – a competitive moat.
The platform supports Gemini 3 Pro, Claude Sonnet 4.5, and GPT-4o. Deliberately model-agnostic, it lets you route agents through different providers, preventing vendor lock-in. Contrast: GitHub Copilot is OpenAI-only. Google’s competing on architecture, not just features.
Early Adopter Reality Check
But the vision meets reality in early adopter frustrations. Dataconomy’s headline says it plainly: “Antigravity Runs Out Of Credits So Fast Developers Are Quitting Immediately.” Credits deplete after roughly 20 minutes of intensive tasks, according to HackerNews reports. DevClass’s hands-on testing “ran aground” due to “model provider overload” errors. Service reliability issues plagued the preview period.
Security concerns compound the problem. The terms of use warn that “Antigravity is known to have certain security limitations,” including data exfiltration and malicious code execution risks. One developer summarized the privacy worry: “Forced Google account login is unsettling.” InfoWorld reports security researchers are cautioning about enterprise risks. Beta testers note stability problems: “Sometimes agents do stupid things or freeze.”
The Agentic Development Race
Antigravity enters a crowded field. GitHub Copilot pioneered AI-assisted coding and remains the gold standard for intelligent code completion, scoring 95/100 for pair programming. Cursor, valued at $29.3 billion, offers a polished daily driver experience with superior UI smoothness. But both operate on synchronous workflows: suggest, accept or reject, repeat.
Antigravity’s architectural bet is different: asynchronous, multi-agent orchestration. “Copilot is a code assistant; Antigravity is an AI development agent with execution capabilities,” one analysis notes. The irony? Google participated as an investor in Cursor’s Series D funding round. Google’s simultaneously competing with and investing in Cursor.
Community reaction split 70% positive, 30% negative in the first 48 hours. HackerNews and Reddit erupted with speculation about whether Google had just “killed Cursor.” The emerging consensus: these tools are complementary, not replacements. Many power users will keep both – Cursor as the daily driver, Antigravity as the experimental lab for greenfield features.
Architecturally Significant, Execution Gaps Remain
The question isn’t whether this is incremental – it’s not. Google’s betting the IDE is a control plane, not a text editor. That’s an architectural paradigm shift worth taking seriously. Asynchronous workflows, multi-agent orchestration, and learning primitives differentiate Antigravity from vendor-locked competitors in meaningful ways.
But vision doesn’t matter if developers quit before it materializes. The credits problem is real. The service reliability issues are real. The security concerns are real. Google needs to fix execution gaps, or this compelling architecture becomes vaporware. They might be right about the future of development. They need to prove they can deliver it.
