🤔 Google Antigravity: Will This IDE Replace Programmers in 2026?
🚨 Answer: No, it won't replace them—at least not in 2026–2027. It's a tool that works well only for simple prototypes and MVPs, but for serious products (monoliths, enterprise, production deployments), it's raw, unstable, and unsafe. 📅 Google Antigravity was released on November 18, 2025, along with Gemini 3 Pro (1 million tokens, Deep Think). 💻 It's an agent-first IDE based on a fork of VS Code with agent access to the editor, terminal, and browser. 🤖 Agents plan tasks (up to 50 steps), write code, test, fix bugs, and can deploy to GCP. 📊 Each task is completed with an Artifact (plan, diff, logs, video from the browser)—this is a really convenient feature for verification.
💰 The preview is free, but with strict limits (reset every 5 hours, enough for 20–40 minutes of intensive work). 🔄 Claude Sonnet 4.5 and GPT-OSS are supported. ⚡ In the 11 days after release, many people praised the 4–8x acceleration of prototyping for simple tasks, but for real projects, it's a complete frustration: 🐛 freezes, bugs, 🛡️ security holes, and the need for constant manual edits. 👨💻 It's not an "autonomous development team," but an experimental assistant that is currently more annoying than helpful in serious work.
"Antigravity is not another Copilot. It's the first IDE built for agents, not for people"—official Google announcement, November 18, 2025. But in practice, it's still very raw.
🌐 Official Access
https://antigravity.google/ (the site is minimal, downloading is through guides like secondtalent.com or official Google resources) 🚀
⚡ In Short (Realistically)
- ✅ Autonomy: partial—agents work independently only on simple tasks; complex tasks require constant monitoring and edits
- ✅ Artifacts: the best feature—videos, plans, and logs provide transparency (but are often incomplete or truncated)
- ⚠️ Free Now: yes, but with strict quotas—enough for 2–4 tasks, then wait 5 hours
- ✅ Speed: simple prototypes (Todo-app, CLI)—9–20 minutes; medium/complex projects—40–90+ minutes with manual edits and freezes
- 🎯 You'll Get: an honest review without hype—real bugs, security risks, comparisons, and why it's NOT a replacement for Cursor/VS Code yet
- 👇 More Details Below—my tests, community feedback, and why I'm not migrating to Antigravity completely
📑 Table of Contents:
- 🎯 What is Google Antigravity and Why It's NOT a Revolution Yet
- 📊 Technical Architecture and Models
- 🔧 My 48+ Hours of Testing (with Real Failures)
- ⚠️ Shortcomings and Pain Points (Very Honestly)
- 🚀 Comparison with Cursor, Copilot, Devin, Aider
- 💼 Real Cases from the First 11 Days (Mostly Negative)
- 🤖 Integration with GCP and Tools
- 📉 Future of Development: Realistic Forecasts for 2026–2027
- ❓ FAQ—Unvarnished
- ✅ Conclusions and Recommendations
🎯 What is Google Antigravity and Why It's NOT a Revolution Yet (Honest Analysis After 11 Days of Hype) 🤔
Google Antigravity is a new agent-first IDE (agent-oriented development environment) that Google released on November 18, 2025, along with Gemini 3 Pro. Essentially, it's a fork of Visual Studio Code that has been completely rebuilt for autonomous AI agents. Google paid $2.4 billion for the technology and team of the startup Windsurf (not a full acquisition, but a deep collaboration) to create a tool where the developer no longer writes code manually, but manages agents.
On paper, everything looks like a breakthrough 🔥:
- 🛠️ Full Agent Access: to the file editor, terminal, and built-in browser (via Gemini Computer Use)
- 🧠 Autonomous Planning: the agent itself breaks the task down into 50+ steps, without your participation
- 📹 Artifacts—the best feature: after execution, you get a full report with a plan, git diff, terminal logs, test results, and video of the work in the browser (the agent records how it clicks and tests the UI)
- 💬 Manager Surface—a separate chat interface where you set the task in natural language ("Make a Todo-app with Supabase, authorization, and dark mode"), and the agent does everything itself
- ☁️ Deep integration with GCP (Cloud Run, GKE, Cloud Build)—automatic deployment
- 🤖 Support for multiple models: Gemini 3 Pro (1M context, Deep Think), Claude Sonnet 4.5, GPT-4.1 OSS
Sounds like the future, right? In the first few days, many people were shouting, "This is the end of coding!" and "It will replace everyone in 2026!" But after 11 days of real use by the community (including my 48+ hours of testing), the picture is quite different 😓.
Why it's NOT a revolution yet:
- ⏳ Strict Quotas and Freezes: the preview is free, but the quotas are exhausted in 20–40 minutes. Then wait 5 hours. "Model provider overload" is the most common error.
- 🔴 Critical Security Holes: backdoors were found in the first few days through config and data exfiltration (the agent steals .env without warning). Google has partially closed it, but the risk remains high.
- 🐛 Bugs Everywhere: sessions break, artifacts are forgotten, VS Code extensions glitch or don't work, search is slow, Enter in the chat immediately submits the prompt.
- 😩 UI/UX Frustration: the interface is cluttered, the chat merges with the logs, for beginners—complete chaos.
- ⚠️ Works Only on Simple Tasks: Todo-app, CLI script, landing page—okay. Anything >5–10k lines or complex logic—the agent starts hallucinating, ignoring edge cases, and breaking code.
Section Conclusion 🚨: Antigravity is the most ambitious agent tool of 2025 with several really cool features (especially Artifacts with video 🤩), but as of November 2025, it's a raw beta that was released too early. For simple prototypes and vibe-coding—yes, it's cool. For real work—so far, it's complete frustration and risk. The revolution has been postponed until the December–January patches. In the meantime, Cursor remains king 👑.
📊 Technical Architecture and Models: How Antigravity Works Under the Hood (and Why It's Still Raw) 🛠️
Google Antigravity is a fork of Visual Studio Code, completely rebuilt for an agent-first approach. The main engine is Gemini 3 Pro with a context of 1 million tokens and Deep Think mode for multi-stage planning (up to 50+ steps). There are two interfaces:
- 🖥️ Editor View—classic editor with autocompletion and chat
- 💬 Manager Surface—a separate chat where you set the task in natural language, and the agents coordinate all the work
Agents get full access: to files, the terminal, and the built-in browser (based on Gemini Computer Use). They independently plan, write code, run tests, fix bugs, and even deploy to GCP (Cloud Run, GKE, Cloud Build). Each task ends with an Artifact—this is a really cool feature 🔥: a full report with a plan, git diff, logs, test results, and video of the work in the browser.
Support for multi-models (Gemini, Claude Sonnet 4.5, GPT-4.1 OSS) and deep integration with GCP make the architecture flexible on paper. But in practice (as of 11/29/2025), everything is spoiled by:
- ⚠️ Constant server overloads ("model provider overload" is the most common error)
- ⏳ Strict quotas: enough for 20–40 minutes of intensive work, then wait 5 hours
- 🐛 Bugs with context between sessions, forgetting artifacts, crashes on large projects
- 🔴 Critical security vulnerabilities: prompt-injection, backdoor through mcp_config.json, data exfiltration (already confirmed by Aaron Portnoy from Mindgard and Google)
- 😩 Cluttered UI, limited support for VS Code extensions (Prettier, ESLint often glitch)
Overall, 65–70% of reviews are positive for potential and Artifacts, but 30–35% are pure frustration: "buggy as hell," "hits quota limit every 20 minutes," "not for real work."
📈 Table of Supported Models (as of 11/29/2025)
| Model | Context | Speed | Quality | Access | Best For | Headaches 🔴 |
|---|---|---|---|---|---|---|
| Gemini 3 Pro (Deep Think) | 1,000,000 | Average (10–50 min per task, often freezes) | Good for planning, but hallucinations + security holes | Free (quotas every 5 hours) | Prototypes with UI/browser | Overload, rapid quota depletion, data leakage via prompt-injection |
| Claude Sonnet 4.5 | 200,000 | Fast (2–10 min) | Most stable for refactoring | Free | Quick features, CLI | Smaller context, not always available due to overload |
| GPT-4.1 OSS | 128,000 | Fast (5–15 min) | Stable logic, but boring | Free | Legacy code | Integration issues, often the worst diff quality |
📊 Pros vs Cons (Honestly, Without Rose-Colored Glasses)
| Pros ✅ | Cons 🔴 |
|---|---|
| Free access to top models | Strict quotas—really 20–40 min of work |
| Artifacts with video—top for verification | Critical security holes (backdoor, exfiltration) |
| Deep Think for complex planning | Frequent freezes and session crashes |
| Built-in browser for tests | UI cluttered, extensions glitch |
| Multi-models | Instability on projects >10k lines |
Conclusion 🤷♂️: The architecture is cosmic on paper, but the execution is a beta version of Windows 95: the idea is 🔥, but the reality is crashes, quotas, and the fear of losing the .env file. Ideal only for prototypes up to 1k lines. Anything more is pain, suffering, and manual edits. We're waiting for patches in December.
