NEW Antigravity 2.0 + Agent OS is INSANE!

Ajouté : 2026-05-25

[00:00:00]New anti-gravity 2.0 plus agent OS is insane. What if the AI tool you just learned has already changed? Why is Google quietly rebuilding the whole way agents work? Is your current setup about to feel completely outdated? What if one update could break your entire workflow?

[00:00:12]And why are smart builders pairing this with a second tool right now? Hey, I'm the digital avatar of Julian Goldie and I help people learn and actually use AI tools in their work. In this video, I'm breaking down everything new in Google anti-gravity 2.0. Why pairing it with an agent OS like Hermes changes the game, the features people are getting wrong, and the simple beginner setup that actually works. Stick with me because the part most creators are missing comes near the end. Let's get into it. Google anti-gravity 2.0 launched at Google IO 2026 on May 19th and it is not just a normal update. Google changed the whole shape of the tool. The old version felt like a coding workspace with an AI agent bolted on. The new version feels like a full agent platform. The biggest change is that the built-in Visual Studio Code style editor and terminal are no longer the center of the experience. The tool now feels more like a standalone agent app focused on chatting with agents, managing projects, and running automations. Some people love this. Some people hate it. Anti-gravity is no longer just an editor. It is one piece of a bigger agent system. So, what is actually inside anti-gravity 2.0? Google split it into five surfaces. There is the desktop app, the new anti-gravity CLI, the anti-gravity SDK, a managed agents feature inside the Gemini API, and an enterprise agent platform for bigger teams. The desktop app is where most people will live. It can now spawn dynamic sub-agents that work in parallel so the main agent can spin up helpers to handle different parts of a job at the same time. It also has scheduled background tasks, native voice commands, and deeper integrations with Google AI Studio, Android, and Firebase. The anti-gravity CLI fully replaces the old Gemini CLI. So, if you were using that, the path is gone. The SDK lets you build custom agents on the same harness Google uses internally. And the managed agents feature gives your agents an isolated Linux environment to run in, which is a big deal for safety. For models, anti-gravity 2.0 supports Gemini 3 Pro with generous limits, Anthropic's Claude Sonnet 4.5, and OpenAI's open source models. So, you are not locked into one provider. Pricing-wise, there is a new AI Ultra tier at $100 per month that gives you five times the usage limits of the Pro plan, which matters because agent workflows burn through tokens fast. But, here is the part most people are missing. Anti-gravity 2.0 on its own is not enough. The tool is more powerful when it sits inside an agent OS. An agent OS is basically a command center for all your AI tools, agents, files, memory, and automations. Instead of opening Anti-gravity in one window, Hermes in another tab, Claude somewhere else, and a separate terminal beside it, everything can be organized inside one system. Agents get messy fast. Without a command center, you lose track of what is happening, where the outputs went, and which tool did which task. This is where Hermes comes in. Hermes handles agent workflows, memory, automation, and computer use. Anti-gravity 2.0 handles agent execution from a different angle.

[00:02:41]Together, the whole stack gets stronger.

[00:02:43]This could be used to build a full agent OS that powers content creation for the AI Profit Boardroom. You could have Hermes manage the memory and context, while Anti-gravity 2.0 runs sub-agents that draft videos, design thumbnails, and write captions in parallel. That kind of system makes it way easier to keep producing content that brings the right people into the AI Profit Boardroom. Now, let's talk about something a lot of people are still confused about, the NA10 question. A lot of viewers ask if NAN is still worth using now that Hermes can run faster automations, and Anti-gravity 2.0 can spawn sub-agents. The honest answer is that it depends on the job. AN is still useful for visual workflows, connecting apps with clear triggers, and managing automations across services. For fast agent-style automations, where the AI is making decisions, Hermes can move quicker. And for parallel agent execution, Anti-gravity 2.0 is now built for that. The smart move is to match the tool to the workflow, not pick one and ignore the others. Now, let's talk about something that breaks most AI workflows, context. When agents work with long documents, lots of files, or extended conversations, the context window fills up. Once that happens, quality drops.

[00:03:41]The agent forgets earlier details and makes weaker decisions. This is not just an Anti-gravity issue. It happens with every AI tool. The fix is to design the workflow better. Split long tasks into chunks. Use compacting where the tool supports it. Pass summaries between steps instead of dumping everything into one giant thread. Pick a model with a larger context window for the heavy parts. Claude is often a strong pick for long documents because it handles reasoning over big inputs well. Big effects is to store your important context outside the chat. That is where a memory system comes in. Tools like Obsidian let you keep your notes, workflows, instructions, and examples in a local knowledge base. When your agents can read from that, they stop guessing and start working with real context. A lot of people ask if Notebook LM is better than Obsidian for this. Notebook LM is great for quick research and summarizing documents. But for long-term agent memory, Obsidian wins. It's local, it is yours, and it connects much more easily to agent workflows without depending on a cloud product that might change next year. Imagine running this act to build a personal context engine for the AI Profit Boardroom. You could load every coaching call note, every member question, and every workflow into Obsidian, then let Hermes and Anti-Gravity 2.0 read from it. That means every piece of content you create for the AI Profit Boardroom would already match your voice, your process, and the topics members actually care about. Now, let's talk about real use cases for this whole setup. The first is SEO and website work.

[00:04:53]Has a lot of repeated steps. Keyword research, content creation, page building, formatting, publishing, tracking. A single chatbot helps with one piece of that. An agent system connects more of it. With Anti-Gravity 2.0 spawning sub-agents and Hermes handling memory, you can run a full content pipeline that drafts articles, builds pages, and pushes updates. Second is site ranking and deployment. If you are building multiple sites, agent work scales much faster than doing it by hand. It's handle the setup, content, internal linking, and basic on-page work. You still review the output. Third is Twitter and social growth. Agents can draft posts, plan threads, schedule content, and respond to early comments.

[00:05:26]Memory in place, the agent learns your voice over time. Fourth is AI Avatar marketing. This is what I'm doing right now. Avatars can record videos, run channels, and turn one script into many formats. If you want to actually learn how to set all of this up step by step, I want to mention something that is built for exactly this moment. Inside the AI Profit Boardroom, there are full walk-throughs on Google Anti-Gravity 2.0, the Hermes setup, how to build your own Agent OS, and how to connect a memory layer using Obsidian. There are live coaching calls where you can ask questions about your specific setup.

[00:05:53]There are road maps that walk you through the first 30 days of building agent workflows. There are tutorials on sub-agents, parallel execution, and connecting these tools together. If you are watching this video and thinking that you want help putting it all into one working system, the AI Profit Boardroom was built for exactly that.

[00:06:07]Now, let's talk about beginners because this is where most people get stuck. T Gravity 2.0 can feel overwhelming if you try to build everything at once. Biggest beginner mistake is opening the tool, seeing all the options, and trying to build a huge system on day one. That creates stress and usually breaks.

[00:06:20]Better approach is to focus on one automation per week. Pick one repeated task. Build the simplest version. Review what happens. Prove it. Then move to the next workflow. A simple landing page workflow, a content draft workflow, or a file organization workflow is enough to start. You do not need a giant agent system on day one. You need one useful workflow that proves the setup works.

[00:06:39]Then you build from there. The other beginner tip is to test on a budget first. You do not need to jump to the $100 Ultra tier on day one. The Pro plan covers most early workflows. You can also run open-source models locally using tools like Ollama and LM Studio.

[00:06:51]Gemma is a solid lightweight pick if you want a smaller model that still performs well. And if you are coming from Open Claw, the migration to Hermes is straightforward. Hermes is faster and integrates more cleanly with newer agent tools like Anti-Gravity 2.0. So, if you have been waiting to switch, this is a good moment. Now, let me give you the bigger lesson from all of this. T Gravity 2.0 is a reminder that systems beat random tools. A new AI tool can look exciting for a few days.

[00:07:12]Update arrives. The interface changes.

[00:07:14]Feature disappears. Another platform becomes popular. If your strategy is just chasing tools, you will always feel behind. A system is different. Your Agent OS connects different tools. Your memory layer keeps your context safe.

[00:07:24]Your workflows keep running even when one interface changes. The future of AI is not about better prompts. It is about better systems. You become the person designing the system. You decide what the agents know, which tools they use, and what gets automated. Anti-Gravity 2.0 is one piece of that future. Hermes is another. Obsidian is another. Claude is another. None of them are the whole answer. The answer is the system you build around them. And one more thing before I wrap up, let's keep a human review step. The goal is not blind automation. It's controlled leverage.

[00:07:50]You get the speed without losing standards. If you want the full process, SOPs, and 100 plus AI use cases like this one, join the AI Success Lab. Links in the comments and description. You'll get all the video notes from there plus access to our community of 58,000 members who are crushing it with AI. And if you are about to actually go and test Anti-Gravity 2.0 with Hermes, here is the thing. You will hit problems. The interface will feel new. Sub-agents will misfire on your first few runs. Your context will overflow at the wrong time.

[00:08:14]Your memory layer will need cleaning up.

[00:08:16]That is normal. That is part of building a real system. Inside the AI Profit Boardroom, there are coaching calls where you can bring those exact problems and get them solved live. There are tutorials that walk through sub-agent setups, parallel agent workflows, and how to connect Anti-Gravity 2.0 to your Agent OS without breaking anything.

[00:08:31]There are roadmaps that show you what to build first, second, and third, so you stop guessing. And there are prompt libraries built around these exact tools, so you are not starting from a blank page. If you want to skip the trial and error and go straight to a working setup, head to aiprofitboardroom.com.