NEW Gemini CLI 2.0 Update is INSANE (FREE!)

Today I'm going to show you Google's brand new Gemini CLI update and it's absolutely insane what they just released for free. We're talking about AI that now lives inside your VS Code editor. It knows what files you have open. It can see your selected text and it can make changes right where you need them. This isn't just some basic chatbot anymore. This is like having a genius coding partner that never sleeps and costs you 0. Look, I've been tracking AI updates for years now, and this Gemini CLI update just dropped, and it's making me rethink everything about how we code. Because what Google just did is they took their most powerful AI model, Gemini 2. 5 Pro, and they gave it eyes into your actual workspace. Not just access to your files, not just the ability to read your code, but realtime awareness of exactly what you're working on at any given moment. And here's the crazy part, it's completely free. We're talking about 60 requests per minute and 1,000 requests per day at zero cost. To put that in perspective, that's more free usage than most paid AI tools give you. And we're talking about Gemini 2. 5 Pro here, the same model that costs money everywhere else. But before I dive into the technical stuff, let me tell you what this really means for your workflow. Imagine you're working on a React component. You select a piece of code that's giving you trouble. Gemini CLI doesn't just see that code. It sees your entire project structure. It knows what other components you have. It understands your file organization. And it can suggest fixes that actually make sense in the context of your whole application. That's the difference between this update and everything else that came before it. Context awareness, real context awareness. So, let me break down what's actually new in this update. First, the VS Code integration is next level. You install the companion extension with one command. Type slash ID install in your terminal and boom, Gemini CLI is now connected to your VS Code workspace. It can see what files you have open. It can access selected text and it can make intelligent suggestions based on exactly what you're looking at. That's why I created the AI profit boardroom is where over 1,000 business owners are learning how to use AI tools like one 2. 2 plus to scale their businesses and save hundreds of hours with automation. Inside the boardroom, we break down exactly how to write prompts that create professional results. We share case studies of businesses making real money with AI video content, and we give you the exact systems and processes to implement this in your own business. The members are seeing incredible results. Some are cutting their video production costs by 90%. Others are creating content 10 times faster than before, and many are discovering new revenue streams they never thought possible. But here's where it gets really interesting. They added something called native in editor diffing. So when Gemini suggests changes to your code, you don't have to copy and paste anything. You get a visual diff right in your editor. Green for additions, red for deletions, you can see exactly what's changing before you accept it. And if you like the changes, you click accept and it's done. The second big thing is GitHub actions integration. This is where things get scary good because now Gemini CLI can work as an autonomous agent in your GitHub repositories. It can automatically triage issues. It can review pull request. And here's the part that blew my mind. You can mention atge Gemini CLI in any issue or pull request and delegate tasks to it. Tell it to write tests for a bug. Tell it to implement suggested changes. Tell it to brainstorm solutions and it just does it. This isn't some basic automation either. We're talking about an AI that understands your codebase architecture. It knows your dependencies. It understands your coding patterns and it can make changes across multiple files to implement complex features from a single prompt. The third major update is the model context protocol enhancements. MCP lets you extend Gemini CLI with custom tools and integrations and they just made it way easier to manage. You can now add, remove, and list MCP servers right from the command line. No more editing config files manually. And they added support for multimodal content. So your tools can return text, images, whatever you need. But let me tell you about the free usage limits because this is where Google just destroyed the competition. Most AI coding tools give you maybe 50 requests per day for free. Some give you 100 if you're lucky. Google is giving you 1,000 requests per day and 60 requests per minute. That means you can literally have Gemini CLI helping you code all day long without hitting any limits. And we're not talking about some dumb down version either. This is Gemini 2. 5 Pro, the same model that powers Google's paid services with a 1 million token context window. That means it can understand massive code bases, entire applications, and still give you relevant suggestions. Now, let me show you how this actually works in practice. You start Gemini CLI in your VS Code integrated terminal. Run the / ID install command to set up the connection. Then toggle integration with / ID enable. From that point on, Gemini

CLI knows everything about your workspace. Let's say you're working on a bug fix. You select the problematic code. Gemini CLI sees not just that code, but the entire file, the project structure, the dependencies, everything. When you ask for help, it gives you suggestions that actually work in your specific context. Or maybe you're implementing a new feature. You describe what you want to build. Gemini CLI analyzes your existing codebase, understands your patterns, and suggests implementation approaches that fit your architecture. And because of the GitHub actions integration, it can even create pulse requests with the implementation. The terminal setup is also incredibly smart. Now, they added a /terminal setup command that automatically configures key bindings for multi-line input in VS Code, cursor, and windsurf terminals. So, you get shift plus enter and cruel plus enter functionality working perfectly. No more fighting with terminal input when you want to write longer prompts. And speaking of prompts, they added a new / settings command that gives you a userfriendly settings editor right in the CLI. You can customize everything about how Gemini CLI works without diving into config files. The error handling got a massive upgrade, too. Better handling for tool errors, schema errors, path processing. They even added loop detection to prevent infinite loops and memory leak prevention in the logging system. This is enterprisegrade reliability in a free tool. But here's what really excites me about this update. The open source nature of it. The entire codebase is available on GitHub under Apache 2. 0 license. That means you can inspect the code, understand how it works, verify security, and contribute improvements. Google is betting big on community development here and they're building on emerging standards like MCP system prompts via Gemini. m MD files and settings for both personal and team configuration. This isn't just a tool, it's a platform that other developers can build on. The extensibility is insane. You can create custom extensions, add new tools, integrate with existing workflows, automate complex tasks, and because it supports OORF 2. 0, zero, you can securely connect to remote servers and services. Now, let me talk about the GitHub actions piece more because this is revolutionary. You set it up once with the / setup GitHub command. From then on, Gemini CLI becomes a team member in your repository. It can automatically handle issue triage, labeling, and prioritization. It reviews pull requests for quality, style, and correctness. And it works asynchronously in the background using the full context of your project. But the ondemand collaboration is where it gets really powerful. You mention at Gemini client any issue or pull request and give it a task. Write tests for this bug. Implement the changes suggested above. Brainstorm alternative solutions. Fix this well-defined bug and it just handles it. The security model is enterprisegrade too. They support workload identity federation for credentialless authentication. You get granular control with command allow listing. Complete transparency with open telemetry integration for logging and monitoring. You're always in control of what the AI can and can't do. And here's something that will save you hours every week. The built-in tools are incredible. Google search grounding so you can fetch web pages and get real-time context. File operations for reading, writing, and searching code. Shell command execution for automating tasks. Web fetching for pulling external resources. all integrated seamlessly into the AI workflow. The workspace context awareness is the game changer though. When you connect VS Code to Gemini CLI, it becomes aware of your open files, selected text, project structure, everything. The suggestions aren't generic. They're tailored to exactly what you're working on. I tested this with a complex React application. Multiple components, shared state, custom hooks, the whole thing. I selected a piece of code that was causing performance issues. asked Gemini CLI for optimization suggestions and it didn't just suggest generic React optimizations. It suggested specific changes that worked with my exact component structure, my state management approach, my naming conventions. It understood the context. That's the difference between this and tools like GitHub Copilot or other AI assistants. Those tools are great for autocomplete and basic suggestions, but they don't really understand your project. Gemini CLI with VS Code integration actually comprehends your workspace. The diffing capabilities make code review effortless, too. When Gemini suggest changes, you see exactly what's being modified. You can review line by line, accept or reject specific changes, and maintain full control over your codebase. No more copyping AI suggestions and hoping they work. And because it's integrated with Gemini Code Assist, you get the same AI assistance in both your terminal and your IDE. consistent experience, shared knowledge, seamless workflow. Now, if you're serious about scaling your business with AI automation, you need to check out my AI profit boardroom. This is where over 1,000 members are learning to use tools like Gemini CLI to get more customers

and save hundreds of hours with AI automation. I share the exact strategies, workflows, and automations that are working right now. The performance improvements in this update are substantial, too. They optimize file search with async operations for non-blocking performance. The CLI layout automatically adapts to different terminal widths, faster loading, better responsiveness, smoother experience overall, and the documentation got a complete overhaul. They added guides for IDE integration, keyboard shortcuts, the Jitinor style Gemini ignore files, everything you need to get up and running quickly. The configuration options are extensive now. You can control line numbers, encode blocks, configure memory loading behavior, customize themes with semantic colors, and they added support for VS Code like editors beyond just VS Code. Cursor, Windsurf, even Z editor integration. But let me tell you about the agent mode capabilities because this is where we see the future of coding. Agent mode acts like an AI pair programmer. It analyzes your entire codebase, not just the open file. It understands your application architecture, dependencies, coding patterns, relationships between components, everything. When you give it a complex task like implementing a new feature or performing a large refactor, it creates a plan first, shows you exactly what it's going to do, you can edit the plan, ask for changes, approve or deny specific steps. Then it executes the plan across multiple files, making coordinated changes that actually work together. This collaborative approach combines AI power with your expertise. You stay in control while delegating the tedious implementation work. The result is better code and a more efficient workflow. The multimodal support opens up even more possibilities. Tools can return not just text but images, diagrams, charts, whatever helps communicate the solution. And the prompt as commands feature lets you expose predefined prompts from MCP servers as new /comands in the CLI. Realtime troubleshooting is incredibly powerful, too. Gemini CLI can access your project files, run shell commands, search for patterns, analyze logs, and suggest fixes all in one conversation. No more switching between different tools and losing context. The quotas are designed so you rarely hit limits during development. 60 requests per minute means you can have rapid back and forth conversations with the AI. 1,000 requests per day means allday coding assistance. And if you need more, you can upgrade to Google AI Studio or Vert. Ex AI for usage based billing. For teams, the enterprise features are solid. Workload identity federation eliminates API key management risks. Granular permissions let you implement lease privilege access. Open telemetry integration gives you full observability into AI usage patterns. The checkpoint system is brilliant for experimentation. Before Gemini CLI modifies files, it can save a project snapshot. If something goes wrong, you can restore to any previous checkpoint. No more fear of AI breaking your code. File referencing is intuitive. You can reference files, directories, images, PDFs, audio, video, whatever you need for context. The CLI respects JIT ignore and Gemini ignore files automatically. Clean, organized, predictable behavior. And the community aspect is exciting. Google is actively encouraging contributions, bug reports, feature suggestions, security improvements, code contributions, everything is welcome. This tool is going to evolve rapidly based on real developer needs. For SEO professionals like myself, the content generation capabilities are incredible. You can use Gemini CLI for research, writing, analysis, reporting, all with the same context awareness, and tool integration. It's not just for developers. The update cycle is aggressive, too. Preview releases every Tuesday night. Stable releases weekly, daily releases from the main branch. This is rapid development with real user feedback driving improvements. Integration with Google Cloud Services is seamless. if you're already in that ecosystem, but it works great with any cloud provider, any hosting setup, any development environment. No vendor lock in. The learning curve is minimal if you're already comfortable with command line tools. The slash commands are intuitive. The help system is comprehensive, and the documentation is actually readable. The collaboration features work great for remote teams, too. Multiple developers can use the same GitHub actions workflows, share MCP server configurations, build on each other's extensions, distributed development with AI assistance, and because Google is betting big on this, you can expect continued investment, feature development, performance improvements, and ecosystem growth. This isn't a side project that might get cancelled. This is core to Google's AI strategy. If you want to book a free SEO strategy session to see how AI tools like this can help scale your business, check the link in the comments and description. We're helping companies implement AI workflows that save hundreds of hours and drive real business results. And remember, if you want access to all the resources, tutorials, and community discussion around AI tools like this, check out the AI Money Lab link in the comments and description. Over 20,000 members are already using these strategies to scale

their businesses with AI automation. That's it for today's update. The AI revolution is accelerating and tools like Gemini CLI are leading the charge. Stay ahead of the curve, implement these tools early, and watch your productivity sore. Thanks for watching and I'll see you in the next