NEW Gemini CLI Update is INSANE! 🤯

Key Takeaways

New Gemini CLI update is insane. Before you give AI a task, it starts coding immediately. No questions, no research, just goes after. You give AI the same task, it stops, reads your entire codebase first, asks you the right questions, builds the full plan, shows it to you, waits for your approval, then codes. That's the difference between AI coding before this update and after it. Google just shipped plan mode for Gemini CLI and it genuinely changes how you work with AI on real projects. I'm going to break down exactly what it does and how to use it. I'm Julian. I make videos helping people learn and actually implement AI tools. Let's get into it. So, first, well, what even is Gemini CLI? It's Google's free open-source AI tool that lives in your terminal. one install command, mpm install, gleemini cli, and you've got an AI agent that can read your files, write code, run commands, search the web, all from the command line. It runs on Gemini 3, which is now the default for everyone. And there's a free tier, and sign in with your Google account, and you get up to a,000 requests a day. No cost to get started. Now, let's talk about the problem it's solving. Every developer who's used AI coding tools has hit this wall. You ask it to do something non-trivial, it dives straight in and somewhere in the middle it makes a wrong assumption, misreads a dependency, overwrites the wrong file, builds the right thing in the wrong place. You catch it 10 minutes later, or worse, you don't catch it until something breaks in production. The reason this keeps happening isn't that the AI is bad at coding. It's that why AI skips the thinking step. A senior engineer would never start writing code the second they heard a requirement. They'd read the existing code first, think through the approach, maybe ask a few questions, then start. AI tools have been skipping all of that. Plan mode is how Gemini CLI fixes it. When you activate plan mode, the AI locks itself into a readonly state, not a suggestion, actually enforced. Write tools are blocked at the policy level. The AI literally cannot modify your files. What it can do is explore. It reads through your codebase, searches for relevant patterns, looks things up on the web, and builds a full picture of what actually needs to happen. Then it writes a complete implementation plan as a markdown file and hands it to you for review. Look it over. You can edit it directly. Press CL to open it in your own editor, rewrite steps, reorder things, leave comments. Gemini CLI picks up your changes and refineses the plan. When you're happy with it, you approve it. That's when implementation starts. Nothing gets touched until you say so. That's the guarantee. And here's something smart happening under the hood. During the planning phase, Gemini CLI automatically roots to the pro model, the higher reasoning one built for architecture decisions. Once you approve the plan and implementation kicks off, it switches to the flash model, which is faster for execution. You get the right model for each phase without touching any settings. So let me walk through what the planning phase actually looks like in practice. You enter plan mode, either type to plan, press shift per tab, or just tell it naturally like start a plan for this feature and it switches on its own. Then you describe what you want to do. Let's say you want to add a caching layer to an existing API. Gemini CLI doesn't start coding and it starts reading. It goes through your project structure, finds the relevant files, traces the request flow, checks what's already there. Then it might stop and ask you something. Should this be in memory or redispacked? Do you want it applied globally or per route? You answer. It continues building the picture. The codebase investigator sub agent, one of the built-in research agents actively explores your workspace during this phase to surface context. the AI might otherwise miss. It's like having a second pair of eyes going through the code while the planner thinks. Once it has enough, it writes the plan step by step, file by file. You can read exactly what it intends to do before it does anything. You can push back on specific steps. You can change the approach entirely and then you approve it. That kind of control is what's been missing from AI coding tools. There's a point in learning any new tool where you hit a wall and can't tell if the problem is you or the tool. When I was getting deeper into Gemini CLI, I kept running into that. That's when I found AI Profit Boardroom. Over 2,000 members, all focused on learning AI tools, and sharing what actually works in practice, real use cases, real implementations. It helped me figure out which workflows were actually worth my time. If you're serious about leveling up with AI, the link is in the description. Now, let's talk about what just shipped. Version 0.33 came out March 11th, 2026 and brought three solid additions to plan mode. Specifically, the codebase investigator sub agent got expanded capabilities during the planning phase, so the research step is more thorough. There's new annotation support. You can now leave feedback directly inside the plan file. And Gemini CLI reads and responds to it, which makes the back and forth much tighter. And there's a new plan copy command so you can grab the approved planer and take it wherever you need. Version 0.32 out March 3 added the external editor integration of the cultural sex flow I mentioned and improved how plan mode handles complex tasks with a lot of moving parts. The team has been shipping updates every couple of weeks. Plan mode is clearly the focus right now. Here's the bigger picture on why this matters. Barrier to using AI on serious work has always been trust. You can use AI to write a quick utility function and it's fine. But use it on a feature that touches 10 files in a codebase you've been building for two years. That's where it gets scary. One wrong assumption as you're debugging for hours. Plan mode removes that barrier because you see everything before it happens. The AI can't act without your approval. The plan is written down. You can read it, edit it, reject it. You're not hoping the AI understood you. You can see that it did or correct it if it didn't. that makes it practical for the work that actually matters. Legacy code, shared repositories, features with real dependencies, the hard stuff, the AI tools have been too unpredictable to touch. And if you're working in a team, Gemini CLI supports enterprise policy configuration. Admins can lock down which tools are allowed, enforce specific authentication, and control how the tool behaves across the team. Plan mode isn't just a solo developer feature. Getting started is straightforward. Install with npm install ja Google gemini class. Sign in with your Google account. Navigate into your project and run Gemini. Type plan to activate plan mode. Describe your task and let it do the research. Review the plan it produces. Edit anything you want. Approve. Done. Full docs at geminacite.com.docs. If this was helpful, drop a like. It makes a real difference. And if you're using plan mode already, tell me in the comments what you're working on. I read every reply. If you want to go deeper on AI tools and actually get them working in your day-to-day, check out AI Profit Boardroom. Over 2,000 people sharing what's actually working with AI. Real workflows, real results, no fluff, what tools are worth it, what to skip, what actually saves time. I found it genuinely useful for staying on top of how fast this space moves. Link in the description. And 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, plus access to our community of 58,000 members who are crushing it with AI. See you in the next one.