Video Title: Here Is How to Vibe Code Large Scale Projects
Video ID: k9fPAzS5_Kw
Video URL: https://www.youtube.com/watch?v=k9fPAzS5_Kw
Export Date: 2025-11-06 20:42:44
Channel: AI LABS
Format: plain
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Planex: The Ultimate Command Line Coding Agent for Large-Scale Projects

If you’ve ever struggled with AI coding assistants choking on large projects due to context size limitations, you’re not alone. Popular tools like Cursor often hit a wall when dealing with big codebases, causing frustration and project disruptions. But what if there was a smarter, more resilient way to manage AI-assisted coding for massive projects?

Enter Planex — a powerful command line coding agent designed specifically for large-scale projects. In this post, we’ll explore what makes Planex stand out, how to install and run it locally, and see it in action through a Swift app demo.
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What is Planex?

Planex is a command line AI coding assistant built to handle huge codebases that typically overwhelm other tools. Here are some of its standout features:
• Massive Context Handling: Supports up to 2 million tokens of context directly and can index directories with 20 million tokens or more.
• Advanced Code Navigation: Utilizes tree sitter project maps, a cutting-edge feature in code editors that helps it understand and navigate complex code structures.
• Multi-Model Support: Automatically selects the best AI model available through the Open Router API, ensuring resilience and flexibility.
• Multiple Operation Modes: Offers cloud-based usage (with or without your own API keys) and a self-hosted local mode.

This combination makes Planex uniquely suited for developers dealing with large, complex codebases who want an AI partner that truly understands their project.
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How to Install Planex Locally

If you want full control and to run Planex on your own machine, the local mode is the way to go. Here’s a quick overview of the setup process:

Prerequisites
• Windows users: You must have Windows Subsystem for Linux (WSL) installed.
• Docker: Ensure Docker is installed and running on your system.

Steps
• Clone the GitHub Repository: Start by cloning the Planex repo to your local machine.
• Start the Local Server: Use the provided command to launch the Planex server locally. Docker must be running, or you’ll encounter errors.
• Install the CLI: Open a new terminal and install the Planex command line interface (CLI). You may need to enter your password for permissions.
• Sign In and Configure: Sign into Planex in local mode by running the sign-in command. Confirm the default host address and create your local user.
• Set Your API Keys: Export your Open Router API key and OpenAI API key — these are necessary for Planex to function.
• Initialize Planex in Your Project: Navigate to your project directory and initialize Planex using a simple command. You’re now ready to interact with Planex!
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Using Planex: Chat Mode and Tell Mode

Planex offers two primary modes to interact with your code:
• Chat Mode: Start by brainstorming your ideas with Planex. You don’t need a fully fleshed-out plan or deep knowledge of your tech stack. Planex will parse your existing project files and understand the architecture, components, and workflows.
• Tell Mode: Once you’re ready to build, switch to tell mode. Planex breaks down your main task into smaller, manageable steps and executes them one by one. All changes are made inside a sandbox environment so you can review, approve, or reject modifications before applying them to your actual codebase.

Additional Features
• Debugging: If errors occur during execution, Planex offers debugging options, including a full auto mode that attempts to fix issues automatically. Be cautious, as this mode can consume a lot of tokens and API credits.
• Command Execution: You can run shell commands and automate setups within Planex.
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Planex in Action: Swift App Demo

To demonstrate Planex’s capabilities, let’s look at a real-world example using a Mac OS menu bar app built with Swift and SwiftUI.
• Project Understanding: After pointing Planex to the project, it instantly recognized the app type, architecture, and key components.
• UI Improvement Prompt: I asked Planex to improve the app’s UI — a challenging task for many AI models due to Swift’s complexity.
• Step-by-Step Implementation: Planex reasoned through the project, formulated a plan, and asked to switch to tell mode for implementation.
• Sandboxed Changes: It created a new script to build the app rather than modifying main files initially, then applied changes after approval.
• Building and Debugging: Planex built the app, identified minor build issues, and used full auto debug mode to fix them without manual intervention.
• Result: The updated app now includes the ability to change the accent color dynamically using native Mac OS and SwiftUI components. The UI enhancement was successful, showcasing Planex’s advanced capabilities.
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Why Planex is a Game-Changer
• Handles Large Projects: With token limits far exceeding other tools, Planex is perfect for real-world, sizable codebases.
• Flexible Deployment: Use it in the cloud or run it locally with your own API keys for privacy and control.
• Smart Multi-Model Selection: Automatically picks the best AI model for each task.
• Safe Sandbox Environment: Review changes before applying them, reducing the risk of breaking your code.
• Effective Debugging: Auto debug mode helps fix issues quickly and efficiently.
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Final Thoughts

Planex represents a significant leap forward in AI-assisted coding for developers working on large-scale projects. Its ability to understand massive codebases, break down complex tasks, and safely implement changes makes it a compelling choice for professional developers.

If you’re interested in trying Planex yourself, check out their GitHub repository for detailed installation guides and documentation.
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Thanks for reading, and happy coding with Planex!