The video showcases the new agent mode in Visual Studio Code, which enables AI to autonomously perform complex development tasks such as setting up projects, installing dependencies, and building full applications with minimal user input. It highlights how this mode, combined with tools like custom instructions, project requirements documents, and external data sources, significantly enhances productivity and automates intricate coding workflows.
The video introduces the latest AI features in Visual Studio Code, focusing on the new agent mode, which significantly enhances the development experience. The presenter explains how to enable agent mode through user settings and demonstrates its three main functions: ask, edit, and agent. Ask mode provides standard AI chat responses, while edit mode allows the AI to modify files based on prompts. Agent mode, however, is more autonomous, enabling the AI to perform complex tasks such as installing dependencies, modifying configuration files, and even starting development servers, mimicking a developer’s workflow.
The presenter showcases how agent mode can be used to automate the process of setting up Tailwind CSS in an AstroJS project. By providing detailed prompts and using tools like the fetch tool to read documentation directly from web pages, the AI can follow instructions accurately. It modifies project files, installs dependencies, and even starts the dev server, all with minimal user intervention. The demonstration emphasizes the importance of providing context and instructions to the AI, especially since models have training cutoff dates and may not have the latest information.
Further, the video explores how to prepare the AI for building a complete application by creating a project requirements document (PRD) and custom instructions. These documents outline the app’s purpose, features, and best practices, guiding the AI in development. The presenter also discusses integrating a PostgreSQL database using MCP (Model Context Protocol) servers, which act as bridges between VS Code and external data sources. By installing an MCP server for PostgreSQL, the AI can query and understand the database schema, enabling it to generate code that interacts with the database effectively.
The core of the video demonstrates an ambitious project where the agent, given a detailed PRD, builds a full URL list application from scratch. The process takes about 30 minutes, during which the AI creates the frontend, connects to the database, and implements features like adding, reordering, and persisting links. The presenter highlights the AI’s ability to adapt and improve code with features like next edit suggestions, which anticipate necessary updates based on changes. The final application is functional, allowing users to manage links dynamically, showcasing the power of agent mode in automating complex development tasks.
Finally, the video reveals a new feature allowing users to bring their own AI keys to VS Code, enabling access to different models like Gemini or Olama. This customization enhances the AI’s capabilities and aligns with individual or project-specific needs. The presenter concludes by emphasizing the incredible potential of these AI tools in VS Code, encouraging viewers to explore and build innovative projects. Overall, the video demonstrates how these new features make development faster, smarter, and more efficient, marking a significant leap forward in AI-assisted coding.