Roo Code and Gemini Inside VS Code: How AI Agents Are Changing App Development

Roo Code: A First Look at AI-Powered Application Development

Roo Code is one of the early autonomous coding agents integrated directly into the IDE. This article offers an initial look at AI-driven app development with Roo and Gemini inside VS Code.

Many developers have been waiting for a coding tool that lets them move seamlessly from idea to app, then continue refining without getting bogged down in code details. The promise has been that AI would make developers obsolete by handling these tasks autonomously. Roo Code aims to deliver on that promise by keeping you focused on ideas while generative AI manifests changes automatically.

Getting Started with Roo Code

Roo Code acts as an agent connecting your application and AI engine. It reads your app’s current state, takes your prompts, sends requests to the AI engine, and applies changes directly to the project files. To get started, you need to provide an AI API key. Gemini is a supported option and was used in this exploration.

Note: Roo Code itself is free, but API calls to your AI provider incur standard charges.

Setting up Roo Code in the Terminal

One notable feature of Roo Code is its ability to run commands directly in the terminal. On Windows, using Git Bash inside VS Code caused errors when Roo tried to execute commands. Switching to PowerShell and adjusting permissions resolved these issues. This setup step is essential for Roo to manage tasks smoothly.

Managing Agency in Roo Code

Roo Code and similar AI assistants, like Kiro, focus on delivering agency by emphasizing file diffs. Diffing acts as a bridge between simple AI coding helpers and fully autonomous agents. Instead of painful copy-pasting, Roo proposes changes as diffs within your IDE, letting you review and approve them. This approach leverages AI’s strength in text manipulation and maintains developer control.

Enabling automatic diff approval activates a more agentic mode, where Roo reviews required tasks and executes them independently. Roo offers different modes, primarily:

• Code mode: Direct code modifications
• Architect mode: Higher-level design decisions and planning

Example App: My Music Gear

Using Roo Code, an app for selling music gear was generated. It featured a frontend built with vanilla CSS, JavaScript, and HTML, and a backend using Node.js, Express, and SQLite. For comparison, Google Firebase Studio would generate a Next.js app for a similar prompt. Both stacks are valid starting points.

Roo Code in the Data Layer

In architect mode, Roo Code discussed database options. The initial choice was SQLite, ideal for development due to its simplicity and integration. When exploring production options, Roo suggested MongoDB, which was then integrated by swapping database drivers and migrating queries. This saved significant manual effort.

Running MongoDB itself is outside Roo’s current capabilities. Installing and configuring external software involves security and authorization complexities. The logical next step would be AI agents provisioning cloud databases like MongoDB Atlas, but this requires careful handling of authentication and costs.

Switching back from MongoDB to SQLite was also handled smoothly by Roo, demonstrating flexibility during development.

Automatic Diffing

When read and write permissions are enabled, Roo can perform diffs and apply changes automatically. Updates happen with minimal intervention, but you still have access to review each changeset if needed. This keeps control in your hands while letting Roo work efficiently.

Adding an About Page

Adding a simple "About us" page was straightforward. Roo provided a clean template, which you can then customize. This kind of routine legwork is exactly what agents like Roo are built for.

Adding a Payment Gateway

Integrating payment processing followed a similar pattern to database setup. Roo helped configure the code for Stripe (or similar services), but account creation, API key management, and testing remain manual tasks. Full automation here would require deeper agent permissions and security considerations.

In the Weeds with Roo Code

Trying a more complex feature—an admin page for adding new items—revealed some rough edges. Roo created an input form, but submitting data caused errors due to mismatches between form submission and JSON endpoints.

Roo suggested restarting the backend server, but since it ran in a separate terminal, it couldn’t do so automatically. After some back-and-forth, Roo generated PowerShell commands to kill and restart the Node process, but these attempts opened new windows and caused further errors.

Eventually, it became clear the backend server was crashing due to SQLite errors. Roo recommended dropping and recreating tables to fix schema issues, then restarted the server again. Despite hiccups, after some manual restarts, the admin form started working.

This experience highlights the limits of current agentic AI: it can handle many tasks but still requires developer oversight and intervention for complex troubleshooting.

Adding Authorization

Adding authentication and authorization to the admin page went better. Roo planned and implemented password hashing with bcrypt, schema changes, login pages, and access checks. While basic, the feature worked and saved substantial manual coding time.

Having AI directly integrated into the IDE—rather than as separate windows or snippet generators—makes this level of agentic assistance practical.

Changing the Text Stack

When asked about converting the prototype to Next.js for Vercel deployment, Roo provided a clear action plan, including a diagram. This shows promise for adapting codebases to different frameworks.

General Impressions of Roo Code

Roo Code mostly operates smoothly but can get stuck or slow down on complex tasks. Occasional crashes require restarting VS Code. Fine-tuning UI or CSS sometimes feels faster to do manually due to back-and-forth fixes and regressions.

The Present and Future State of Agentic AI

Pairing Roo Code with Gemini in VS Code currently offers one of the most effective agentic AI setups. Still, the idea that AI will fully replace developers is unlikely. Roo Code acts more like an exosuit, augmenting human capabilities rather than replacing them.

Responsible developers should disable auto-approval during critical stages to review AI-generated code carefully. Blindly accepting AI changes risks introducing unvetted code, which is acceptable during rapid prototyping but not for production projects.

Looking ahead, one can imagine AI handling increasingly complex tasks—from provisioning cloud resources to full deployment and financial management—but this will require balancing autonomy with security and oversight.

For developers interested in enhancing their AI skills and tools, exploring courses and resources at Complete AI Training can provide practical knowledge on AI-assisted development.