Firebase made an IDE?

This is all about Google's surprise announcement: Firebase Studio, an AI-powered app builder integrated directly with Firebase. Initially, there was a lot of skepticism towards anything Google Cloud or Firebase, but their recent AI advancements (like Gemini) made this worth a look, even if it means having to talk about Firebase now (which isn't a favorite).

Firebase Studio aims to be an 'agentic development environment' – basically, an AI assistant that helps you build, test, and deploy AI apps all in one web-based interface, built on the foundation of Project IDX (an earlier Google editor project). The core idea is pretty exciting: creating an 'AWS for AI' – not a place to host AI models, but an environment where an AI agent can easily set up all the backend stuff (databases, auth, storage) without the usual hassle of configuring multiple services like AWS or stitching together Supabase, Netlify, and Clerk. Currently, setting up infrastructure is a pain, even with tools like Terraform. The dream is more 'infrastructure as code' where configurations live in your codebase, making deployment simpler – something platforms like Vercel and Convex are closer to achieving. Firebase, traditionally relying on clicking buttons in dashboards, isn't known for this, but Firebase Studio could change that by offering an integrated backend solution that an AI can easily manage.

Let's dive into what Firebase Studio offers and how it performed in a real test:

• Core Concept: Firebase Studio combines tools like Project IDX (the editor base), GenKit (for AI flows), and Gemini (Google's AI model) into one unified platform. The goal is to speed up building AI-driven apps.
• Technology Choice: Surprisingly, it defaults to using Next.js for generated apps, not Angular. This is seen as a positive sign that the team understands the current web dev landscape and isn't just pushing Google's older tech.
• Editor Experience: The built-in editor is based on VS Code's open-source tooling, so it feels familiar. It runs in the browser and includes handy features like instant previews accessible via a URL for easy testing on different devices.
• AI App Generation: The initial prompt interface looks polished, better than many other AI builders. You type in what you want to build.
• The Test Case: The test involved building a 'Party Planner' app with features like event creation, invitations, RSVP tracking, and AI party ideas.
• Initial Generation Speed: The AI (powered by Gemini) generated the initial UI and file structure incredibly fast. It even broke down the plan into features and picked colors.
• AI Interaction: The chat interface on the right side is a nice touch. It responded quickly to prompts like changing the color scheme.
• Code Quality Issues (Attempt 1): The first generated app looked okay but was functionally broken. Buttons were missing or invisible, and there were no loading states. The generated code (using ShadCN components) had issues, and the live editor environment felt a bit buggy (e.g., reloading on save wasn't smooth).
• Backend Implementation Failure (Attempt 1 & 2): Despite the promise of Firebase integration, the generated app completely lacked backend logic. Critical functions like creating events or generating invitation links were just placeholder comments (// TODO: Implement this). This was a major letdown, as the whole point of Firebase Studio should be leveraging Firebase's backend services.
• Gemini API Key: The app constantly required a Gemini API key for its AI features, and the process to auto-generate one was slow and annoying.
• Iterative Refinement: Trying again with more specific prompts (like explicitly asking for authentication and a complete backend implementation) didn't fix the core issues. The AI seemed to ignore or fail at implementing the backend persistence and auth.
• Excalidraw Integration: A cool, innovative feature discovered was the integration with Excalidraw (initially mistaken for TL draw). You can draw UI changes, and the AI should be able to implement them, although this also glitched during the test.
• Comparison with Other Tools: Frustrated with Firebase Studio, the same 'Party Planner' prompt was tested on other AI builders:
  • Bolt: Also struggled significantly, especially with setting up Supabase integration, database migrations, and had UI/runtime errors.
  • V0 (by Vercel): Was slower to generate but handled Supabase setup more smoothly. However, the final app still had bugs, particularly with the authentication confirmation flow (using incorrect localhost links) and UI layout issues (broken padding). It also failed to create events properly.
  • Lovable: Had a nice UI and seemed promising. Connected to Supabase but then revealed authentication was 'coming soon' or simply didn't work upon testing sign-up. Even after some persistence and getting sign-in partially working (after much back-and-forth and manual URL hacking), creating an event didn't actually save or display it.
• Overall Verdict on AI Builders: The shocking takeaway was that none of the tested AI builders could successfully create the relatively simple Party Planner app with working authentication and backend data persistence. They can generate nice-looking frontends, but fall apart spectacularly when asked to do basic full-stack tasks.
• Firebase Studio's Missed Opportunity: Firebase Studio is uniquely positioned because it has its own integrated backend (auth, database, etc.). It doesn't need to rely on integrating Supabase like the others. Yet, it completely failed to implement these features in the generated code, opting out instead of failing, which is arguably less bad than generating broken code, but misses the entire point of its potential advantage. There's no excuse for it not handling its own backend services.
• Potential vs. Reality: Firebase Studio looks polished and has genuinely good ideas (like the integrated editor, Next.js choice, Excalidraw integration). The concept of an AI-native development platform integrated with a backend is powerful. However, in its current preview state, it's deeply flawed and doesn't deliver on its core promise. It needs a lot of work, specifically on making the AI actually implement the full-stack features it's supposed to be integrated with.
• Actionable Takeaway: Don't rely on these AI builders for anything beyond simple frontend generation or prototyping yet. They are not ready for building functional full-stack applications, especially concerning authentication and database interactions. Wait for demos showing working full-stack implementations before jumping in, especially for Firebase Studio.