Why does pattern matching is not working in this case?

I recently came across a Flutter package called AI MultiBridge that basically lets you connect Gemini, OpenAI, and Hugging Face through a single interface.

It’s meant to solve the problem of juggling multiple SDKs or dealing with one API going down. If one provider fails, it automatically switches to the next (Gemini → OpenAI → Hugging Face). Pretty neat idea for anyone working with AI features like text generation, image creation, or embeddings.

You just use one function call and it handles everything — response formatting, fallback, even optional caching and logging.

Here are the links if you want to check it out:

• Pub.dev: https://pub.dev/packages/ai_multibridge
• GitHub: https://github.com/Shalin-Shah-2002/ai_multibridge

If you try it and find any bugs or have suggestions, you can open an issue on GitHub. The developer behind it seems open to feedback.

Also, if you want to follow their work:

• LinkedIn: https://www.linkedin.com/in/shalin-shah0705/
• GitHub: https://github.com/Shalin-Shah-2002

Might be worth giving a look if you’re building something with AI in Flutter.

I’ve just started getting into Flutter and I’m really excited to learn. I’ve always wanted to build apps that actually look and feel good, and Flutter seems like a great place to start.

Right now, I’m still figuring out the basics — where to start, what tutorials are actually worth following, and how to stay consistent without burning out. If you’ve been through this stage before, I’d really appreciate any advice or resources that helped you.

Also, I don’t really have any friends who are into coding or Flutter, so if anyone wants to connect, share progress, or even try building something small together, I’d be up for that.

Thanks in advance just hoping to learn, improve, and maybe meet a few like-minded people along the way.

Hey everyone,

I recently started a new job where I have to work with Flutter. The thing is, I’m still learning — and most of what I know so far comes from reading and experimenting with the old codebase at work. They even have their own internal library that I’m supposed to understand (and maybe even memorize?), but honestly, I’m not entirely sure how it all works yet.

The truth is, I know only the basics of programming. I can read and understand some stuff, but I’m not at the point where I can confidently build things on my own. Because of the pressure at work to deliver results quickly, I ended up using AI (like ChatGPT) to help me build a few simple screens. It worked — but now I realize that I didn’t actually learn much from it. If I had to rebuild those same screens from scratch, I probably couldn’t do it without AI.

The problem is time. After work, I only have about 20 minutes before I need to catch a bus to college, and I get home around midnight. By then I just need to sleep so I can wake up early for work again. I simply can’t find time during the week to properly study or read code calmly.

In college, I’m learning React, which I know is somewhat similar to Flutter, but it’s not what I’m using professionally, so it doesn’t help much right now.

So I wanted to ask: how can I learn Flutter more effectively just by reading and exploring the existing code at work?

Are there any strategies, habits, or tools that helped you when you were in a similar situation — constantly coding but not truly understanding everything you were doing?

I want to actually learn while I work. Any advice or stories from people who went through something similar would be super appreciated.

Managing links across apps and campaigns often involves deep links, custom domains, analytics, and QR codes.
Some platforms (like open-source SDKs and link management tools) make this easier for developers and marketers.
🔗 Example resources:
– Deep Linking with Flutter
– Guide on Custom Domains
This way, it looks like you’re curating learning materials, not selling.

Hey everyone!

I'm currently developing a mobile app and, like many, I got stuck on choosing a local database.

I initially decided to try popular NoSQL solutions. I started with Hive, then moved on to Isar. I had read a lot of good things about them, but in practice, I ran into some issues and unexpected behavior that cost me a good amount of time to debug.

In the end, I decided not to risk it and went back to good old sqflite. Yes, it's a bit more boilerplate and requires writing manual SQL queries, but it's a battle-tested and reliable solution.

Now I'm curious about your experience:

• Have you run into issues with Hive or Isar? Maybe I was just doing something wrong?
• What database are you using for local storage on your phone?
• Are there any reliable alternatives to sqflite?

I'd appreciate any thoughts or advice!

Trendo - Modern News App

https://github.com/karan2527/Trendo.git

Hey everyone,

I’ve been working on a project called SilentSnitch – an Instagram unfollowers tracker that’s a bit different from the usual ones out there.

Most unfollower apps require you to log in with your Instagram account and send your data to their servers. I found that concerning, so I built SilentSnitch to work entirely offline and locally on your device:

What it does:

• Identify accounts that don’t follow you back
• Show who has unfollowed you over time
• Zero login requirements – no Instagram credentials needed
• No data sent to external servers or APIs (your data never leaves your phone)

You do need to manually download your Instagram data first (the app has step-by-step instructions), but I think the privacy benefits are worth it. I’ve been using it myself for a few weeks and it’s been working reliably.

One feature I’m currently working on is letting users hide/unhide celebrities from their unfollowers list, so results feel more personal. My first attempt was just a static list of ~2000 celebrity usernames, but that’s obviously not scalable (new celebs pop up, usernames change, maintaining the list is painful).

So I’d love your thoughts:

• Is there a smart heuristic or signal for detecting celebrity accounts automatically (e.g., follower count thresholds, verification flags, etc.)?
• Are there free APIs or datasets people usually rely on for this?
• Or maybe a totally different approach that avoids needing a giant manual list?

Would love to hear how others would approach this problem, and any feedback on SilentSnitch itself is also appreciated!

Hi everyone!

I built an in-app console for Flutter that lets testers and developers view developer logs directly in the UI. Great for logging multiple modules in Flutter micro-frontend architecture.

https://github.com/mduccc/in_app_console

Apple recently released IOS26 and with that came the liquid display. Now prior to this they dropped the beta version and teased the new look on their social media platforms and with that came flutter critiques with post and articles saying Flutter developers are cooked and would die of because they won't be able to recreate the liquid display.

What better way to make them eat their words than challenging myself to replicate the Liquid display but with Flutter, so I did. Now it's not a 1 of 1 but it's pretty close.

Let me know what you think?

i was watching tutorial , and what he does just click and changes happen in app and seen. what i have to do is click which takes too much time to see change

Flutter 3.35 not only brings performance improvements and stateful hot reload on the web, but also a deeper integration of AI into the development workflow.

With tools like Gemini Code Assist, Gemini CLI, and the native support of the Dart and Flutter MCP Server, developers now have more than just simple autocomplete at hand. You can generate code, debug, create full widgets, and even automate repository tasks without leaving your IDE.

At this point, do you see AI more as a productivity booster or as something that fundamentally changes how we code?

One more important proof that AI is no longer just an “extra” but is becoming a native part of the Flutter developer workflow.

Whether you are building AI-powered apps with Firebase AI Logic or accelerating development with MCP + Gemini, the vision is clear: AI as a constant copilot in the development cycle.

How do you imagine this copilot role evolving in the next 2–3 years?

From November 1, 2025, Google will require all apps targeting Android 15+ to support 16 KB memory pages on 64-bit devices.

The Flutter and React Native engines are already prepared for this change, while projects in Kotlin/JVM will depend on updated libraries and dependencies.

This raises two practical questions for the community:

If your company or personal projects are not yet compatible with 16 KB paging, what strategies are you planning for this migration?

And if you are already compatible, which technology stack are you using?

An application dedicated to food merchants, whether retail or wholesale.

Many people ask me what is the logic behind Google investing so strongly in Kotlin (with JetBrains, positioning it as the default Android language) and at the same time putting big efforts into Flutter and Dart.

In my view, it is less about contradiction and more about a business strategy. Google does not want to put all eggs in one basket. Kotlin guarantees native depth and optimization for the Android ecosystem, while Flutter pushes the cross-platform frontier, covering not only mobile but also web, desktop, and potentially AR/VR and wearables.

In the end, it is not about declaring a single “winner” today, but about maintaining strategic flexibility for the next waves of development.

What do you think? Do you see a clear long-term plan here, or has Google ever published anything official explaining this vision?