As mobile applications grow into large, long-lived systems, maintaining a clear and scalable codebase becomes increasingly challenging. This talk explores a production-proven architectural approach for large-scale Flutter applications, successfully used for several years in a product with millions of users and a multi-million-line codebase, developed by a team of 100+ mobile engineers.
Built around a LEGO concept, where the application is composed of highly modular, interchangeable, self-contained building blocks, this architecture enables teams to develop and deliver features in isolation, while keeping the overall system consistent and maintainable. We’ll cover key aspects such as code organization, state management, navigation, dependency injection, configuration, testing, and more, along with the principles that guided these choices.
You’ll leave with practical recommendations for structuring large codebases and scaling development without sacrificing efficiency or maintainability.

You use AI to write code, automate boring tasks, research faster, plan a trip, or test a business idea. Then you look at your partner, parents, or friends and realize they may use it in a completely different way. Or barely at all. Could that difference matter five years from now?

Early research already points to gaps in how people across genders and ages adopt and experiment with AI. Social media may widen them by feeding people different ideas, tools, and opportunities. AI itself can also reinforce old stereotypes, associating software and technology more strongly with some genders and care, beauty, or lifestyle with others. If AI fluency becomes a career advantage, a small difference in how we use these tools today can turn into a much bigger gap tomorrow.

This panel brings Flutteristas together to challenge that idea. Is the gap real? Where does it come from? Are algorithms making it worse? And what can we do before AI skills become another advantage that is unevenly distributed?