The article covers the Flutter 3.44 highlights from Google I/O 2026, emphasizing scaling to more users on more devices. It details features such as agentic hot reload, generative UI, and the platform's focus on AI-assisted development.
The article details the development of Coach Ivy, a nutrition app that embeds a 3D AI avatar built with Unity inside a Flutter application. This hybrid architecture aims to transform calorie tracking into an interactive experience with a reacting 3D coach, leveraging Flutter for UI and Unity for the avatar.
This content is a submission for the DEV Education Track, showcasing a receipt and document scanner built in Flutter. The application leverages Google AI Studio and the Gemini API for its core functionality.
This article details how to add real-time AI tag suggestions to Flutter notes using the free Groq API with the Llama-3.3-70b model. The solution aims to eliminate the cognitive overhead of manual tagging by integrating AI to automatically classify notes.
The article describes how to build a zero-cost AI feature in Flutter apps by combining on-device inference with Gemma 4 and cloud sync with Firebase. This approach eliminates API fees and server costs, allowing AI-powered apps to scale without draining resources.
The author significantly reduced manual UI revisions from 4-6 to 0-2 by integrating a golden tests and Figma screenshot diff loop into their AI-driven Flutter UI workflow. Despite AI generating well-formed code, it struggled to match Figma specifications, making manual iteration a bottleneck.
This content details the development of a Pomodoro-style focus timer and an AI writing assistant in Flutter Web, aiming to compete with Forest and Grammarly. It outlines the shipped features and backend implementation using Edge Functions for managing focus sessions.
The author details building a zero-buffer NAS media player in Flutter, overcoming SMB streaming issues with a local HTTP proxy. The project utilized an AI coding assistant, but required corrections for its "hallucinations".
The author developed PsyScore, a mental health and therapy management MVP in Flutter with AI-assisted insights, featuring therapist/patient dashboards, journaling, and assessments. They are now considering selling the project as a SaaS starter or template rather than scaling it themselves, seeking feedback from founders and indie hackers.
A developer recounts building the first Dart package for MG/SAIC connected vehicles by reverse-engineering the official app. This personal project allowed them to control their car functions, like unlocking, through their own custom-built client.
This Flutter testing guide explains the three main test types – Unit, Widget, and Integration – detailing their purpose, speed, and when to use each. It emphasizes building tests from the bottom up, with unit tests as the foundation and integration tests reserved for critical paths.
This article discusses the importance of mobile applications for businesses, comparing Android and Flutter development approaches. It promotes Floating Infotech's services, highlighting benefits and technologies for building powerful mobile apps.