Mobile developers are the creative minds and technical wizards behind the applications we use daily on our smartphones and tablets. In other words, they translate ideas into the mobile apps that control how we communicate, shop, play games, and access information on the go. Pieces, which is free to individuals, is the easy way for developers to use AI in mobile app development.
Four Ecosystems for AI Mobile App Development
As mobile technology continues to evolve, the knowledge and skills required for mobile app development AI continue to change. The immediate effect of AI’s rapid rise in popularity is the expectation that its full functionality will be available as an AI tool to create mobile apps. Emerging trends like augmented reality, virtual reality, and foldable devices require developers to change and push the boundaries of their AI tools for mobile app design.
Even the definition of a “mobile app developer” depends on the project. A mobile developer may be either front-end or full-stack for Android, iOS, or cross-platform with one codebase for both. There are also mobile game developers with different stacks who write C# or C++ for game engines.
There are four mobile app ecosystems with different frameworks, rules, guidelines, libraries, and other tools. Pieces can assist as an AI to create mobile apps in any of these through its browser and desktop modules.
- A developer of native Android apps will probably use Android Studio and write code in Kotlin or Java.
- An iOS native-app developer will probably use Xcode and write in Swift or Objective-C.
- A developer who wants to maintain consistency with .Net will probably use Xamarin and write in C#.
- The tools a developer writing for Web open-source would use are less clearly defined. For example, the developer might use Qt (“cute”) software, but the limited market share and lack of dedicated development tools and resources compared to Android and iOS make it less popular than other frameworks.
Choosing the Right Framework
A cross-platform developer may use React Native, Flutter, Electron, Xamarin, or other frameworks (learn the difference between Flutter vs React Native, and Flutter vs Electron). The five major frameworks (or Native IDEs) listed in the following table vary in several ways, including how much they are like native code. The most important factors in choosing a framework (or multiple frameworks) are discussed after the table.
There are three very important considerations when choosing a framework or native IDE for mobile app development with AI:
- Consider your target platform: If you specifically need to target only Android or iOS, using the native framework (Kotlin/Java for Android, Swift for iOS) might be the preferred approach for optimal performance and access to native functionalities.
- Evaluate your team's skills: If your team is already comfortable with JavaScript and React, React Native could be a good choice. If you prefer a single codebase for both platforms and are open to learning Dart, Flutter could be a viable option (see how Pieces used Dart and Flutter to build their cross-platform application). If your team has experience with .NET languages, Xamarin (or Microsoft’s replacement for it) might be a strong contender.
- Project requirements: If your app requires specific functionalities or needs deep integration with native features, using the native framework might be necessary. For simpler apps, a cross-platform framework could be a more efficient choice.
It's important to research each framework in detail, consider your specific needs and constraints, and explore the resources and communities available for each option before making a decision. Remember, there's no "one size fits all" answer, and the best framework for your mobile app project depends on various factors.
Where Pieces Is Especially Useful
The more variations in the types of code snippets used by a developer, the more Pieces for Developers can streamline the workflow. This especially includes moving between frameworks for different projects. You can relaunch onboarding in Pieces at any time to change your persona(s) and languages. This, along with storing various code snippets from your workflow, regrounds the AI into the languages and materials of your workflow.
There are four major stages in a developer’s mobile app workflow:
Collaborative Design
This involves understanding user needs, translating them into app features and functionalities, and creating user interfaces (UI) that are intuitive and visually appealing. This often requires working closely with designers, product managers, and other stakeholders to understand the purpose, target audience, and desired features of the app. It also includes ensuring maintainability.
Pieces’ advanced features, such as workflow history, support easy communication and code collaboration. For example, if the code for a widget comes from someone, then the source, perhaps even the person's name, is associated with that widget’s code in the developer’s workflow. That information can be retrieved months later to ask a question.
Development
Choosing the appropriate programming languages and frameworks to write the code. This involves building the user interface (UI) for the interactions, writing the back-end logic for functionality, and integrating various features like databases, APIs, and security measures.
Pieces provides all the traditionally expected features of a copilot and more. It can easily translate code in a language for one framework into a different language for a different framework, such as described in this mobile app development user story. It supports 40+ languages. It also can keep track of different versions of the same functional snippet in different languages, used in different UI versions, or for different projects.
Testing and Debugging
Testing the app on various devices and operating systems to ensure it functions as intended, identifying and fixing any bugs or performance issues.
Pieces can troubleshoot code and debug it. It also can write unit tests, and even enhance AI code review efficiency.
Deployment and Maintenance
Deploying the app to app stores like Google Play Store or Apple App Store, and continuing to monitor its performance, address user feedback, and release updates with new features or bug fixes.
Pieces’ snippet enrichments and the developer’s annotations can be retrieved for any code written by the developer in the past. If a new developer is onboarded to the same repository after the previous developer leaves, the new developer has access to the stored workflow to ask the AI questions and get intelligent answers about the code.
Also, Pieces provides different views for looking at code. The list view shows more auto-enrichment data and is great for shorter snippets. In contrast, the gallery view is more for longer snippets, and it is easy to move left and right between them.
There is another view in Pieces called workflow activity. You can filter that and search through it to see anything that you've referenced or opened any code snippets that you've used. This also works with the extensions as well. You can review any snippet that you saved when you did it. Later, you can go back through your workflow and remember how you did something.
Pieces Mobile Use Case Interview
Dan O’Leary, an avid Pieces user, was working on an iOS application for tracking aviation fuel at the time of the interview. It is now his fourth app in the Apple store. His full-time job is being a pilot, so he requires that any tool in his stack makes him more productive. He switches among frameworks depending on the mobile app project.
The iOS app development user story he discussed in the interview is a recurring theme across his apps: “I seem to always find myself working with dates, date comparisons, whether I want to or not. I have another app on the store that's a running app. And so then that's not really dates, but it's more timers. Date comparisons and working with time is strangely complicated.”
Before using Pieces, Dan used Snippets Lab for Mac. He said, “It was about half of the functionality or maybe a quarter of the functionality” of Pieces. His repository was “blocks of code that helped me sort dates—or things that I like to use to deal with sorting and comparing time. And so, you know, these are either live in a project or they live in a file that I can reference back because once I switch frameworks or I work on a different project, I'll forget again how to do that.
Then I go back to falling into the trap of working with dates again–-I've forgotten. So I need to go back and open up my toolbox and look for what I need to do to remember how to do that. Because I don't. I don't work on only that all the time. And when you're context switching like that, it's too hard to just memorize everything. I don't think it's reasonable to expect a developer to do that.
So having some sort of a tool in your workflow that you can search, which is great with your app that's got this automatic tagging for the frameworks and what the code actually does. Super handy for me. It just speeds up what I'm looking for and knowing what I have–-because maybe I don't have a block of code that does that. I won't waste my time looking for something that I don't have.”
What Else the User Said
- Conversational Interface: “I played around with the copilot and I love that very familiar ChatGPT style. You know, kind of ask a question and I really like that it actually gave me an answer on how I was working on something. It spit out an answer that I needed, so that is very cool.”
- Searchable tags: “I can't think of any other platform I've used that I've had my searchable tags for my code. … The fact that it auto-generates this stuff is, to me, that blew me away.”
- Security and Privacy: “[I]t's so cool that it’s on-device … for people working in a security-sensitive or intellectual-property kind of environment, ... it's like, oh, that's very cool that you can't just send your code out to the world for storage or reference or anything.” Some people save API keys because they reuse them and Pieces will be able to identify sensitive information. The actual key will get flagged before you try to share it with someone or use it in your IDE. You'll get a little warning pop-up.
Conclusion
Each of the mobile-device ecosystems includes many different devices with different screen sizes, pixel densities, and OS versions. The complexity these differences add to development, testing, and maintenance is a strong justification for including Pieces as a tool for workflow integration with AI. Its intelligent management of snippets identifies and organizes which snippets are relevant to what devices and when and where they were used.
The following quote from a user confirms the statements made in this post. Pieces’ advanced features gives it a special position among the numerous AI tools for mobile app development.
“Pieces is the most useful piece of AI, machine learning, you know, whatever you want to call it, to me so far… because one thing in researching AI, as I've been doing the last few months, is I want to use this to make my work more efficient, … I guess my answer is, what I've seen you guys do is the best integration to my daily life that I have yet to see from any sort of machine learning and artificial intelligence [tool]—to my software development life.”
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