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ExternalSoftware Architecture
Martin Fowler

Fragments: July 21

With this post, I’ll wrap up my notes from the second Future of Software Development Retreat. But before I do, I should note that the full Thoughtworks report on the retreat is now available. They have five headline findings: Code generation is no longer the bottleneck — verification is. ‘Harness engineering’ is emerging as a distinct, ownable discipline. Organizations are colliding with a real apprenticeship crisis. The executive/engineer expectation gap is a bigger risk than any technical lim

Martin FowlerRead original
ExternalSoftware Engineering
DZone

Reducing CI Execution Time Using Impact-Based Test Selection Across Repositories

Modern CI/CD pipelines often execute complete regression suites for every code change, regardless of the actual impact of the modification. While this approach guarantees broad validation coverage, it also introduces unnecessary test execution, slower feedback loops, and increased infrastructure cost. This challenge becomes more visible in microservice-based systems where repositories, services, and automation suites are distributed across multiple projects. A small change in one module can unin

DZoneRead original
ExternalMobile Development
Android Developers Blog

Build intelligent Android apps: Cloud and hybrid inference

Posted by Thomas Ezan, Jolanda Verhoef, Caren Chang, Senior Developer Relations Engineers, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we explored how to build intelligent on-device features using Gemini Nano through ML Kit's Prompt API. In this post, we will look at how you can leverage Firebase AI Logic to b

Android Developers BlogRead original
ExternalMobile Development
Android Developers Blog

Build intelligent Android apps: Integrate into Android's intelligence system using AppFunctions

Posted by Ben Weiss, Senior Developer Relations Engineer, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post, we explored how to leverage Firebase AI Logic to build cloud-hosted and hybrid AI features. Traditional mobile UIs excel at focused, hands-on tasks, and the Android intelligence system is introducing complement

Android Developers BlogRead original
ExternalMobile Development
Android Developers Blog

Build intelligent Android apps: Introduction to Jetpacker

Posted by Jolanda Verhoef, Senior Developer Relations Engineer, Android Developer Relations Building GenAI features in your app usually means navigating through various models, APIs and architecture choices:  Execution location: Where does your model run? On device, in the cloud, or both? Complexity: How complex is your setup? Are you doing a single inference call or do you need a more agentic flow? In-app or Android System: Should your feature be built into your Android app or does it fit b

Android Developers BlogRead original
ExternalMobile Development
Android Developers Blog

Build intelligent Android apps: On-device inference

Posted by Caren Chang, Developer Relations Engineer, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we introduced Jetpacker, the demo app we'll use throughout this series. In this blog post, we will share how you can use Gemini Nano through ML Kit’s Prompt API to build intelligent on-device features. Building in

Android Developers BlogRead original

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