Kotlin Programming Tutorials & Engineering Articles

Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement application-level session tracking directly within the runtime to accurately measure the committed concurrent workload of active conversations. By feeding these precise session counts alongside standard CPU utilization metrics into a hybrid routing algorithm, infrastructure can effectively distribute stateful AI traffic and prevent individual backend bottlenecks.

Answering the questions of "why we built ADK 2.0". This explains the rationale, some of the features, and why a developer should consider upgrading. This will be published the day after ADK go 2.0 launches.

We are excited to bring Express checkout with Google Pay for Android native apps enabling developers...

Google has announced the launch of version 0.1.0 of the Agent Development Kit (ADK) for Kotlin, alongside a specialized ADK library for Android. This open-source framework simplifies the creation of AI agents by managing complex orchestration, session sharing, and error handling across cloud and edge environments. The release supports hybrid orchestration, enabling developers to build multi-agent systems where a cloud-based model can seamlessly offload specific tasks to local, on-device models like Gemini Nano to enhance user privacy.

Google announced the transition from assistive AI to independent agents, highlighting the launch of the Gemini 3.5 series and major updates to its Antigravity agent-first development platform. For mobile developers, the post introduces new Android CLI tools, the Android Bench evaluation leaderboard, and an automated Migration agent designed to rapidly convert various frameworks into native Kotlin code. Web development is also being transformed through Chrome DevTools for agents, the HTML-in-Canvas API, and the proposal of WebMCP, an open web standard that enables browser-based AI agents to execute complex tasks.

Google AI Edge’s LiteRT-LM provides a production-proven, highly optimized infrastructure for running Gemma 4 across cross-platform mobile and edge environments. It actively unlocks the model's native multimodal and agentic features on-device by utilizing memory-efficient dynamic loading, Multi-Token Prediction for up to a 2.2x speedup, and advanced orchestration tools like Thinking Mode and Constrained Decoding. Furthermore, the engine is rapidly expanding its integration surfaces beyond Android, introducing new native Swift APIs for Apple ecosystems and WebGPU-accelerated JavaScript APIs for high-performance, serverless browser inference.

Moving from an internal tool to a community-driven, production-ready data mesh.

How Airbnb built a lightweight workflow engine to solve durable execution.

LiteRT is a production-ready framework designed to help mobile developers unlock the power of Neural Processing Units (NPUs), overcoming the performance and battery limitations of traditional CPU or GPU processing. By providing a unified API that abstracts away hardware complexities, it allows industry leaders like Google Meet and Epic Games to deploy sophisticated AI models for real-time video, animation, and speech recognition with significantly higher efficiency. The platform further supports developers through benchmarking tools and cross-platform compatibility, enabling seamless AI deployment across mobile devices, AI PCs, and industrial IoT hardware.

The newly introduced continuous checkpointing feature in Orbax and MaxText is designed to optimize the balance between reliability and performance during model training, addressing issues with conventional fixed-frequency checkpointing. Unlike fixed intervals—which can either compromise reliability or bottleneck performance—continuous checkpointing maximizes I/O bandwidth and minimizes failure risk by asynchronously initiating a new save operation only after the previous one successfully completes. Benchmarks demonstrate that this approach significantly reduces checkpoint intervals and results in substantial resource conservation, especially in large-scale training jobs where mean-time-between-failure (MTBF) is short.

This article explains how OpenAI built the Codex App Server, a bidirectional JSON-RPC API that serves as the critical link between the Codex harness (agent loop and logic) and various client surfac...

The article discusses the development of the Sora Android app, which was built in 28 days using Codex.

The article discusses the advancements in on-device AI powered by MediaTek's Neural Processing Unit (NPU) and the introduction of the LiteRT NeuroPilot Accelerator.

The article discusses optimizing performance on Qualcomm's Neural Processing Unit (NPU) using LiteRT, Google's high-performance on-device ML framework.

Airbnb built a system that combines GraphQL infrastructure, product context, and LLMs to automatically generate and maintain realistic, type-safe mock data using a custom @generateMock directive.

This article details how Uber standardized its mobile analytics system to improve data consistency and quality across its applications.

The article discusses how Meta has utilized Android's Baseline Profiles to enhance the performance of its applications, achieving up to a 40% improvement in critical performance metrics.

The article discusses how Meta is utilizing Large Language Models (LLMs) to enhance mutation testing and compliance in software development.

The article discusses the deployment of on-device generative AI (GenAI) using LiteRT-LM in Chrome, Chromebook Plus, and Pixel Watch.

The article discusses the evolution and modernization of Viaduct, Airbnb's data-oriented service mesh, highlighting its transition to open-source software.

The article discusses the integration of Kotlin's incremental compiler into Buck2, Meta's build system, highlighting the improvements in build times and developer productivity.

The article discusses Airbnb's migration of its JVM monorepo from Gradle to Bazel, detailing the motivations, process, and outcomes of this significant transition.

Meta has officially joined the Kotlin Foundation as a gold member, reinforcing its commitment to Kotlin and the Android development ecosystem.

The article discusses the implementation of Impulse, an internal load-testing-as-a-service framework at Airbnb, designed to enhance system reliability and performance through comprehensive load tes...

The article discusses the integration of Google Pay within Android WebView, highlighting its availability starting from WebView version 137.

The article summarizes the key announcements and developments from Developer Week 2025, highlighting new features and tools added to Cloudflare's developer platform.

NVIDIA and the PyTorch team at Meta have collaborated to integrate federated learning capabilities into mobile devices using NVIDIA FLARE and ExecuTorch.

SafetyCulture describes how they streamlined gRPC development for their offline-first mobile apps by automating code generation for their C++ middleware layer called Crux.

Meta is transitioning its Android codebase from Java to Kotlin, leveraging the advantages of Kotlin for Android development.

Meta is undertaking a significant project to translate its extensive Android codebase from Java to Kotlin, aiming to improve developer productivity and null safety.

The article celebrates Flutter's evolution into a production-grade app framework, highlighting its widespread adoption and the vibrant community that supports it.

The article introduces the developer preview of the Android XR SDK, a comprehensive toolkit designed for creating applications that leverage extended reality (XR) on Android devices.

This article explores the evolution of Notion's data catalog, detailing the challenges faced and solutions implemented across three distinct phases.

Uber has joined the Kotlin™ Foundation as a Silver Member, highlighting its commitment to the Kotlin community and ecosystem.

The article discusses Kotlin Multiplatform (KMP) and its applications in cross-platform development, highlighting Google's adoption of KMP in its products and the insights shared during KotlinConf ...

The article recaps the Google I/O 2024 event, highlighting advancements in AI technologies aimed at making AI accessible for developers.

The article discusses how Google is simplifying cross-platform development for developers by recommending specific technologies and frameworks.

This article discusses the implementation of Trio, Airbnb's framework for Jetpack Compose screen architecture in Android, focusing on the use of Props for type-safe communication between ViewModels.

This article discusses Shopify's approach to remote rendering, a technique that separates UI definition from rendering, allowing third-party developers to create extensions that integrate seamlessl...

The article discusses Airbnb's migration of its iOS build system from Buck to Bazel, detailing the approach taken to ensure a smooth transition with minimal disruption to developer workflows.

The article introduces Gemini Pro, Google's latest AI model designed for developers and enterprises, highlighting its capabilities, integration options, and pricing.

KAYAK successfully integrated passkeys into their Android and web applications, achieving a 50% reduction in sign-in time and enhancing security.

The article highlights the experiences of developers using Google tools and Bard in their projects.

The article details the construction of ClickHouse's Internal Data Warehouse (DWH), emphasizing its architecture, data sources, and operational strategies.

The article explores the unique and evolving nature of the JavaScript ecosystem, highlighting its historical context, the shift in how developers write JavaScript, and the impact of frameworks and ...

The article introduces an updated Google Pay button view for Android, enhancing customization and integration capabilities for developers.

Google I/O 2023 is set to begin on May 10, featuring keynotes and sessions focused on Modern Android Development, multi-device experiences, and platform quality.

LinkedIn has integrated Google Protocol Buffers (Protobuf) with Rest. li to enhance microservices performance, achieving significant reductions in latency and improvements in resource utilization.

The article discusses Tophat, a tool developed by Shopify to enhance the mobile developer experience by streamlining the testing process for mobile applications.