Posts Tagged ‘Kotlin’
[VoxxedDaysBucharest2026] Building a Sarcastic, Agentic Pair Programmer: Alexander Chatzizacharias on Crafting Playful LLM Workflows
Lecturer
Alexander Chatzizacharias is a software engineer at JDriven, a specialized consultancy in the Netherlands focused on JVM technologies and modern software development practices. With a unique background blending Dutch and Greek influences and a keen interest in game studies, Alexander brings creativity and playful thinking to technical challenges. He frequently speaks on topics including Java, Spring Boot, AI applications, and innovative development workflows.
Abstract
As mainstream AI coding assistants converge toward similar polished but somewhat generic experiences, Alexander Chatzizacharias demonstrates how to build a highly personalized, characterful AI pair programmer named “Pip.” Inspired by interactions with a sarcastic colleague named Ricardo, Pip incorporates personality through vectorized Slack history, utilizes Spring Boot and Kotlin, runs entirely locally with Qwen models via Ollama, and employs sophisticated workflows, multi-vector RAG, and the Model Context Protocol (MCP) to create delightful and productive assistance while addressing challenges like non-determinism and model drift.
The Homogenization of AI Assistants and the Quest for Personality
Alexander observes that leading AI coding tools have converged on remarkably similar chat-based interfaces and interaction patterns, largely influenced by OpenAI’s design choices. While incremental improvements continue, the overall experience feels increasingly uniform. This observation inspired the creation of Pip — an intentionally quirky, sarcastic AI pair programmer that injects personality drawn from real colleague interactions.
By processing Slack conversation history into vector embeddings stored in Qdrant, Pip can retrieve and emulate Ricardo’s characteristic sarcastic tone, witty retorts, and playful threats (such as threatening to delete poorly written code). This transforms the assistant from a neutral tool into a more engaging, human-like collaborator that questions unclear requirements, offers humorous feedback, and makes the development process more enjoyable.
Technical Architecture: Workflows, Agents, and Local Execution
Pip is implemented as a Spring Boot application written in Kotlin, with an IntelliJ IDEA plugin providing the frontend interface. Everything runs locally to maintain privacy and control: Qwen 3.5 models served through Ollama handle the language tasks.
Rather than pursuing fully autonomous agents, Alexander favors structured workflows that provide greater determinism and reliability — attributes particularly valued in enterprise environments. A categorization agent, functioning as an LLM-as-Judge, routes incoming queries to appropriate specialized handlers. Each handler uses carefully crafted system prompts derived from Slack history to consistently embody the desired personality traits.
The architecture incorporates multiple specialized agents for response generation, sophisticated RAG pipelines leveraging both dense and sparse vector representations with ColBERT reranking for improved retrieval quality, and integration with the Model Context Protocol (MCP) for tool usage such as playing music or generating memes when appropriate.
RAG, Tools, and the Challenges of Non-Determinism
Retrieval-Augmented Generation forms a cornerstone of Pip’s capabilities, dynamically pulling relevant context to overcome the inherent token limitations of even advanced models. Multi-vector search strategies combine semantic understanding with keyword precision for more reliable information retrieval from project documentation, codebases, and conversation history.
Tool integration via MCP enables rich interactions but introduces additional complexity due to the non-deterministic nature of local models. Alexander discusses practical challenges including prompt sensitivity to model updates (“model locking” strategies), the art of prompt engineering which he likens to “vibe checking,” and the necessity of implementing guardrails to maintain appropriate behavior boundaries.
Implications for Future AI Development
Alexander encourages attendees to experiment with building personalized, domain-specific AI assistants using accessible open-source tools. While acknowledging the increasing commercialization of AI, he emphasizes the current window of opportunity for creative, playful implementations that enhance both productivity and developer satisfaction.
Pip serves as an inspiring example of how thoughtful combination of RAG techniques, vector databases, workflow orchestration, and personality injection can create AI tools that feel genuinely collaborative rather than merely functional.
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[VoxxedDaysAmsterdam2026] Ouvroir de Code Potentiel: Discovering Creativity Through Constraints in Programming
Lecturer
Anders Norås is a software engineer and speaker known for exploring unconventional approaches to coding and language design. He frequently presents on topics that challenge traditional programming practices while revealing deeper insights into how languages shape thought processes.
Abstract
The Oulipo literary movement of the 1960s imposed artificial constraints on writing to spark creativity and produce novel works. Anders Norås applies similar principles to programming, reimagining familiar exercises under unusual restrictions. By removing common language features or enforcing mathematical structures, developers gain fresh perspectives on problem-solving. The presentation demonstrates how such constraints reveal hidden capabilities within languages, encourage exploration of alternative paradigms, and foster deeper appreciation for the tools we use daily. Far from mere novelty, this approach yields practical lessons about flexibility, idiom discovery, and creative thinking in software development.
The Oulipo Tradition and Its Relevance to Programming
The Ouvroir de littérature potentielle, or Workshop of Potential Literature, sought to expand creative possibilities through self-imposed rules. Authors produced works without using specific letters, following mathematical patterns, or adhering to other arbitrary constraints. These limitations, rather than stifling expression, forced innovative solutions and surprising results.
Programming shares fundamental similarities with writing. Both involve crafting structures from symbolic systems to convey meaning or achieve outcomes. Both benefit from deliberate practice and exploration of form. Just as Oulipo writers discovered new literary techniques, programmers can uncover language capabilities and problem-solving approaches by temporarily restricting their usual tools and patterns.
This method serves multiple purposes. It combats the complacency that develops from repeatedly solving problems the same way. It encourages examination of features developers might otherwise overlook. Most importantly, it transforms routine tasks into opportunities for discovery and renewed engagement with the craft.
Exploring Familiar Problems Under Novel Constraints
Classic programming exercises provide ideal subjects for constraint-based experimentation. The FizzBuzz problem, for instance, typically relies heavily on conditional statements. Removing the ability to use if statements or ternary operators forces alternative implementations that reveal language-specific idioms and capabilities.
One approach in C# leverages pattern matching within switch expressions to handle the logic. The resulting code, while unconventional, demonstrates how modern language features can replace traditional control structures. Translating the same constraint to Java yields an elegant, albeit unusual, solution using string repetition methods. These variations highlight how different languages encourage distinct thinking patterns even when solving identical problems.
Chessboard traversal problems offer another rich domain. The standard Warnsdorff’s rule provides an efficient algorithmic solution for visiting every square exactly once. However, constraint exercises might require solving the same task through exhaustive backtracking, ant colony optimization simulating natural behavior, genetic algorithms, or Monte Carlo tree search. Each method exposes different aspects of computational thinking and language expressiveness.
The value lies not in replacing established algorithms but in understanding the range of possible approaches. By deliberately limiting options, developers gain appreciation for why certain solutions feel natural in specific languages and discover techniques transferable to everyday work.
Benefits and Practical Applications
Constraint-based programming yields several advantages. It reveals language features that receive little attention in typical development. It encourages deeper engagement with syntax and semantics, moving beyond surface-level usage. It fosters creativity by breaking habitual patterns, often leading to more elegant or insightful solutions even after constraints are lifted.
Teams can apply these ideas in several ways. Code katas or brown-bag sessions focused on constrained implementations build collective knowledge and discussion. Exploring how the same problem manifests across languages strengthens architectural thinking and technology evaluation skills. Individual developers benefit from occasional deliberate practice that prevents skill stagnation.
The approach also serves as an effective teaching tool. Students or new team members gain rapid insight into language philosophy when asked to solve problems while avoiding common constructs. The resulting discussions illuminate design decisions embedded in language evolution.
Broader Implications for Software Development Culture
Modern development increasingly involves instructing AI systems rather than writing every line manually. In this environment, human strengths shift toward system thinking, trade-off analysis, and creative problem framing. Constraint exercises hone precisely these capabilities by forcing reconsideration of fundamental assumptions.
The Oulipo-inspired mindset aligns with broader movements in software craftsmanship that value deliberate practice and reflection. It echoes the Japanese concept of finding meaning in the space between elements—discovering insights that emerge when conventional approaches are temporarily set aside.
Programming communities benefit when members periodically step outside comfort zones. New libraries, paradigms, and techniques often arise from individuals willing to question established norms. By cultivating curiosity through playful constraint, developers contribute to collective advancement while maintaining personal engagement with the craft.
Embracing Constraints as Catalysts for Growth
The central insight from Oulipo applied to code is that limitations can liberate. By temporarily removing familiar tools or imposing unusual rules, programmers discover unexpected pathways and deepen their mastery of available ones. What begins as an exercise in absurdity often yields practical wisdom and renewed appreciation for the languages and techniques we employ daily.
This practice requires no special resources beyond willingness to experiment. A simple problem, a chosen constraint, and honest reflection suffice to begin. Over time, the habit of viewing constraints as invitations rather than obstacles transforms how developers approach challenges both large and small.
In a field where routine can dull creativity, the workshop of potential code offers a refreshing reminder that innovation often hides in the space between what we usually do and what becomes possible when we choose differently.
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[KotlinConf2025] Blueprints for Scale: What AWS Learned Building a Massive Multiplatform Project (2nd version)
In a talk on building large-scale, multiplatform projects, Ian Botsford and Matis Lazdins of Amazon Web Services (AWS) shared their experiences creating the AWS SDK for Kotlin. This project is colossal, spanning over 300 services and targeting eight different platforms, with its code distributed across four repositories and nearly 500 Gradle modules. The talk provided a blueprint for managing a codebase with over 8.6 million lines of code, 98% of which is auto-generated. The key to their success, they claimed, was a set of five core principles that kept their maintainers sane and productive.
A Principled Approach to Development
Botsford and Lazdins detailed five tenets for managing a project of this scale: owning your dependencies, structuring the project for growth, designing for Kotlin Multiplatform (KMP) from the beginning, maintaining backward compatibility, and optimizing the maintainer experience. They provided a practical example of owning dependencies by discussing their choice of HTTP clients. Instead of exposing third-party library types directly, which could lead to inconsistent configurations and vulnerability to unexpected API changes, they created a common, abstract interface to maintain consistency and shield users from underlying implementation details.
Automating for Maintainer Sanity
A significant part of their strategy focused on the maintainer experience. Lazdins explained the importance of automating repetitive and mundane tasks to free up time for more complex work. They developed broad checks to catch issues before they are merged, which helps prevent regressions and enforce project standards. The speakers stressed that these checks should be highly informative but also overridable, giving developers autonomy while providing valuable feedback. This focus on a positive maintainer experience is crucial for the health of any large open-source project and is a key factor in the daily releases that happen sometimes multiple times a day.
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[KotlinConf2025] Simplifying Full-Stack Kotlin: A Fresh Take with HTMX and Ktor
Becoming a full-stack developer is a highly sought-after and valuable skill in today’s tech landscape, allowing individuals to own features from start to finish and make holistic architectural decisions. This versatility is particularly important for small teams and startups. However, the role can be intimidating due to the extensive list of technologies one is expected to master, including Kubernetes, Postgres, Kotlin, Ktor, and numerous JavaScript frameworks. Anders Sveen’s talk challenges this complexity, proposing a simpler, more streamlined approach to web development by using HTMX and Ktor with Kotlin.
The Case for Simplicity
Sveen poses a crucial question: do we truly need all this complexity when HTML and CSS remain stable, unlike the ever-changing frontend frameworks?. He argues that many applications don’t require the overhead of a modern JavaScript Single Page Application (SPA), since everything ultimately renders to HTML anyway. His proposed solution uses technologies like HTMX, AlpineJS, and Unpoly, which build upon HTML and CSS rather than replacing them, allowing developers to achieve 98% of SPA functionality with significantly less frontend code and complexity.
A Synergistic Solution
The core of the presentation demonstrates how HTMX and kotlinx.html combine with Ktor to build modern, interactive web applications. The stack offers a refreshing simplicity, leveraging Ktor’s powerful backend capabilities, kotlinx.html’s type-safe HTML generation, and HTMX’s elegant method for handling frontend interactions. The talk also highlights how this simplified stack can reduce the need for microservices and complex technical setups by minimizing unnecessary coordination within development teams. Sveen, with 20 years of experience, emphasizes that this approach allows developers to be more full-stack, enabling them to quickly take an idea, deliver a solution, and learn from user feedback.
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[KotlinConf2025] Blueprints for Scale: What AWS Learned Building a Massive Multiplatform Project
Ian Botsford and Matis Lazdins from Amazon Web Services (AWS) shared their experiences and insights from developing the AWS SDK for Kotlin, a truly massive multiplatform project. This session provided a practical blueprint for managing the complexities of a large-scale Kotlin Multiplatform (KMP) project, offering firsthand lessons on design, development, and scaling. The speakers detailed the strategies they adopted to maintain sanity while dealing with a codebase that spans over 300 services and targets eight distinct platforms.
Architectural and Development Strategies
Botsford and Lazdins began by breaking down the project’s immense scale, explaining that it is distributed across four different repositories and consists of nearly 500 Gradle projects. They emphasized the importance of a well-defined project structure and the strategic use of Gradle to manage dependencies and build processes. A key lesson they shared was the necessity of designing for Kotlin Multiplatform from the very beginning, rather than attempting to retrofit it later. They also highlighted the critical role of maintaining backward compatibility, a practice that is essential for a project with such a large user base. The speakers explained the various design trade-offs they had to make and how these decisions ultimately shaped the project’s architecture and long-term sustainability.
The Maintainer Experience
The discussion moved beyond technical architecture to focus on the human element of maintaining such a vast project. Lazdins spoke about the importance of automating repetitive and mundane processes to free up maintainers’ time for more complex tasks. He detailed the implementation of broad checks to catch issues before they are merged, a proactive approach that prevents regressions and ensures code quality. These checks are designed to be highly informative while remaining overridable, giving developers the autonomy to make informed decisions. The presenters stressed that a positive maintainer experience is crucial for the health of any large open-source project, as it encourages contributions and fosters a collaborative environment.
Lessons for the Community
In their concluding remarks, Botsford and Lazdins offered a summary of the most valuable lessons they learned. They reiterated the importance of owning your own dependencies, structuring projects for scale, and designing for KMP from the outset. By sharing their experiences with a real-world, large-scale project, they provided the Kotlin community with actionable insights that can be applied to projects of any size. The session served as a powerful testament to the capabilities of Kotlin Multiplatform and the importance of a thoughtful, strategic approach to software development at scale.
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[DevoxxUK2025] Kotlin: The New and Noteworthy
Anton Arhipov, a developer advocate from JetBrains, captivated the DevoxxUK2025 audience with an overview of Kotlin’s recent advancements and future roadmap. Focusing on Kotlin 2.0’s K2 compiler and upcoming features like guard conditions, context parameters, rich errors, and name-based destructuring, Anton highlighted how Kotlin balances conciseness, safety, and expressiveness. His interactive talk, enriched with personal anecdotes and live demos, underscored Kotlin’s evolution as a versatile, multi-platform language that empowers developers to write robust, readable code.
Kotlin 2.0 and the K2 Compiler
Anton introduced Kotlin 2.0, released nearly a year ago, emphasizing the K2 compiler’s new front-end intermediate representation (FIR) and control flow engine. K2 improved compilation performance by 40% in IntelliJ IDEA Ultimate, fixed numerous small bugs, and provided a scalable foundation for future features. By desugaring complex constructs (e.g., if to when expressions, for loops to iterators), K2 enhances smart casts and type inference, enabling seamless handling of nullable types and complex expressions without manual casting.
Guard Conditions for Safer Control Flow
Set to stabilize in Kotlin 2.2, guard conditions enhance when expressions by allowing conditional checks without variable binding. In a demo, Anton showed processing orders with guard conditions to handle subscriptions and discounts, reducing repetition and ensuring exhaustiveness. Unlike Java’s pattern matching, Kotlin leverages existing destructuring to avoid redundancy, with guard conditions adding logical safety by enforcing checks (e.g., amount > 100) directly in when branches, minimizing errors in complex control flows.
Name-Based Destructuring for Robustness
Anton discussed name-based destructuring, planned for experimental release in Kotlin 2.4. Unlike positional destructuring, which risks logical errors during refactoring, name-based destructuring matches variable names to class properties, improving readability and safety. This feature extends to non-data classes and sealed hierarchies, with plans to deprecate positional destructuring in future versions (e.g., Kotlin 3.0), ensuring long-term language consistency while maintaining backward compatibility.
Context Parameters for Scoped APIs
Context parameters, entering beta in Kotlin 2.2, enable scoped extension functions for type-safe builders, often mistaken for DSLs. Anton demonstrated a client-building DSL where an infix extension function for dates (e.g., 10 March 2000) was restricted to a specific context, preventing global namespace pollution. This feature supports library developers in creating intuitive APIs, such as dependency injection-like logger scoping, reducing boilerplate and enhancing code clarity without compromising safety.
Rich Errors for Expressive Error Handling
Planned for experimental release in Kotlin 2.4, rich errors (previously called union types for errors) introduce a new error class syntax to distinguish error types explicitly. In a demo, Anton showed how rich errors improve over null-based error handling in functions like fetchUser and parseUser, enabling clear differentiation between network and parsing errors. Using when expressions, developers gain exhaustiveness checks and readable error handling, avoiding the verbosity of sealed hierarchies or result types.
Enhancing Compiler Safety with Return Value Checks
Anton highlighted a Kotlin 2.2 feature that mandates checking return values for standard library functions, preventing logical errors like missing return statements or incorrect function calls (e.g., using sort instead of sorted). By marking core functions with annotations, the compiler issues warnings for unused return values, reducing bugs like those in a demo where sorting a mutable list failed due to an overlooked return. This opt-in feature will expand to application code, enhancing reliability.
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[KotlinConf2025] Build your Kotlin and Android apps with Buck2
Sergei Rybalkin, a software engineer from Meta, introduced the audience to Buck2, an open-source build system that is now equipped to support Kotlin and Android applications. In a concise and informative presentation, Rybalkin detailed how Buck2, a successor to the original Buck system, addresses the need for a fast and scalable build solution, particularly for large-scale projects like those at Meta. The talk centered on Buck2’s core principles and its capabilities for accelerating development cycles and ensuring consistent, reliable builds.
The Power of a Scalable Build System
Rybalkin began by outlining the motivation behind Buck2. He explained that as projects grow in size and complexity, traditional build systems often struggle to keep up, leading to slow incremental iterations and hindered developer productivity. Buck2 was designed to overcome these challenges by focusing on key areas such as parallelism and a highly opinionated approach to optimization. The talk revealed that Buck2’s architecture allows it to execute build tasks with remarkable efficiency, a crucial factor for Meta’s own internal development processes. Rybalkin also touched on advanced capabilities like Remote Execution and the Build Tools API, which further enhance the system’s performance and flexibility.
A Blueprint for Optimization
The presentation also shed light on Buck2’s philosophy of “opinionated optimization.” Rybalkin clarified that this means the system takes a firm stance on how things should be done to achieve the best results. For example, if a particular feature or integration does not perform well, the Buck2 team may choose to drop support for it entirely, rather than provide a subpar experience. This selective approach ensures that the build system remains fast and reliable, even as it handles a multitude of dependencies and complex configurations. Rybalkin underscored the fact that the open-source version of Buck2 is almost identical to the internal solution used at Meta, offering the community the same powerful tools and optimizations that drive one of the world’s largest development teams. He concluded by encouraging the audience to try Buck2 and provide feedback, underscoring the collaborative nature of open-source development.
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[KotlinConf2024] Compose Multiplatform Evolves on iOS and Beyond
At KotlinConf2024, Sebastian Aigner, a JetBrains developer advocate, unveiled advancements in Compose Multiplatform, now in beta for iOS and alpha for web. Extending beyond business logic, Compose enables shared UI across platforms, integrating native capabilities. Sebastian showcased new common APIs—previews, resources, lifecycle, navigation, and UI testing—alongside iOS-specific enhancements like accessibility and scroll physics. Through live demos, he demonstrated how these features simplify cross-platform development, inviting developers to shape Compose’s future with feedback.
A Year of Progress for Compose Multiplatform
Since its debut at KotlinConf2023, Compose Multiplatform has matured significantly. Sebastian highlighted its role in sharing UI code, complementing Kotlin Multiplatform’s business logic sharing. On Android, it leverages Jetpack Compose; on desktop, it powers JetBrains Toolbox; and on iOS, it reached beta status at KotlinConf2024. The web target hit alpha, broadening its reach. Progress spans accessibility, navigation, text input, and scroll physics, with most features now stable or experimental, ready for developers to adopt and refine through real-world use.
iOS-Specific Enhancements
Compose Multiplatform on iOS now feels native, thanks to revamped scroll physics mirroring iOS’s overscroll and spring effects. Sebastian demonstrated accessibility improvements, with components supporting VoiceOver and gesture navigation out of the box, provided content descriptions are added. Interop with SwiftUI allows popups to span the screen, and window insets APIs handle notches and dynamic islands, ensuring full-screen rendering. These enhancements make iOS apps built with Compose visually and functionally indistinguishable from native counterparts, enhancing user experience.
Common Resources for Seamless UI
The new common resources API simplifies asset management. Sebastian showed how to add drawables and strings in a composeResources directory, accessed via a type-safe res object. In a demo, he added a banner image and a localized conference description, with Fleet auto-generating accessors. Support for multimodule resources and translations (e.g., German dark mode) ensures flexibility. This API, familiar from Android, reduces boilerplate, letting developers focus on crafting polished, platform-agnostic UIs with minimal effort.
Lifecycle and View Models in Common Code
Compose Multiplatform now supports common lifecycle and view model APIs, enabling robust app architecture. Sebastian demonstrated a lifecycle logger tracking states like onCreate and onPause, with collectAsStateWithLifecycle ensuring efficient flow collection. In a view model demo, he outsourced mood-tracking logic, using a factory function to instantiate it. Integration with Koin for dependency injection and lifecycle-aware state collection streamlines development, making MVVM patterns viable across platforms without platform-specific workarounds.
Navigation for Cross-Platform Apps
Navigation, a cornerstone of multiplatform apps, is now available via a Jetpack Navigation-inspired API. Sebastian built a demo app with a fruit list and detail pages, using a NavHost and NavController for stack-based navigation. Features like window insets padding, animated transitions, and rememberSaveable for state persistence ensure a native feel. Type-safe routing with Kotlinx.serialization is in development, reducing errors. This API, while optional, simplifies porting Android navigation logic to iOS and beyond, enhancing developer productivity.
UI Testing and Community Feedback
A new common UI testing API allows writing tests once for all platforms. Sebastian showed a test verifying a composable’s text content, executed across targets. This reduces testing overhead, ensuring consistent behavior. He urged developers to try these features, citing the Compose Multiplatform portal (jb.compose) for documentation. Feedback via the Kotlin Slack and issue tracker is vital, as community input drives stabilization. With support for features like strong skipping mode and shared element transitions, Compose continues to evolve dynamically.
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[KotlinConf2024] Compose Multiplatform Evolves on iOS and Beyond
At KotlinConf2024, Sebastian Aigner, a JetBrains developer advocate, unveiled advancements in Compose Multiplatform, now in beta for iOS and alpha for web. Extending beyond business logic, Compose enables shared UI across platforms, integrating native capabilities. Sebastian showcased new common APIs—previews, resources, lifecycle, navigation, and UI testing—alongside iOS-specific enhancements like accessibility and scroll physics. Through live demos, he demonstrated how these features simplify cross-platform development, inviting developers to shape Compose’s future with feedback.
A Year of Progress for Compose Multiplatform
Since its debut at KotlinConf2023, Compose Multiplatform has matured significantly. Sebastian highlighted its role in sharing UI code, complementing Kotlin Multiplatform’s business logic sharing. On Android, it leverages Jetpack Compose; on desktop, it powers JetBrains Toolbox; and on iOS, it reached beta status at KotlinConf2024. The web target hit alpha, broadening its reach. Progress spans accessibility, navigation, text input, and scroll physics, with most features now stable or experimental, ready for developers to adopt and refine through real-world use.
iOS-Specific Enhancements
Compose Multiplatform on iOS now feels native, thanks to revamped scroll physics mirroring iOS’s overscroll and spring effects. Sebastian demonstrated accessibility improvements, with components supporting VoiceOver and gesture navigation out of the box, provided content descriptions are added. Interop with SwiftUI allows popups to span the screen, and window insets APIs handle notches and dynamic islands, ensuring full-screen rendering. These enhancements make iOS apps built with Compose visually and functionally indistinguishable from native counterparts, enhancing user experience.
Common Resources for Seamless UI
The new common resources API simplifies asset management. Sebastian showed how to add drawables and strings in a composeResources directory, accessed via a type-safe res object. In a demo, he added a banner image and a localized conference description, with Fleet auto-generating accessors. Support for multimodule resources and translations (e.g., German dark mode) ensures flexibility. This API, familiar from Android, reduces boilerplate, letting developers focus on crafting polished, platform-agnostic UIs with minimal effort.
Lifecycle and View Models in Common Code
Compose Multiplatform now supports common lifecycle and view model APIs, enabling robust app architecture. Sebastian demonstrated a lifecycle logger tracking states like onCreate and onPause, with collectAsStateWithLifecycle ensuring efficient flow collection. In a view model demo, he outsourced mood-tracking logic, using a factory function to instantiate it. Integration with Koin for dependency injection and lifecycle-aware state collection streamlines development, making MVVM patterns viable across platforms without platform-specific workarounds.
Navigation for Cross-Platform Apps
Navigation, a cornerstone of multiplatform apps, is now available via a Jetpack Navigation-inspired API. Sebastian built a demo app with a fruit list and detail pages, using a NavHost and NavController for stack-based navigation. Features like window insets padding, animated transitions, and rememberSaveable for state persistence ensure a native feel. Type-safe routing with Kotlinx.serialization is in development, reducing errors. This API, while optional, simplifies porting Android navigation logic to iOS and beyond, enhancing developer productivity.
UI Testing and Community Feedback
A new common UI testing API allows writing tests once for all platforms. Sebastian showed a test verifying a composable’s text content, executed across targets. This reduces testing overhead, ensuring consistent behavior. He urged developers to try these features, citing the Compose Multiplatform portal (jb.compose) for documentation. Feedback via the Kotlin Slack and issue tracker is vital, as community input drives stabilization. With support for features like strong skipping mode and shared element transitions, Compose continues to evolve dynamically.
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[KotlinConf2025] LangChain4j with Quarkus
In a collaboration between Red Hat and Twilio, Max Rydahl Andersen and Konstantin Pavlov presented an illuminating session on the powerful combination of LangChain4j and Quarkus for building AI-driven applications with Kotlin. The talk addressed the burgeoning demand for integrating artificial intelligence into modern software and the common difficulties developers encounter, such as complex setups and performance bottlenecks. By merging Kotlin’s expressive power, Quarkus’s rapid runtime, and LangChain4j’s AI capabilities, the presenters demonstrated a streamlined and effective solution for creating cutting-edge applications.
A Synergistic Approach to AI Integration
The core of the session focused on the seamless synergy between the three technologies. Andersen and Pavlov detailed how Kotlin’s idiomatic features simplify the development of AI workflows. They presented a compelling case for using LangChain4j, a versatile framework for building language model-based applications, within the Quarkus ecosystem. Quarkus, with its fast startup times and low memory footprint, proved to be an ideal runtime for these resource-intensive applications. The presenters walked through practical code samples, illustrating how to set up the environment, manage dependencies, and orchestrate AI tools efficiently. They emphasized that this integrated approach significantly reduces the friction typically associated with AI development, allowing engineers to focus on business logic rather than infrastructural challenges.
Enhancing Performance and Productivity
The talk also addressed the critical aspect of performance. The presenters demonstrated how the combination of LangChain4j and Quarkus enables the creation of high-performing, AI-powered applications. They discussed the importance of leveraging Quarkus’s native compilation capabilities, which can lead to dramatic improvements in startup time and resource utilization. Additionally, they touched on the ongoing work to optimize the Kotlin compiler’s interaction with the Quarkus build system. Andersen noted that while the current process is efficient, there are continuous efforts to further reduce build times and enhance developer productivity. This commitment to performance underscores the value of this tech stack for developers who need to build scalable and responsive AI solutions.
The Path Forward
Looking ahead, Andersen and Pavlov outlined the future roadmap for LangChain4j and its integration with Quarkus. They highlighted upcoming features, such as the native asynchronous API, which will provide enhanced support for Kotlin coroutines. While acknowledging the importance of coroutines for certain use cases, they also reminded the audience that traditional blocking and virtual threads remain perfectly viable and often preferred for a majority of applications. They also extended an open invitation to the community to contribute to the project, emphasizing that the development of these tools is a collaborative effort. The session concluded with a powerful message: this technology stack is not just about building applications; it’s about empowering developers to confidently tackle the next generation of AI-driven projects.