# Kotlin Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/kotlin
> Markdown URL: https://aitinkerers.org/technologies/kotlin.md
> Technology record last updated: 2026-02-22T17:59:34Z
> Generated: 2026-09-22T15:36:29Z

Kotlin is a modern, statically typed, multiplatform language (JVM, JS, Native) from JetBrains, officially preferred by Google for Android development.

Kotlin is a pragmatic, general-purpose programming language developed by JetBrains, designed for conciseness, safety, and full interoperability with Java (it compiles to JVM bytecode). A key feature is its robust null-safety system, which eliminates NullPointerExceptions at compile time, boosting code reliability. Adopted by Google as the preferred language for Android, Kotlin is also heavily used for server-side development (e.g., with Spring and Ktor) and multiplatform projects, allowing developers to share code across Android, iOS, web, and desktop applications.

- Official technology site: https://kotlinlang.org
- Public AI Tinkerers demos and talks: 6
- Result page: 1 of 1

## Recent Public Talks and Demos

### [LLMs in Your Pocket: Running AI Fully On-Device](https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_3NT0ZUJ7U5o)

This project demonstrates how to run LLMs entirely on Android devices without relying on the cloud. During the live demo, I'll walk through the complete development workflow, model selection, application architecture, inference pipeline, performance evaluation, and optimization techniques. I'll also showcase the source code, repository structure, logs, and a fully working Android application running an on-device LLM in real time, along with the practical trade-offs and lessons learned while building it.

- Event context: AI Tinkerers Islamabad - August 15, 2026 — 2026-08-15 — Islamabad Rawalpindi
- Public talk page: https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_3NT0ZUJ7U5o

### [PicoClaw on MaixCam and OpenClaw on Android: Making a Claw Machine](https://manizales.aitinkerers.org/talks/rsvp_ltSlhnfnf4Y)

This is a technical teardown of how I got PicoClaw running on a MaixCam (K210-based) board and OpenClaw on Android client, turning a claw into a live phone hardware controller No slides. Just code, firmware, serial logs, and hardware. The demo will cover: 1. Porting PicoClaw to MaixCam PicoClaw was designed with a specific embedded environment in mind. I’ll walk through: Adapting the firmware to run on MaixCam Fixing build system assumptions Debugging boot and runtime issues We’ll look at: What broke immediately What silently failed What needed to be stubbed or reworked Timing quirks and hardware assumptions in the original firmware This section is mostly about embedded friction and reality. 2. Running OpenClaw on Android On the Android side, we’ll walk through: USB permission handling Threading model Command dispatch UI → Command translation We’ll examine: How commands are built How the app handles connection drops What assumptions the Android client makes about the firmware Where the abstraction leaks This is not a UI demo — it’s a transport-layer autopsy.

- Event context: 🚀 ¡13vo Encuentro de AI Tinkerers Manizales! 🤖 — 2026-02-26 — Manizales
- Public talk page: https://manizales.aitinkerers.org/talks/rsvp_ltSlhnfnf4Y

### [Using AI to channel Olympic excitement into skill development of homegrown athletes](https://toronto.aitinkerers.org/talks/rsvp_pFLrl0ONOj0)

I coach at a speedskating club, and one of the most difficult aspects of training young athletes is focusing them on technical aspects, tracking progress, and communicating tips and form correction effectively. This is a mobile app designed specifically with speedskaters in mind, and it gamifies the process of holding a "basic position" i.e. the crouched-over skating position. The user begins a game and video is captured. A wireframe is overlaid on the athlete, and the knee and hip angles are calculated. When the athlete goes into basic position, the user enters a session and begins to accrue a score. Score accrual multipliers are applied the closer to "perfect form" an athlete has, which has visual indicators displayed in realtime. Feedback from an AI coach is also given in realtime, which keeps the user engaged and focused. The user finishes a session after they stand up, and a report generated by AI is shown to help them understand what could be improved, as well as their final score. AI also uses the user's home country to query a public API on speedskater results and world records (ex. a Canadian user would be shown world records and stats of famous skaters such as Laurent Dubreuil). It helps users connect more with how strong the Olympic-level athletes are, along with recording progress and showing improvement over time.

- Event context: AI Tinkerers Toronto - February 2026 @ Cohere! — 2026-02-26 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_pFLrl0ONOj0

### [Quantization for Edge AI](https://nairobi.aitinkerers.org/talks/rsvp_ax9_20x3YMo)

So, I’ll be presenting my journey building my first Android APK, CHWs Augment. The focus will be on augmentation, because with the rise of AI, people often think of it as a replacement tool—but my project explores AI as an augmentor, designed to enhance human work rather than replace it. Technically, the project dives into quantization, Edge AI, and responsible AI, with an emphasis on equity: How can someone in a remote area benefit from AI just like someone in the city? How can we build free AI solutions that run efficiently on low-budget phones and scale augmentation to improve efficiency for CHVs? I’ll be doing a live demo of the APK, showing its workflow and the tangible ways it helps CHVs in remote areas. The focus is on impact, not revenue: building scalable AI that improves work and accessibility. Along the way, I’ll share the internals—the code, model design, and deployment choices—so the audience sees not just what it does, but how it was built. This project is imperfect and experimental, which is intentional: sharing raw builds accelerates learning, sparks collaboration, and pushes the boundaries of AI deployment in resource-constrained settings.

- Event context: AI Tinkerers Nairobi - Edition #4 (Nov 6, 2025) — 2025-11-06 — Nairobi
- Public talk page: https://nairobi.aitinkerers.org/talks/rsvp_ax9_20x3YMo

### [Giving AI Agents access to the mobile domain](https://sf.aitinkerers.org/talks/rsvp_eL_bTsbknUM)

AI Agent have been locked out of the mobile domain for too long. But they can finally act and mobile phones (especially Android) now to do all kinds of automations. With Droidrun you can automate every mobile app there is by providing the devtools to automate your own phone or scale your Automations with our Cloud API. I will present the cli and framework for a local phone and show how the cloud version look like.

- Event context: AI Infra Jam: Demos That Weren’t Possible Two Months Ago — 2025-09-25 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_eL_bTsbknUM

### [Kooging while Windsurfing: Building Advanced AI Agents with Kotlin](https://dublin.aitinkerers.org/talks/rsvp_GWirmkbfRcg)

Explore a pure Kotlin-based framework for building and running AI agents. This talk will demonstrate how Koog enables seamless integration with leading Large Language Models (LLMs) from providers like Google, OpenAI, Anthropic etc. We will cover key features such as custom tool creation, intelligent history compression, persistent agent memory, showcasing how Koog facilitates the development of advanced AI agents capable of tackling real-world problems.

- Event context: AI Tinkerers - Dublin Event (June) — 2025-06-26 — Dublin
- Public talk page: https://dublin.aitinkerers.org/talks/rsvp_GWirmkbfRcg

## Related Technologies

- [Android](https://aitinkerers.org/technologies/android) ([Markdown](https://aitinkerers.org/technologies/android.md)) — 11 public demos
- [Android Accessibility API](https://aitinkerers.org/technologies/android-accessibility-api) ([Markdown](https://aitinkerers.org/technologies/android-accessibility-api.md)) — 1 public demo
- [Android SDK & NDK](https://aitinkerers.org/technologies/android-sdk-ndk) ([Markdown](https://aitinkerers.org/technologies/android-sdk-ndk.md)) — 1 public demo
- [Android Studio](https://aitinkerers.org/technologies/android-studio) ([Markdown](https://aitinkerers.org/technologies/android-studio.md)) — 2 public demos
- [Anthropic API](https://aitinkerers.org/technologies/anthropic-api) ([Markdown](https://aitinkerers.org/technologies/anthropic-api.md)) — 66 public demos
- [C](https://aitinkerers.org/technologies/c-2) ([Markdown](https://aitinkerers.org/technologies/c-2.md)) — 6 public demos
- [C++](https://aitinkerers.org/technologies/c) ([Markdown](https://aitinkerers.org/technologies/c.md)) — 10 public demos
- [Droidrun](https://aitinkerers.org/technologies/droidrun) ([Markdown](https://aitinkerers.org/technologies/droidrun.md)) — 1 public demo
- [Gemini](https://aitinkerers.org/technologies/gemini) ([Markdown](https://aitinkerers.org/technologies/gemini.md)) — 188 public demos
- [GGUF](https://aitinkerers.org/technologies/gguf) ([Markdown](https://aitinkerers.org/technologies/gguf.md)) — 5 public demos
- [Java](https://aitinkerers.org/technologies/java) ([Markdown](https://aitinkerers.org/technologies/java.md)) — 8 public demos
- [K210](https://aitinkerers.org/technologies/k210) ([Markdown](https://aitinkerers.org/technologies/k210.md)) — 1 public demo
- [llama](https://aitinkerers.org/technologies/llama) ([Markdown](https://aitinkerers.org/technologies/llama.md)) — 48 public demos
- [LlamaIndex](https://aitinkerers.org/technologies/llamaindex) ([Markdown](https://aitinkerers.org/technologies/llamaindex.md)) — 12 public demos
- [LLMs](https://aitinkerers.org/technologies/llms) ([Markdown](https://aitinkerers.org/technologies/llms.md)) — 83 public demos
- [MaixCam](https://aitinkerers.org/technologies/maixcam) ([Markdown](https://aitinkerers.org/technologies/maixcam.md)) — 1 public demo
- [MediaPipe](https://aitinkerers.org/technologies/mediapipe) ([Markdown](https://aitinkerers.org/technologies/mediapipe.md)) — 7 public demos
- [ONNX](https://aitinkerers.org/technologies/onnx) ([Markdown](https://aitinkerers.org/technologies/onnx.md)) — 83 public demos