Summary of open source Kotlin Multiplatform samples (with platforms supported and key libraries used). The UI in all cases is implemented using either Compose or SwiftUI. Confetti 🔗github.com/joreilly/Confetti ✅ Android, Wear OS, Android Auto, Automotive OS, iOS, Compose for Desktop, JVM backend 📚Apollo GraphQL 📚Decompose 📚Koin 📚MultiplatformSettings BikeShare 🔗github.com/joreilly/BikeShar… ✅ Android, iOS, Compose for Desktop 📚Ktor 📚Realm 📚Koin PeopleInSpace 🔗github.com/joreilly/PeopleIn… ✅ Android, Wear OS, iOS, watchOS, macOS, Compose for Desktop, Compose for Web (JS and Wasm), Compose for iOS, JVM backend 📚Ktor 📚SQLDelight 📚Koin GalwayBus 🔗github.com/joreilly/GalwayBu… ✅Android, iOS, macOS 📚Ktor 📚SQLDelight 📚Koin 📚MultiplatformSettings FantasyPremierLeague 🔗github.com/joreilly/FantasyP… ✅Android, iOS, Compose for Desktop 📚Ktor 📚Realm 📚MultiplatformSettings MortyCompose 🔗github.com/joreilly/MortyCom… ✅Android, iOS 📚Apollo GraphQL 📚Koin 📚MultiplatformPaging StarWars 🔗github.com/joreilly/StarWars ✅Android, Wear, OS, iOS 📚Apollo GraphQL 📚Koin Chip-8 🔗github.com/joreilly/chip-8 ✅Android, Wear, OS, iOS, Compose for Desktop There are also a number of Kotlin Multiplatform related posts based on these samples at johnoreilly.dev/.

Worth staying up to watch. What a performance by the Knicks! 🏀 #nbafinals

We just open sourced the AppFunctions Testing Agent! 🧪 Manual deterministic testing & LLM-based agent evaluation 📱 Clean multi-module refactor of ChatApp with Wear OS support! Grab your API keys and check it out. #AndroidDev #AI #FridayDeploy github.com/android/appfuncti…

Have been using Fable 5 today and haven't really seen anything noticeably different from Opus so far but perhaps haven't give it something hard enough to work on!

Just got feedback from @kotlinconf talk. Of course you want to make everyone happy but I'll take this 😀

Claude Fable 5 changed how we work on the Claude Code team day to day. We used to verify that Claude did the work right. Now we verify that it's doing the right work. Here’s the 3 biggest changes:

Good morning Cambridge! Visiting Neat office here for first time since I came back.

I'll often get Claude to do a review of code it just generated and it frequently comes back with very good suggestions for things to change....just wonder why it doesn't make those changes initially!

More new friends made while hiking the Picos de Europa 😄

Latest Android Weekly Issue 729 is out! androidweekly.net/issues/iss… #AndroidDev #Kotlin

Breakfast in Bilbao

Build intelligent Android apps with Google's AI youtube.com/watch?v=_iuXykdl…

Announcing ADK for Kotlin & Android 0.1.0 → goo.gle/3PPKhq9 The first release of the experimental Android ADK is out. You can now build multi-agent workflows across on-device and Cloud models. Early feedback welcome!

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors. Available today at the same price.

"We think that with AI we can replace all of our Jr developers in our company" AWS CEO Matt Garman: "That's the dumbest thing I've ever heard"

Anyone know if/when it should be possible to run Qwen3.7 with @ollama ?

RAG vs Embeddings vs Vector Databases 𝗘𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀 turn data into numbers that capture meaning. Similar ideas end up close together, which makes semantic search possible. 𝗩𝗲𝗰𝘁𝗼𝗿 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 store and search embeddings. They help systems find information by meaning, not just exact keywords. 𝗥𝗔𝗚 uses retrieval to improve generation. It finds relevant context, adds it to the prompt, and helps the model answer with external knowledge. Each one solves different parts of the same problem: helping AI systems use external knowledge. ↳ Without embeddings, the system cannot compare meaning. ↳ Without a vector database, retrieval becomes hard to scale. ↳ Without RAG, retrieval is not integrated into the model’s response. These same concepts are key foundational building blocks for memory-aware AI agents. If you're learning agent memory, here's a great breakdown → lucode.co/agent-memory-artic… And if you want to go deeper into unified memory systems for agents, here's a more advanced deep dive → lucode.co/unified-memory-cor… What else would you add? —— ♻️ Repost to help others learn and grow. 🙏 Thanks to @OracleDevs for sponsoring this post. ➕ Follow me ( Nikki Siapno ) to improve at AI engineering.