Https://typequicker.com Building a typing application that helps you quickly learn and improve your typing. We believe everyone can type at 80wpm or more. It just takes a good tool to help them and a couple months of consistent practice. - Source: Hacker News / 20 days ago

Learning something new often can take as little 10-15 minutes a day of focused time. If you do it consistently, it becomes easier and easier to maintain, and it starts to require less and less mental capacity to start > You can learn new things. Pixel art, touch typing, 3d modelling, music, calligraphy, wood working, knitting, a language. Whatever is practical and calls to you, you can learn. Shameless plug: if... - Source: Hacker News / 29 days ago

Building the most effective typing application. https://typequicker.com. - Source: Hacker News / about 2 months ago

Building https://typequicker.com An AI first typing application. I think anyone can learn touch typing and potentially 2x their typing speed. We make typing practice engaging and data driven. - Source: Hacker News / 3 months ago

TypeQuicker (https://typequicker.com) - personalized and engaging typing application. Anyone can learn to type fast - I think it just takes the right tools to make it interesting enough for the users to use daily. - Source: Hacker News / 5 months ago

If you build on the JVM and want to use Qdrant, the official client is io.qdrant:client — and it's built for Java. Every call returns a ListenableFuture, requests are assembled with protobuf builders, and it drags a gRPC/Netty stack onto your classpath. From Kotlin, that means fighting the language:. - Source: dev.to / 11 days ago

The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago

Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 8 months ago

Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 9 months ago

James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 12 months ago