Polymarket ships a unified Python SDK, py-sdk, for building on their prediction market: constructing, pricing, signing, and submitting orders. It's currently in beta and moving fast, which is exactly where money path bugs like to hide. I've been running the SDK against live markets, so I pointed an audit pass at its order validation and signing code and found a real one. - Source: dev.to / about 2 months ago

Platforms like Kalshi and Polymarket have created an entirely different way of looking at Bitcoin. - Source: dev.to / 4 months ago

Success takes time. Polymarkethas faced skepticism multiple times, but founder @shayne_coplan and his team remained steadfast in their belief that prediction markets could enhance truth. In 2024, Polymarket achieved over $423M in volume and significantly impacted the U.S. Presidential election. Their conviction and persistence have truly paid off. - Source: dev.to / 6 months ago

That same account[0] has also already lost at least a 100k betting on similar middle eastern conflict markets. Not at all ruling out insider information, certainly looks suspicious, but it’s easy just to find one big win or winner. [0] https://polymarket.com/@magamyman. - Source: Hacker News / 6 months ago

Polymarket and similar platforms have proved something simple and powerful: price behaves like probability. Traders want to bet on elections, sports, and crypto outcomes with the speed and responsiveness of a modern exchange. - Source: dev.to / 9 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 / about 2 months 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 / 7 months ago

Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 10 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 / 10 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 / about 1 year ago