Java demo repository | Difficulty: Intermediate Java | Format: Seven chapters with code and exercises Build a Java assistant one capability at a time, following the rounds of Codepocalypse Now: LangChain4j vs. JetBrains Koog. Each chapter explains the API that introduces the next capability, gives you an experiment to run, and identifies a pattern you can use in your own application. The examples use LangChain4j builders and Java interfaces directly. ...
TLDR Meta’s director of AI alignment told her agent "confirm before acting." It deleted her entire inbox anyway. OpenClaw hit 250k GitHub stars in 60 days, its codebase hit 400,000 lines, and about 12% of its skill marketplace was malware. NanoClaw runs every agent in its own Linux container with 4,000 lines of code you can read in one sitting. I picked a third option. It runs on the JVM. ...
TLDR There are twelve million Java developers and the AI ecosystem built everything for Python first. LangChain4j fixes that. You can wire up an LLM, give it tools (database queries, API calls, search), and let it decide which tool to use and when. That’s an agent, built in Java. It handles prompt templates, chat memory, RAG pipelines, MCP support, and tool calling across 20+ LLM providers through a single API. ...