Show HN: Orloj – agent infrastructure as code (YAML and GitOps)
Hey HN, we're Jon and Kristiane, and we're building Orloj (<a href="https://orloj.dev" rel="nofollow">https://orloj.dev</a>), an open-source (Apache 2.0) orchestration runtime for multi-agent AI systems. You define agents, tools, policies, and workflows in declarative YAML manifests, and Orloj handles scheduling, execution, governance, and reliability.<p>We built this because running AI agents in production today looks a lot like running containers before Kubernetes: ad-hoc scripts, no governance, no observability, no standard way to manage the lifecycle of an agent fleet. Everyone we talked to was writing the same messy glue code to wire agents together, and nobody had a good answer for "which agent called which tool, and was it supposed to?"<p>Orloj treats agents the way infrastructure-as-code treats cloud resources. You write a manifest that declares an agent's model, tools, permissions, and execution limits. You compose agents into direc
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Show HN: Book Grounded AI Learning
I constantly ask Gemini/ChatGPT/Claude about books on a certain topic, then ask the llm to give me a summary of the book its chapters - this helps me: 1. keep the llm grounded as a real expert (instead of saying pretend to be an engineering expert, give it a distributed systems book and then ask opinions on it) 2. helps me discover and buy books! Once i go through book concepts and chat with llm about it, i'm more convinced to buy it and dig deeper on low level on it<p>So i built an app through Replit on it, try it on<p><a href="https://teach-me.replit.app/" rel="nofollow">https://teach-me.replit.app/</a><p>Cheers!