Production-Grade AI Agent Architecture: The Hermes Runtime That Keeps Agents Alive
19 days ago 高效码农Production-Grade AI Agent Architecture: A Deep Dive into the Hermes Runtime Treating an AI Agent as nothing more than a ReAct loop wrapped around an LLM works fine in a demo. Ship it to production, and it’ll collapse within three days. It’s not the model’s fault—it’s the missing runtime. The Real Question: What Is an Agent Framework Actually Solving? Over the past two years, I’ve built my fair share of Agent applications. I started with quick LangChain prototypes—basic chatbots that barely held context. But eventually, I needed something that could run inside Feishu (Lark), read local files, call internal APIs, …
OpenClaw v2026.6.1: Self-Healing AI Agents & Multi-Channel Messaging – What’s Inside?
2 months ago 高效码农OpenClaw v2026.6.1 Release: Resilient Agents, Multi‑Channel Messaging, and a Complete Skill Workshop Core question this article answers: How can AI agents stay stable and self‑healing in real‑world, unpredictable environments — network flaps, failed tool calls, and concurrent multi‑platform messages? OpenClaw v2026.6.1 provides a systematic answer. This release focuses on runtime recovery, channel stability, the full Skill Workshop workflow, and storage performance optimizations. Whether you are an operator running multiple chat bots or a product engineer building internal AI assistants, these improvements will lower troubleshooting costs and deliver a smoother end‑user experience. 1. Agent & Runtime: From “Crash‑to‑Stop” to “Graceful Self‑Healing” …