We just published palyan-cli to npm. It is the first governance-first command line tool for multi-agent AI systems. Most CLI tools in the AI space help you write code faster. This one helps you govern what your agents actually do. palyan-cli wraps three MCP servers (Nervous System, Game, Ops) into 29 commands across three layers: governance (audit, snapshot, kill switch, drift detection), dispatch (agent management, scanning, inbox), and interoperability (A2A Agent Cards for

Governance for multi-agent AI systems. 7 rules. 19+ tools. Production-tested. Free (Community Edition) $0/month - Open source, npm install 7 core rules enforcement Preflight check for file protection Session handoff for context preservation Worklog for progress documentation Up to 5 governed agents Basic drift audit (3 scopes) Community support via GitHub Issues Best for: individual developers, experimentation, proof-of-concept npm install mcp-nervous-system Pro $49/month per

What happens when you give an AI the tools to manage other AIs? Not a chatbot. Not an assistant. A full autonomous operations manager that monitors, dispatches, fixes, and reports - 24 hours a day, 7 days a week, on a single VPS. We built her. Her name is Tamara. What Tamara Actually Does Tamara is not a concept or a demo. She is a production system running right now, managing 13 specialized AI agents serving users across 175 countries through Telegram, Instagram, Facebook, a

Everyone is building AI agents. Almost nobody is building the systems to manage them. This is the infrastructure gap of 2026. And it is the same gap that created billion-dollar companies in cloud computing (monitoring), microservices (orchestration), and containers (Kubernetes). The Pattern Every technology wave follows the same arc: 1. Build phase: Everyone builds the new thing (websites, APIs, containers, agents) 2. Scale phase: The new thing works, so people deploy more of

Multi-agent AI is here. Anthropic shipped Agent Teams. Orchestration frameworks handle hive mind coordination. Dev Team mode lets LLMs spawn parallel workers. Hundreds of startups are deploying autonomous agent fleets. Nobody is asking who governs those agents. 5 Failures of Ungoverned Agents We run 13 autonomous AI agents on a single VPS. Before governance, here is what happened: 1. Context loss. An agent would time out mid-task. The next session started from zero. No handof