We built an operating system for AI agents that actually deploy and run autonomously — not just chat interfaces you have to babysit. The core idea: Agents should work like specialists on your team, not assistants you prompt all day. What that means in practice: 15 prebuilt production agents (legal, finance, marketing, operations, etc.) 32+ skills from the OpenClaw library (email, web search, browser automation, code execution, council deliberation, etc.) Deploy to Telegram, Slack, email, or dashboard Heartbeat scheduling for proactive agents (weekly reports, daily checks, etc.) BYOK support (Claude, GPT-4, Gemini, DeepSeek, local models) Portable Mind Format: every agent is a JSON file you own and can export Three layers that matter: 1. KARMA (cost governance) Agents with unlimited API access burn money fast. Every skill call is budget-tracked. You set spending limits. Agents that exceed budget get throttled, not shut down. 2. SILA (audit) Every agent action is logged with full context: what skill was called, what data was accessed, what was sent externally. SOC2/GDPR/HIPAA compliance isn't an afterthought — it's built into the execution layer. 3. SUTRA (orchestration) Council deliberation as a first-class skill. 8 specialist agents (Right View, Right Intention, Right Speech, etc.) can be invoked by any other agent. You get multi-perspective analysis without manually coordinating LLM calls. Why we built this: Most "agent frameworks" are libraries for developers to stitch together their own infrastructure. That's fine for engineers, but it leaves everyone else stuck with ChatGPT. We wanted something in between: opinionated infrastructure that handles deployment, security, and cost control — so you can focus on what your agents do, not how they run. Current state: Live in production $9/month Explorer tier (full platform access) Companion book: How to Use Autonomous Agents — free on Kindle March 1-5, 2026 16+ agent build examples across business, creative, and household domains The constraint we're designing around: Agents that "write code on the fly" are powerful in demos, brittle in production. Our bet: pre-audited, composable skills + user-defined constraints + transparent cost tracking = agents you can actually trust to run unsupervised. Built by: JB Wagoner (patent holder for transportable AI persona architecture, founder of Sutra.team) Feedback welcome — especially from people building agent systems in production. What's missing? What would make this more useful?