[dead]

Damn, that looks nice!

I built SteerPlane — an open-source runtime guardrail system for AI agents.

The problem: AI agents run autonomously, calling LLMs and tools in loops. Without runtime controls, a single agent can burn $50+ in minutes, get stuck in infinite loops, or call dangerous actions without oversight.

What it does: - Cost ceilings — auto-kills when spending exceeds $X - Step limits — prevents runaway execution - Loop detection — catches repeated action patterns - Full telemetry — every step logged with tokens, cost, latency - Dashboard — real-time visibility into all agent runs

One decorator. That's it: @guard(max_cost_usd=10, max_steps=50) def run_agent(): agent.run()

Stack: Python SDK, TypeScript SDK, FastAPI backend, Next.js dashboard

Links: - GitHub: https://github.com/vijaym2k6/SteerPlane - PyPI: pip install steerplane - npm: npm install steerplane

Currently building: policy engine (allow/deny actions), remote kill switch, and framework integrations.

Would love feedback from anyone running AI agents in production! What controls do you wish you had?