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Why AI Agent Runtimes Need a 'Constitution': Lessons from Ironclaw and the Rise of Policy-First Autonomous Systems

Originally published on tamiz.pro . Introduction Autonomous AI agents are transitioning from research prototypes to production-critical systems.

  • Autonomous AI agents perform critical tasks requiring safety measures.
  • Constitution for AI agent runtimes addresses alignment and reliability issues.
  • Ironclaw runtime case study demonstrates challenges and policy-first solutions.

One terminal, two trust levels โ€” running Claude Code against a real subscription and a cheap proxy

Part of an ongoing series on model routing and trust tiering for agentic coding tools. This one's the boring, working half โ€” no bug hunt, just a setup that's been running clean across two machines.

  • Claude Code runs on two trust levels using a real subscription and a cheap proxy
  • Self-hosted proxy translates Anthropic-format requests to DeepSeek V4
  • Proxy config separates planning/review tasks from high-volume, low-stakes work

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