[jbwagoner]

A bit more on the architecture: Each layer is a middleware that wraps the agent's execution loop. When an agent calls a tool or spawns a subagent, the request passes through the stack: Agent Request → SUTRA (rate limit) → DHARMA (permissions) → SANGHA (skill check) → KARMA (cost) → Execute ↓ Agent Response ← SILA (audit log) ← METTA (sign) ← BODHI (isolate) ← NIRVANA (kill if needed) ← Policies are YAML: yamlpermissions: file_system: read: ["/data/*"] write: [] network: allowed_domains: ["api.anthropic.com"] cost: max_per_request: 0.10 max_per_session: 5.00

kill_conditions: - token_count > 100000 - execution_time > 300s - error_rate > 0.5 The key insight from running agents in production: most failures aren't the model being malicious — they're the model being helpful in ways you didn't anticipate. DHARMA and SANGHA catch those before they execute. Happy to go deeper on any layer.