Security enforced by architecture, not by AI self-discipline.
当治理是结构性的，Agent 能力才能安全流通。
Most AI agent frameworks enforce security through prompts, telling the LLM "don't do that." Prompt injection defeats this in seconds. We took a different approach:
| Typical Framework | Monstrum | |
|---|---|---|
| Unauthorized tools | In the schema; LLM told to refuse | Never sent to LLM; invisible, not denied |
| Parameter validation | Prompt instructions | Declarative scope engine; validated by code |
| Credentials | In env vars or prompts; LLM may leak | Encrypted vault; the model has never seen them |
| Budget enforcement | No structural guarantee | Just another scope dimension, checked by the same engine |
Prompt injection attacks the LLM's judgment. Our architecture doesn't rely on it.
When governance is structural, you can confidently hand real operations to AI. Multi-agent collaboration, budget enforcement, credential isolation, full-chain audit. All enforced by infrastructure, not instructions.