secure-ai-agent-coding

Build or review AI agents and LLM applications so their blast radius stays small, their behavior is auditable, and high-impact actions require explicit control.

Scale controls to the actual trust boundaries, data sensitivity, effects, and deployment. A read-only public-data assistant, a disposable coding sandbox, and a production payment agent need different controls. Keep authorization and isolation outside the model; leave architecture and implementation choices open when they preserve those guarantees. The reference catalog is a risk checklist, not a requirement to add every mechanism to every feature.

Decision Tree

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