Policy Engines

Centralized systems that evaluate rules and enforce access control decisions dynamically

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Introduction

Here are the essential insights about policy engines for AI agent authorization:

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You have learned how policy engines centralize authorization logic, enabling dynamic, context-aware access control for AI agents. You explored policy languages like Rego and Cedar, understood how engines evaluate rules, and mastered conflict resolution strategies. Use these principles to build secure, maintainable authorization systems that scale with your needs.

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Policy Engines

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Key Takeaways

1. Policy engines centralize authorization logic

2. Separate policies from code

3. Choose the right policy language

4. Evaluation performance matters

5. Deny overrides is the safest default

6. Test policies like you test code

7. Version and audit policy changes

8. Context is king for dynamic policies

9. Start simple and add complexity gradually

10. Policy engines enable zero-trust architecture