appendix-b

Appendix B. Step-by-step AI-assisted policy authoring

 

This appendix provides a hands-on, step-by-step walkthrough for using AI-assisted development tools to help author and review authorization policies. It is intended to be used alongside a code editor, following the examples in the companion repository as you read.

This appendix focuses on how to apply AI assistance in practice. It does not explain why AI can be useful for policy authoring or what role authorization plays in AI-enabled systems. Those topics are covered in chapter 17. It also does not introduce Cedar syntax or policy fundamentals, which are covered earlier in the book.

Readers should approach this appendix with the companion repository open in an AI-enabled editor such as Cursor. The steps are designed to be followed in order, with short pauses to interact with the tools and review results.

Note

The examples in this appendix make use of Cursor and the GitHub repository acme-cedar-ai-authoring (https://github.com/windley/acme-cedar-ai-authoring).

B.1 Why AI assistance is useful in policy authoring

Authorization policies encode intent in a form that must be precise, unambiguous, and deterministic. Translating business intent into executable policy is often difficult and error-prone, particularly as policies grow in number and complexity.

B.2 Recap: the ACME policy environment

B.3 Getting set up: the companion repository and Cursor

B.4 Providing the right context to the AI

B.5 A human-in-the-loop authoring workflow

B.6 Steps for modifying a policy set to achieve a specific outcome

Step 1: Establish the current behavior

Step 2: State the desired outcome precisely

Step 3: Ask the AI to explore implementation options

Step 4: Evaluate options as a human reviewer

Step 5: Apply the change deliberately

Step 6: Reflect on the change

Things to try

B.7 Guardrails and review checklist

B.8 Key takeaways