# AI use cases for Enterprise System Design (DrHazemAli/enterprise-system-design) Repo: [DrHazemAli/enterprise-system-design](https://github.com/DrHazemAli/enterprise-system-design) | Use cases: 3 | Page: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/ A source-grounded course and technical reference on enterprise system design, distributed systems, AI systems, and reliable Azure operations. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Design a reliable service with failure and capacity notes: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/design-reliable-service-with-failure-artifacts/ - Trace permission-aware retrieval in an AI feature: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/trace-permission-aware-ai-retrieval/ - Test an AI agent's tool authority with security principles: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/review-agent-tool-authority-with-cybersecurity-principles/ ## How to design a reliable service with failure and capacity notes with Enterprise System Design Repo: [DrHazemAli/enterprise-system-design](https://github.com/DrHazemAli/enterprise-system-design) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Follow the reliable service route from scale and consistency through caches, queues, and backpressure. **Who it is for:** A backend engineer who must explain how a service keeps working under load and partial failure. **The problem:** Scale, failure, and capacity reasoning is often skipped until traffic forces the issue. **The outcome:** A design note with requirements, failure modes, and capacity reasoning for one service. ### Steps 1. Run `git clone https://github.com/DrHazemAli/enterprise-system-design.git` 2. Run `cd enterprise-system-design` 3. Open reference/01-system-design-foundations/06-scale-from-one-to-one-million.md and read it. 4. Write one design artifact for your service: requirements, failure modes, and capacity reasoning, as the README's lesson guarantees describe. 5. Check the draft against the Azure Well-Architected Framework lens: reliability, security, cost optimization, operational excellence, and performance efficiency. ### Prompt to paste into your agent ```text Using the enterprise-system-design repository, read reference/01-system-design-foundations/06-scale-from-one-to-one-million.md, then write a design artifact for listing requirements, failure modes, and capacity reasoning. Verify that every failure mode names a detection signal. ``` ### Caveat The repository is a course and reference, so its terminal-style banners in the README are illustrative text, not tools to run. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/design-reliable-service-with-failure-artifacts/ ## How to trace permission-aware retrieval in an AI feature with Enterprise System Design Repo: [DrHazemAli/enterprise-system-design](https://github.com/DrHazemAli/enterprise-system-design) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Follow one AI query from identity through authorized retrieval and grounding to the response. **Who it is for:** An AI platform engineer deciding how retrieval must respect user permissions before an answer is generated. **The problem:** Permission-aware retrieval, token limits, and tool authority are easy to leave implicit in AI designs. **The outcome:** A boundary-by-boundary trace of one query with each authority check and owner named. ### Steps 1. Run `git clone https://github.com/DrHazemAli/enterprise-system-design.git` 2. Run `cd enterprise-system-design` 3. Open reference/02-data-and-retrieval/12-embeddings-and-vector-similarity.md and read how knowledge becomes searchable evidence. 4. Open reference/03-ai-control-plane/ and note who controls tokens, tools, state, and model selection. 5. Open principles/ai-systems/01-representation-authority-and-memory.md and apply its governing question to your design. ### Prompt to paste into your agent ```text Read the enterprise-system-design repository and trace a retrieval request for from user identity through authorization, retrieval, grounding, and response. Output a table of each boundary with its authority check and one unverified assumption. Verify that every boundary has a named owner. ``` ### Caveat The README covers AI systems as design reasoning, so the chapters do not supply a working retrieval implementation to deploy. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/trace-permission-aware-ai-retrieval/ ## How to test an AI agent's tool authority with security principles with Enterprise System Design Repo: [DrHazemAli/enterprise-system-design](https://github.com/DrHazemAli/enterprise-system-design) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Apply the zero-trust AI execution principle to each tool call an agent can make. **Who it is for:** A security reviewer approving an AI agent that can call tools or change systems. **The problem:** An authentic control is often assumed to prove that the intended object and consequence were authorized. **The outcome:** A list of consequences a compromised proposer could cause, each paired with the capability check that stops it. ### Steps 1. Run `git clone https://github.com/DrHazemAli/enterprise-system-design.git` 2. Run `cd enterprise-system-design` 3. Open principles/cybersecurity/01-zero-trust-ai-execution.md and read it. 4. Take the governing question for P03 from the principles domains table and answer it for the target agent. 5. Write one checklist item per tool the agent can call, naming the fresh, target-bound capability each call needs. ### Prompt to paste into your agent ```text Using the enterprise-system-design repository, read principles/cybersecurity/01-zero-trust-ai-execution.md and answer its governing question for . Output a list of each tool call the agent can make with the fresh, target-bound capability it needs. Verify that no tool call appears without a named capability check. ``` ### Caveat The principles are reasoning guidance, so the review still needs your own system's controls and evidence to confirm each check. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/drhazemali-enterprise-system-design/review-agent-tool-authority-with-cybersecurity-principles/