book

System Design with AI Interview Guide : Designing Scalable, Agentic, and Defensible Systems

Name: System Design with AI Interview Guide : Designing Scalable, Agentic, and Defensible Systems
Author: Rohit Bhardwaj
ISBN: 9798868827822

by Rohit Bhardwaj

September 2026

777 pages

19h 6m

English

Apress

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System Design with AI Interview Guide
Foreword 1
Foreword 2
Introduction
The Friday Night FailureWhat the Failure Taught MeWhy AI Raises the StakesWhat This Book TeachesHow to Read This BookThe Promise to the Reader
Preface
Why I Wrote This BookThe Shift in System DesignWho This Book Is ForWhat You Will LearnHow to Use This BookCompanion GitHub RepositoryNavigating the BookExample DomainsA Final Word Before We Begin
Acknowledgments
Table of Contents
About the Author
About the Technical Reviewer
Part I: System Design Methodology
DrawBefore You DrawWhy This Matters More in the AI EraThe Running Example: DreamMartWhat Part I Gives YouBefore You Move OnTransition to Chapter 1

1. The 7-Step System Design Method
1.1 Introduction: Think Before You Draw1.2 What Interviewers Are Actually Evaluating1.3 The 7 Steps at a GlanceStep 1: Clarify Requirements and ConstraintsStep 2: Understand the Domain and UsersStep 3: Empathize with the Customer JourneyStep 4: Define Business Capabilities and BoundariesStep 5: Design High-Level Architecture with ARCHVIEWStep 6: Deep-Dive Critical ComponentsStep 7: Validate, Scale, and Stress-Test1.4 Mini Example: DreamMart Checkout1.5 Why Order Matters1.6 AI-Specific Blind Spots the Method Prevents1.7 How to Use the Method in Interviews vs. Production1.8 The Most Common Mistake1.9 A Simple Mental Model for Applying the Method1.10 What Breaks If You Skip This Method1.11 Chapter Summary1.12 Architect’s Reflection1.13 Transition to Chapter 2: Understanding the Business Domain1.14 Interview Practice and Assignments1. The 7-Step Warm-Up Question2. Requirements and Constraints Question3. Customer Journey and Trust Question4. AI Authority and Boundaries Question5. Senior Architect Stress-Test Question1.15 GitHub Companion Artifacts
2. Understanding the Business Domain
2.1 Introduction2.2 Domain Understanding Is an Architectural Skill2.3 What Architects Mean by “Domain”2.4 Domain Questions That Change Architecture2.5 How Domain Ignorance Breaks Systems2.6 Domain Shapes Architecture Before You Draw AnythingMini Example: DreamMart Domain Questions2.7 Business Models Are Architectural Forks, Not Variations2.8 Domain Thinking in Interviews2.9 What Breaks If You Skip Domain Understanding2.10 Chapter Summary2.11 Architect’s Reflection2.12 Transition to Chapter 3: Understanding the User Journey2.13 Interview Practice and Assignments1. Domain Understanding Warm-Up Question2. Actor and Journey Question3. Business Capability Mapping Question4. AI Opportunity and Boundary Question5. Senior Architect Domain-to-Architecture Question2.14 GitHub Companion Artifacts
3. Customer Journeys
3.1 Introduction3.2 Systems Do Not Fail Everywhere. They Fail Somewhere.3.3 The Myth of the Average User3.4 Journeys Are Behavioral Sequences, Not Screens3.5 Where Latency, Failure, and Consistency Actually Matter3.6 AI Changes the Journey in Dangerous Ways3.7 Designing for Escalation, Recovery, and Trust3.8 Operationalizing Empathy3.9 Journey Thinking in Interviews3.10 What Breaks If You Skip Customer Journey Thinking3.11 Chapter Summary3.12 Architect’s Reflection3.13 Transition to Chapter 4: Business Capabilities3.14 Interview Practice and Assignments1. Customer Journey Warm-Up Question2. Trust Moment Question3. Friction and Failure Question4. AI Customer Assistant Question5. Senior Architect Experience-to-Architecture Question3.15 GitHub Companion Artifacts
4. Business Capabilities
4.1 Introduction4.2 Capabilities Are Responsibilities, Not Functions4.3 Translating Journey Moments into CapabilitiesMini Example: DreamMart Checkout and Refund Capability4.4 Capability Boundaries: Define What the System GuaranteesWhere Boundaries Collapse4.5 AI Changes Capability Boundaries and Risk OwnershipWhere AI Must Not Decide AloneDrift Is a Boundary Problem4.6 The Final Test of a Capability4.7 Capability Thinking in InterviewsHow Senior Answers Sound4.8 What Breaks If You Skip Capability Thinking4.9 Chapter Summary4.10 Architect’s Reflection: Where Responsibility Actually Lives4.11 Transition to Chapter 54.12 Interview Practice and Assignments1. Capability Mapping Warm-Up Question2. Capability Boundary Question3. AI Capability Placement Question4. Ownership and Accountability Question5. Senior Architect Capability-to-Architecture Question4.13 Companion Repository
5. Structuring Architecture with ARCHVIEW
5.1 Introduction5.2 From C4 to C4+ to ARCHVIEW5.3 The Five ARCHVIEW Perspectives5.4 How to Use Each ARCHVIEW PerspectiveContext PerspectiveCapability PerspectiveInteraction PerspectiveDecision PerspectiveRecovery Perspective5.5 Worked Example: Checkout Recovery AssistantIntent View: Name the Unacceptable FailureCapability View: Separate Where AI Helps from Where AI Can Break the SystemC4+ View: Show Reasoning, Retrieval, Guardrails, and OversightInteraction and Decision Views: Control the Risk PathSafety and Escalation View: Define When the Agent Must StopOwnership View: AI Is a Team Sport5.6 ARCHVIEW in Interviews: How to Use It Without Drawing EverythingSample Interview Answer: DreamMart Checkout5.7 Where ARCHVIEW Returns in Part III5.8 What Breaks If You Skip ARCHVIEW5.9 Chapter Summary5.10 Architect’s Reflection5.11 Transition to Chapter 6—AI Architecture Primitives5.12 Interview Practice and Assignments1. High-Level Architecture Warm-Up Question2. Architecture View Question3. Synchronous vs. Asynchronous Design Question4. AI Architecture Integration Question5. Senior Architect Trade-Off and Defense Question5.13 Companion Repository
Part II: System Design Fundamentals
.Before You Trust the DiagramPart II at a GlanceWhy These Fundamentals Are Not BasicThe DreamMart Thread ContinuesThe Mechanics That Make Guarantees BelievableHow Part II Is OrganizedThe Mistake Readers Still Make After Part IIf You Read Part II Without Part IWhere Your Architecture Agreement Gets TestedThe Executive Question: Which One Saves the Most Money?What You Will Be Able to Answer by the End of Part IITransition to Chapter 6
6. AI Architecture Primitives
6.1 Introduction6.2 Authority: Who Is Allowed to Act, Not Just Call6.3 Commitment: The Moment You Stop Suggesting and Start Owning6.4 Time: Which Clock Wins, and Where That Rule Is Written6.5 Degradation: The Refusal Lines That Keep You Honest6.6 Evidence and Replay: If Legal Asks Why, What Must Exist?6.7 Ownership: Who Can Stop the System, and What Triggers That Stop6.8 A Design-Review Walkthrough: One Capability, All Six Primitives6.9 Operational Kit: The Three ArtifactsDecision Replay Card: Minimum SpineAuthority Envelope: Minimum SpineStop Authority SOP: Minimum Spine6.10 Worked Example: DreamMart Order Modification6.11 How to Use the Primitives in an Interview6.12 Chapter Summary6.13 Architect’s Reflection6.14 Transition to Chapter 76.15 Interview Practice and Assignments1. Six-Primitives Warm-Up Question2. Authority Boundary Question3. Commitment Question4. Time Policy Question5. Degradation and Refusal-Line Question6. Evidence and Replay Question7. Ownership and Stop Authority Question8. Senior Architect Design-Review Question6.16 GitHub Companion Artifacts
7. Trust, Safety, and the LLM-SHIELD Lens
7.1 Introduction7.2 Why AI Security Feels Different7.3 The LLM-SHIELD Lens: A Security Journey, Not a Checklist7.4 Scope: Define Capability Guarantees, Non-Negotiables, and Attack Surface7.5 Harden: Treat Prompts, Policies, and Guardrails as Production Assets7.6 Isolate: Zero Trust for Retrieval, Memory, Tools, and Data Paths7.7 Empower: Grant Autonomy Deliberately7.8 Live-Defend: Runtime Defense, AI Firewalls, Observability, and Replay7.9 Demonstrate and Evolve: Prove the Controls Still Work7.10 Applying LLM-SHIELD to Real SystemsDreamMart: Order Creation and Modification by an AgentDreamEntertainment: Ensemble Retrieval and the Multiple Truths TrapSales Development Representative Agent: Global Automation vs. Regional Reality7.11 Practical Design Review Checklist7.12 Architect’s Reflection7.13 Further Reading and References7.14 Interview Practice and Assignments1. LLM-SHIELD Warm-Up Question2. Scope and Unacceptable Failures Question3. Prompt and Policy Hardening Question4. Retrieval and Tool Isolation Question5. Autonomy and Empowerment Question6. Runtime Defense Question7. Demonstrate and Prove Controls Question8. Senior Architect LLM-SHIELD Design Review Question7.15 GitHub Companion Artifacts
8. ROCS: The Control System of Modern Architecture
8.1 Introduction8.2 The Core Claim: ROCS Is a Coupled Control System8.3 AI Inference Is a DAG, Not a Single Model Call8.4 The ROCS Loop: Sense, Interpret, Decide, Act, Prove8.5 Reliability Is Not Uptime8.6 Observability Is Not Dashboards8.7 Cost Is Behavior at Scale8.8 Sustainability Means Governable Change and Responsible Computing8.9 The ROCS Failure Anti-Pattern: Instrumented Indecision8.10 Three Scars That Prove ROCS Is RealDreamMart: When Inventory Lag Becomes ArchitectureDreamManufacturing: Digital Twin + Sensor DriftDreamFinance: Approvals Under Delayed Evidence8.11 ROCS Control Patterns for AI Inference8.12 The ROCS Design Review Canonical Table8.13 How This Chapter Connects to What Follows8.14 Architect’s Reflection8.15 Further Reading and References8.16 Interview Practice and Assignments1. ROCS Warm-Up Question2. AI Inference DAG Question3. ROCS Loop Question4. Reliability Is Not Uptime Question5. Observability and Decision Replay Question8.17 GitHub Companion Artifacts
9. Scale Is the Truth Serum
9.1 Introduction9.2 Scale Does Not Break Systems; It Reveals Them9.3 Average Load Is a Lie9.4 Capacity Estimation Is a Trust Exercise9.5 The Hidden Queues Before the Outage9.6 Bottleneck Analysis: Find the Narrowest Promise9.7 Scaling Patterns and Their Trade-offs9.8 Sharding and Partitioning: Scaling Truth by Splitting It9.9 Caching: Speed, Staleness, and Trust9.10 AI Changes Scale9.11 Designing for Scale: A Practical Walkthrough9.12 Interview Playbook: How to Talk About Scale Under Pressure9.13 What Breaks If You Skip Scale Thinking9.14 Chapter Summary9.15 Architect’s Reflection9.16 Transition to Chapter 109.17 Interview Practice and Assignments1. Scale as Truth Serum Question2. Average Load Is a Lie Question3. Capacity Estimation As a Trust Exercise Question4. Hidden Queues Before the Outage Question5. Bottleneck Analysis Question9.18 GitHub Companion Artifacts
10. Consistency Is a Trust Contract
10.1 Introduction10.2 Consistency Is Not a Data Property—It Is a Capability Promise10.3 The Moment That Matters: Actionability10.4 Consistency vs. Availability: The Lie We Tell Ourselves10.5 Classic Consistency Models Through a Trust Lens10.6 DreamFinance Scar: Balance Is Not Eventually Consistent10.7 DreamHealthcare Scar: Preliminary Is Not Harmless10.8 DreamTravel Scar: Confirmed Means Something10.9 The Most Common Failure Pattern: Unlabeled Consistency10.10 The Table You Should Use in Design Reviews10.11 Designing for Consistency Without Slowing Everything Down10.12 Consistency in AI-Enabled Systems: The New Failure Shape10.13 How Senior Architects Talk About Consistency in Interviews10.14 Consistency Lives Inside the ROCS Loop10.15 Chapter Summary10.16 Architect’s Reflection10.17 Transition to Chapter 1110.18 Interview Practice and Assignments1. Consistency As a Trust Contract Question2. Actionability Cliff Question3. Consistency vs. Availability Question4. Classic Consistency Models Through a Trust Lens Question5. AI Consistency and Admissible Evidence Question10.19 GitHub Companion Artifacts
11. Latency Is How Broken Architecture Becomes Visible
11.1 Introduction11.2 The Business Definition of Scale Is Not QPS11.3 Latency Is a Journey, Not an Endpoint Metric11.4 Tail Latency Changes User Behavior, and Behavior Becomes Load11.5 Moments of Commitment: Where Latency Becomes Trust11.6 The First Thing That Breaks at Scale Is Usually a Boundary11.7 Two Lies Teams Tell About Latency11.8 Latency Requires Evidence, Not Just MonitoringLatency Budget Template11.9 AI Latency: The Hidden DAG Behind One Answer11.10 How Senior Architects Talk About Latency in Interviews11.11 Chapter Summary11.12 Architect’s Reflection11.13 Transition to Chapter 1211.14 Interview Practice and Assignments1. Latency As Trust Pressure Question2. Journey-Weighted Latency Question3. Tail Latency Behavior Loop Question4. Moment of Commitment Question5. Latency Myths Question11.15 GitHub Companion Artifacts
12. Failure Is a System Behavior, Not an Event
12.1 Introduction12.2 Failure Is a Path, Not a Point12.3 Blast Radius Is an Architectural Decision12.4 Latency, Consistency, and Failure Reinforce Each Other12.5 AI Turns Failures Into Confident Wrongness12.6 Designing for Degradation, Not Collapse12.7 Escalation Is an Architectural Contract12.8 Failure in Interviews: How Senior Architects Talk About It12.9 Failure As Behavior: Design Review Table12.10 What Breaks If You Design Only for Success12.11 Chapter Summary and Transition to Chapter 1312.12 Architect’s ReflectionTransition to Chapter 1312.13 Interview Practice and Assignments1. Failure As a Path Question2. Blast Radius Question3. Latency-Consistency Failure Loop Question4. AI Confident Wrongness Question5. Degradation Ladder Question12.14 GitHub Companion Artifacts
13. Economics Is Architecture
13.1 Introduction13.2 The Core Claim: Economics Is What Your System Does Repeatedly13.3 FinOps Is Not Finance: It Is Architectural Control13.4 The Seven Questions That Make the Scars Visible13.5 ROCS for Economics: The Cost-Awareness Cycle13.6 Where Cost Multiplies: The Inference DAG Problem13.7 Sustainability Is Not Branding: It Is Scaling Without Regret13.8 ROCS for Sustainability: The Sustainability Cycle13.9 Three Dream Scars Where Economics Becomes a Trust ProblemDreamInsurance Scar: The Helpful Agent RunawayDreamLogistics Scar: Routing Waste Becomes Real-World WasteDreamMedia Scar: Fan-Out Intelligence and Marginal Value Collapse13.10 The Canonical Table This Chapter Should Own13.11 How Senior Architects Talk About Economics in Interviews13.12 Chapter Summary and Transition to Part III13.13 Architect’s Reflection13.14 References and Further Reading13.15 Interview Practice and Assignments1. Economics As System Behavior Question2. Unit of Value and Unit Cost Question3. FinOps As Architectural Control Question4. AI Cost Multiplier Question5. Cost Budget Contract Question13.16 GitHub Companion Artifacts
Part III: Applied Systems
Applied SystemsBefore You Draw the Applied SystemPart III at a GlanceWhy Applied Systems Are Commitment EnginesThe Same System Wearing Different ClothesHow Part III Is OrganizedThe Visual Grammar We Will ReuseWhat Goes in the Book vs. GitHubWhat You Should Be Able to Say by the End of Part IIITransition to Chapter 14
14. Ride-Sharing Systems
14.1 IntroductionHow This Chapter Applies Parts I and II14.2 Chapter 14 at a GlanceYour Three Non-Negotiable Guarantees14.3 The System You Are Actually Building14.4 Commitment Is the Center of the Architecture14.5 Worked Example: One Request in Motion14.6 Freshness Budgets: What Counts As Admissible RealityLatency Becomes Fairness DriftPricing Is a Commitment14.7 Inference Becomes a DAG, and Loops Hide ThereScar Box: The Night We Created a Rematch Storm14.8 Conflict Handling: Phase-Aware Outcomes14.9 Safety and Fraud: When Optimization Stops14.10 Worked Example: Conflict After Commit14.11 Interview Lens: What Seniors Sound LikeChapter SummaryArchitect’s Reflection14.12 Interview Practice and Assignments1. Ride-Sharing As a Commitment Engine Question2. Hold Token vs. Commit Token Question3. Freshness Budget Question4. Bounded Churn and Rematch Storm Question5. Pricing As a Defensible Commitment QuestionCompanion Artifacts for GitHub
15. Social Networking Systems
15.1 Introduction15.2 How This Chapter Applies Parts I and II15.3 The System You Are Actually Building15.4 Push vs. Pull Is Not a Performance Choice—It Is a Power Choice15.5 Your Three Non-Negotiable Guarantees15.6 Commitment Tokens: When Showing Becomes Amplifying15.7 Mode Is a Boundary: Profiling vs. Non-Profiling15.8 Admissible Evidence: What the System May Believe at Amplification Time15.9 Inference Becomes a DAG—and Loops Hide Inside It15.10 The Five Surfaces: Authority Boundaries You Must Enforce15.11 Stop Authority: Keeping Influence Stable Under Pressure15.12 ROCS Loops: Keeping Influence Stable, Provable, and Operable15.13 Scar Box: The Night Trending Stayed Green While Trust Went Red15.14 Worked Example: One Post in Motion15.15 Interview Lens: What Seniors Sound Like15.16 Chapter Summary15.17 Architect’s Reflection15.18 Interview Practice and Assignments1. Social Feed As an Influence Engine Question2. Push vs. Pull As a Power Boundary Question3. Visibility Grant vs. Amplification Token Question4. Recommendation Mode Boundary Question5. Admissible Evidence for Amplification Question15.19 Companion Artifacts for GitHub
16. E-Commerce Systems
16.1 Introduction16.2 How This Chapter Applies Parts I and II16.3 The System You Are Actually Building16.4 Architecture Is Admissible Behavior16.5 Your Three Non-Negotiable Guarantees16.6 Commitment Is the Center of the Architecture16.7 Freshness Budgets: What Counts As Admissible Reality16.8 Journeys: Where Latency, Failure, and Consistency Actually Matter16.9 Degradation: Refusal Lines That Keep You Honest16.10 Evidence and Replay: If Legal Asks Why, What Must Exist?16.11 Stop Authority: Who Can Stop the System and What Triggers That Stop16.12 ROCS Loops: Keeping DreamMart Stable, Provable, and Operable16.13 Movie Scene A: Order Creation16.14 Movie Scene B: Order Modification16.15 Interview Lens: What Seniors Sound Like16.16 Chapter Summary16.17 Architect’s Reflection16.18 Interview Practice and Assignments1. E-Commerce As a Commitment Engine Question2. Hold Token vs. Commit Token Question3. Freshness Budgets As Admissible Reality Question4. Checkout Latency and Duplicate Commitment Question5. Order Modification After Fulfillment Cutoff Question16.19 Companion Artifacts for GitHub
17. Messaging Systems
17.1 Introduction17.2 How This Chapter Applies Parts I and II17.3 Chapter 17 at a Glance17.4 The System You’re Actually Building17.5 Why Messaging Feels Different + Your Three Non-Negotiable Guarantees17.6 Commitment Tokens: What Counts as “This Happened.”17.7 Streams vs. Queues: What Your Infrastructure Is Really Promising17.8 Idempotency: Where You Store the Truth That Something Already Happened17.9 Ordering Scope: Pay for Order Only Where the Business Needs It17.10 Retry Budgets + DLQ: The Difference Between Resilience and Recursion17.11 Decision Replay Card: What Must Exist to Satisfy “Prove It Later.”17.12 Worked Example: One Event in Motion17.13 Scar Box: The Night Consumer Lag Looked Like Performance—Until Money Doubled17.14 Operate It: Stop Authority + ROCS Loops for Messaging17.15 Interview Lens: What Seniors Sound Like17.16 Chapter Summary17.17 Architect’s Reflection17.18 Interview Practice and Assignments1. Messaging As a Commitment Engine Question2. eventId vs. businessTxnId vs. effectId Question3. Idempotency Store Design Question4. Streams vs. Queues Question5. Retry Budget and DLQ Replay Question17.19 Companion Artifacts for GitHub
18. Auction Systems
18.1 Introduction18.2 How This Chapter Applies Parts I and IIFrom Earlier Book Lenses to Auction SystemsChapter 18 at a Glance18.3 Your Three Non-Negotiable Guarantees18.4 Commitment Tokens: Make the Boundary Unmissable18.5 Ending Rules: Hard Close vs. Soft Close18.6 Bidding Mechanics: Proxy Bidding, Increments, Reserve18.7 Freshness Budgets and Admissible Reality18.8 Manipulation and Fraud: Shill, Collusion, Bid Shielding18.9 Settlement and Fulfillment: Side Effects Equal Liability18.10 Operate It: ROCS, Stop Authority, and Re-enable18.11 Scar Box: The Night Close Created Two Realities18.12 Interview Lens: What Seniors Sound Like18.13 Chapter Summary18.14 Architect’s Reflection18.15 Interview Practice and Assignments1. Auction As a Commitment Engine Question2. Commitment Token Chain Question3. Hard Close vs. Soft Close Question4. Admissible Time and Late Bid Question5. Proxy Bidding, Increments, and Reserve Price Question18.16 Companion Artifacts for GitHub
19. Fraud Detection Systems
19.1 Introduction19.2 How This Chapter Applies Parts I and II19.3 Earlier Book Lens Mapping19.4 Chapter 19 at a Glance19.5 Chapter Promise19.6 Fraud Commitment Engine (ARCHVIEW Snapshot)19.7 Your Three Non-Negotiable Guarantees19.8 Tokens and Boundaries: Stop Advising, Start Enforcing19.9 Fraud Clocks: Admissible Reality and Label Delay19.10 Control Ladder: Reversibility As Architecture19.11 Adversary Loop and Drift: The System Is Being Gamed While You Tune It19.12 Evidence Tiers: What the System Is Allowed to Believe at Enforcement Time19.13 Operate It: Stop Authority + ROCS Loops19.14 Worked Example: One Case in Motion19.15 Scar Box: The Night the System Stayed Green While Trust Went Red19.16 Interview Lens: What Seniors Sound Like19.17 Chapter Summary19.18 Architect’s Reflection19.19 Interview Practice and Assignments1. Fraud As an Authority Allocation System Question2. Advisory Risk vs. Enforcement Token Question3. Fraud Clocks and Label Delay Question4. Reversible Control Ladder Question5. Evidence Tiers and Enforcement Admissibility Question19.20 Companion Artifacts for GitHub
20. Video Streaming Systems
20.1 Introduction20.2 How This Chapter Applies Parts I and II20.3 Earlier Book Lens Mapping20.4 Chapter 20 at a Glance20.5 Chapter Promise20.6 Your Three Non-Negotiable Guarantees20.7 Tokens and Boundaries: Name the Moment You Stop Serving Bytes and Start Owning Experience20.8 Ingest ➤ Encode ➤ Package: Make Time Addressable and Refuse Lies Early20.9 Distribution: Multi-CDN Is Not Redundancy; It Is Control20.10 Playback Is a Closed-Loop Control System, Not an App Screen20.11 Live + Low Latency: The Clock War You Must Declare20.12 DRM, Entitlement, and Policy Pinning: Playable Must Be Provable20.13 Ads Are Side Effects: SSAI/CSAI Decisions Must Be Replayable20.14 Decision Replay Card: What Must Exist to Satisfy Prove It Later20.15 Operate It: Stop Authority + ROCS Loops for Streaming20.16 Movie Scene: One Session in Motion20.17 Scar Box: The Night HD Was Green While Experience Was Red20.18 Interview Lens: What Seniors Sound Like20.19 Chapter Summary20.20 Remember This20.21 Architect’s Reflection20.22 Interview Practice and Assignments1. Streaming As a Continuous-Experience Commitment Engine2. Playback Token Chain and Session-Grant Boundary3. Ingest, Encode, and Package As Truth Gates4. Multi-CDN As Control, Not Redundancy5. Playback Control Ladder and ABR Governance20.23 Companion Artifacts for GitHub
21. Payment Systems
21.1 Introduction21.2 How This Chapter Applies Parts I and II21.3 Earlier Book Lens Mapping21.4 Chapter 21 at a Glance21.5 Why Payments Feel Different + Your Three Non-Negotiable Guarantees21.6 Tokens and Boundaries: Name the Moment You Stop Attempting and Start Owning21.7 The Liability Action Matrix21.8 Ledger Truth + Delayed Truth: Reconciliation Is the Price of Reality21.9 Idempotency and Ordering: Scoped Truth, Not Global Guarantees21.10 Retry Budgets + DLQ + Ambiguous Outcome Handling21.11 Operate It: Stop Authority + ROCS Loops21.12 Worked Example: One Payment in Motion21.13 Scar Box: The Night Everything Was Green and Money Duplicated21.14 Interview Lens: What Seniors Sound Like21.15 Chapter Summary21.16 Remember This21.17 Architect’s Reflection21.18 Interview Practice and Assignments1. Payments As a Liability Commitment Engine2. Token Chain and Side-Effect Boundary3. Idempotency versus Exactly-Once Question4. Ambiguous Capture Timeout Question5. Ledger Truth and Delayed Truth Question21.19 Companion Artifacts for GitHub
22. File Storage Systems
22.1 Introduction22.2 How This Chapter Applies Parts I and II22.3 Earlier Book Lens Mapping Table22.4 Chapter 22 at a Glance22.5 Chapter Promise22.6 Why Storage Feels Different and Your Three Non-Negotiable Guarantees22.7 Tokens and Boundaries: Name the Moment You Stop “Saving Bytes” and Start “Owning Truth”22.8 The Storage Clocks—Admissible Reality Is a Time Policy22.9 Integrity Is Not Checksum Theater, It’s How Truth Survives Systems22.10 Metadata Is the Real Storage System (and the Fastest Way to Lose Defensibility)22.11 Life Cycle and Deletion: The Liability Action Matrix Teams Will Actually Use22.12 AI Changes Storage into a Multi-truth System: Name What Is Regeneratable22.13 Operate It: Stop Authority + ROCS Loops for Storage22.14 Worked Example: One File Across Time (Write ➤ Index ➤ Hold ➤ Attack ➤ Restore ➤ Proof)22.15 Scar Box: The Night Storage Stayed Green While Truth Went Missing22.16 Interview Lens: What Seniors Sound LikeWhat to Say in the Interview22.17 Chapter Summary22.18 Remember This22.19 Architect’s Reflection22.20 Interview Practice and Assignments1. Storage As a Long-Lived Truth Engine2. Token Chain and Storage State Boundaries3. Stored vs. Discoverable Question4. Integrity Proof Chain Question5. Life Cycle and Deletion As Liability Actions22.21 Companion Artifacts for GitHub
23. Search Engine Systems
23.1 Introduction23.2 Why Search Feels Different: Three Non-Negotiable Guarantees23.3 Tokens and Boundaries: When Search Starts Owning Retrieval Truth23.4 The Search Clocks: Freshness Is a Time Policy23.5 Indexing Is Not Storage: It Is a Commitment to Future Retrieval23.6 Ranking Is Where Search Stops Being Neutral23.7 Retrieval Modes: Lexical, Vectorless, Vector, and Hybrid23.8 Query Understanding and Routing: Where Should the System Go?23.9 AI Changes Search into a Multi-truth System23.10 RAG Defendability: Vector, Vectorless, and Hybrid23.11 Search Liability Matrix: Actions Teams Must Defend23.12 Operate It: Stop Authority + ROCS Loops for Search23.13 Worked Journey: One Customer, Two Truth Paths23.14 Scar Box: The Day the Old Policy Outranked the Real One23.15 Interview Lens + Architect Reflection23.16 Interview Practice and Assignments1. Search As a Governed Visibility Engine2. Token Chain and Search Commitment Boundaries3. Freshness As a Time Policy4. Indexing Is Not Storage5. Ranking As a Decision Surface23.17 GitHub Companion Artifacts
24. Conclusion: Designing for Uncertainty Is the Job Now
24.1 Introduction24.2 What This Book Has Really Been Teaching YouBook Synthesis: From Method to Proof24.3 The Shift From Structure to Authority24.4 The Single Idea That Unifies the Book24.5 The Three Non-NegotiablesThe Three Non-Negotiables of Modern Architecture24.6 Admissible Reality: Clocks, Freshness, and Delayed TruthProduction Clocks and Their Architectural Meaning24.7 Stop Authority: Ownership Is the Ability to Become ConservativeStop Authority Mode Ladder24.8 ROCS Loops: How You Keep Systems Stable in the Real WorldROCS As a Closed Control Loop24.9 The Scar: “Payment Failed, Retrying” Was the Lie24.10 Interview Lens: What Does a Senior Sound LikeBoundary/Proof/Stop Interview Checklist24.11 The Architect’s Oath24.12 Your Next 30 Days As a System DesignerThirty-Day Practice Plan24.13 Stay Tuned: The Advanced Work Begins NextAdvanced Topics for the Next Volume24.14 Final Reflection24.15 Final Interview Readiness Check1. Commitment Boundary Question2. Admissible Reality and Freshness Question3. Stop Authority Question4. ROCS Loop Question5. Senior Interview Framing Question24.16 Companion Artifacts for GitHub
Index

Content preview from System Design with AI Interview Guide : Designing Scalable, Agentic, and Defensible Systems

Foreword 2

Enterprise architecture is being rewritten by AI.

The next generation of systems will not simply store data, execute workflows, and expose APIs. They will interpret intent, retrieve context, remember prior interactions, call tools, reason across policies, and act on behalf of people and businesses. This shift demands a new discipline: Agentic Enterprise Architecture.

In this book, Rohit Bhardwaj gives architects a practical way to think about that discipline. He moves beyond traditional system design and focuses on the concepts that now matter most: agentic memory, grounding, retrieval, policy-aware reasoning, tool-use boundaries, learning ...

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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

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System Design with AI Interview Guide : Designing Scalable, Agentic, and Defensible Systems

by Rohit Bhardwaj

Foreword 2

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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