System Design AI Mastery: Architecting for Scale, Speed, Reliability - Full Day

Modern system design has entered a new era. It’s no longer enough to optimize for uptime and latency — today’s systems must also be AI-ready, token-efficient, trustworthy, and resilient. Whether building global-scale apps, powering recommendation engines, or integrating GenAI agents, architects need new skills and playbooks to design for scale, speed, and reliability.

This full-day workshop blends classic distributed systems knowledge with AI-native thinking. Through case studies, frameworks, and hands-on design sessions, you’ll learn to design systems that balance performance, cost, resilience, and truthfulness — and walk away with reusable templates you can apply to interviews and real-world architectures.

Target Audience

Enterprise & Cloud Architects → building large-scale, AI-ready systems.

Backend Engineers & Tech Leads → leveling up to system design mastery.

AI/ML & Data Engineers → extending beyond pipelines to full-stack AI systems.

FAANG & Big Tech Interview Candidates → preparing for system design interviews with an AI twist.

Engineering Managers & CTO-track Leaders → guiding teams through AI adoption.

Startup Founders & Builders → scaling AI products without burning money.

Learning Outcomes

By the end of the workshop, participants will be able to:

Apply a 7-step system design framework extended for AI workloads.

Design systems that scale for both requests and tokens.

Architect multi-provider failover and graceful degradation ladders.

Engineer RAG 2.0 pipelines with hybrid search, GraphRAG, and semantic caching.

Implement AI trust & security with guardrails, sandboxing, and red-teaming.

Build observability dashboards for hallucination %, drift, token costs.

Reimagine real-world platforms (Uber, Netflix, Twitter, Instagram) with AI integration.

Practice mock interviews & chaos drills to defend trade-offs under pressure.

Take home reusable templates (AI System Design Canvas, RAG Checklist, Chaos Runbook).

Gain the confidence to lead AI-era system design in interviews, enterprises, or startups.

Workshop Agenda (Full-Day, 8 Hours)
Session 1 – Foundations of Modern System Design (60 min)

The new era: Why classic design is no longer enough.

Architecture KPIs in the AI age: latency, tokens, hallucination %, cost.

Group activity: brainstorm new KPIs.

Session 2 – Frameworks & Mindset (75 min)

The 7-Step System Design Framework (AI-extended).

Scaling humans vs tokens.

Token capacity planning exercise.

Session 3 – Retrieval & Resilience (75 min)

RAG 2.0 patterns: chunking, hybrid retrieval, GraphRAG, semantic cache.

Multi-provider resilience + graceful degradation ladders.

Whiteboard lab: design a resilient RAG pipeline.

Session 4 – Security & Observability (60 min)

Threats: prompt injection, data exfiltration, abuse.

Guardrails, sandboxing, red-teaming.

Observability for LLMs: traces, cost dashboards, drift monitoring.

Activity: STRIDE threat-modeling for an LLM endpoint.

Session 5 – Real-World System Patterns (90 min)

Uber, Netflix, Instagram, Twitter, Search, Fraud detection, Chatbot.

AI-enhanced vs classic system designs.

Breakout lab: redesign a system with AI augmentation.

Session 6 – Interviews & Chaos Drills (75 min)

Mock interview challenges: travel assistant, vector store sharding.

Peer review of trade-offs, diagrams, storytelling.

Chaos drills: provider outage, token overruns, fallback runbooks.

Closing (15 min)

Recap: 3 secrets (Scaling tokens, RAG as index, Resilient degradation).

Templates & takeaways: AI System Design Canvas, RAG Checklist, Chaos Runbook.

Q&A + networking.

Takeaways for Participants

AI System Design Canvas (framework for interviews & real-world reviews).

RAG 2.0 Checklist (end-to-end retrieval playbook).

Chaos Runbook Template (resilience drill starter kit).

AI SLO Dashboard template for observability + FinOps.

Confidence to design and defend AI-ready architectures in both career and enterprise contexts.