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Your 7-Day AI Architect Sprint

Each day is thematically sequenced — foundations first, then retrieval, then agents, then design, infrastructure, security, and finally operations. Every day pairs overview notes (your study guide) with real articles (concrete examples). Don't skip days — each one builds on the last. Aim for 2–3 hours per day. That's enough to go deep without burning out.

Sunday
Foundations, Transformers & LLM Architecture
Start with the why before the how. Understand attention and transformers before touching any framework. These are the bedrock — every other topic in this plan builds directly on what you learn today.
3 topics 4 articles
▼
Study Topics
📚
AI Fundamentals
overview.txt
 ⚡
LLM Architecture ⭐
overview.txt
 🚀
Inference
overview.txt
Articles to Read
Attention Is All You Need — Explained Simply MD The Bitter Lesson — Explained Simply MD Building LLM Applications for Production MD GPT-Live: Voice AI Architecture Notes MD
Monday
RAG & Data Architecture
RAG is the most deployed AI pattern in enterprise. Master the full pipeline — ingest, chunk, embed, retrieve, rerank. This single day alone can answer 40% of AI architect interview questions.
2 topics 3 articles
▼
Study Topics
🔍
RAG ⭐⭐⭐
overview.txt
 🗄️
Data Architecture ⭐⭐⭐
overview.txt
Articles to Read
Notion's Vector Search — 10× Scale, 1/10th Cost MD Streaming LLM Inference — Continuous & Interruptible MD GPT-5.6: Smarter and Cheaper to Run MD
Tuesday
Agentic AI & Multimodal
Agents are where AI moves from Q&A to autonomous work. Focus on the loop: observe → plan → act → observe. Understand tool calling, memory, and LangGraph deeply — this is where most new AI Architect roles are moving.
2 topics 4 articles
▼
Study Topics
🤖
Agentic AI ⭐⭐⭐
overview.txt
 🎨
Multimodal
overview.txt
Articles to Read
Building Effective AI Agents — Easy Notes MD Writing Better Tools for AI Agents MD Managed Agents — Easy Notes MD Multi-Agent Application Step-by-Step Learning MD
Wednesday
AI System Design & Economics
This is where your 16 years of engineering become your superpower. You're not learning AI here — you're applying Days 1–3 to real-world architecture problems. Practice designing end-to-end systems. Always ask: "Is this AI solution economically viable?"
2 topics 5 articles
▼
Study Topics
🏗️
AI System Design ⭐⭐⭐
overview.txt
 💰
AI Economics ⭐⭐⭐
overview.txt
Articles to Read
Helium — Architect & CTO Questioning Muscle MD Payment Reconciliation System — Architecture Guide MD NoSQL System Design — Architect & CTO Questioning MD System Design: Question Before Choosing Technology MD The High-Interest Credit Card of Technical Debt MD
Thursday
AI Infrastructure & Cloud Architecture
How do you actually serve 10,000 users? GPU sizing, quantization, KV cache, autoscaling. Make AWS your primary cloud — go deep on Bedrock and SageMaker. Your distributed systems background is a direct advantage here.
2 topics 2 articles
▼
Study Topics
🖥️
AI Infrastructure ⭐⭐⭐
overview.txt
 ☁️
Cloud AI ⭐⭐⭐
overview.txt
Articles to Read
MRC: How OpenAI Built a Network for 100,000+ GPUs MD Speeding Up Agentic Workflows with WebSockets MD
Friday
Security, Governance & Evaluation
In fintech, this is non-negotiable. Know OWASP Top 10 for LLMs cold. Being strong on security and governance is a major differentiator at VP / Architect level. Also answer: "How do you know your AI system actually works?" — that's evaluation.
3 topics 5 articles
▼
Study Topics
🔐
AI Security ⭐⭐⭐
overview.txt
 ⚖️
AI Governance
overview.txt
 📊
AI Evaluation ⭐⭐⭐
overview.txt
Articles to Read
AI Agents — Guardrails Architecture & Sandboxing MD Guardrails, Schema-Driven Generation & Local Security MD Securing AI Agents — Virtualized Harness Runtime (VHRN) MD Leviath: Structure and Reliability in AI Agents MD Demystifying Evals for AI Agents MD
Saturday
LLMOps, Observability & Final Drills
The final layer: how do you run AI in production reliably? Monitoring, drift detection, canary deploys, harness design. Finish with the interview drills — by now all the pieces connect. Review everything, then practice designing a system end-to-end from scratch.
1 topic 14 articles
▼
Study Topics
⚙️
LLMOps ⭐⭐⭐
overview.txt
Articles to Read
AI Observability — Architect's Notes MD Architect-Level AI Fine-Tuning Interview Drill MD Effective Harnesses for Long-Running Agents MD Harness Design for Long-Running AI Apps MD Disaster Recovery System Design — Interview Guide MD AI Monitoring — Architect's Notes MD Context Window — 5-Minute Architect Guide MD Decoding Strategies — 5-Minute Architect Guide MD Fine Tuning — 5-Minute Architect Guide MD GPU Basics for LLMs — 5-Minute Architect Guide MD KV Cache — 5-Minute Architect Guide MD LLM Model Serving & APIs — 5-Minute Architect Guide MD Quantization — 5-Minute Architect Guide MD Transformers — 5-Minute Architect Guide MD
Article Notes & Deep Dives
🤖ai-agents
8▼
Building Effective AI Agents — Easy NotesMD Writing Better Tools for AI AgentsMD Demystifying Evals for AI AgentsMD Effective Harnesses for Long-Running AgentsMD Harness Design for Long-Running AI AppsMD Managed Agents — Easy NotesMD Multi-Agent Application Step-by-Step LearningMD Speeding Up Agentic Workflows with WebSocketsMD
⚡llm
5▼
Attention Is All You Need — Explained SimplyMD The Bitter Lesson — Explained SimplyMD GPT-5.6: Smarter and Cheaper to RunMD GPT-Live: Voice AI Architecture NotesMD Building LLM Applications for ProductionMD
✨new articles
5▼
AI Agents — Guardrails Architecture & SandboxingMD Guardrails, Schema-Driven Generation & Local SecurityMD Leviath: Structure and Reliability in AI AgentsMD Streaming LLM Inference — Continuous & InterruptibleMD Securing AI Agents — Virtualized Harness Runtime (VHRN)MD
🏗️Sys-Design
6▼
Helium — Architect & CTO Questioning Muscle TrainingMD Payment Reconciliation System — Architecture GuideMD NoSQL System Design — Architect & CTO QuestioningMD System Design: Question Before Choosing TechnologyMD The High-Interest Credit Card of Technical DebtMD Disaster Recovery System Design — Interview GuideMD
⚙️mlops
12▼
AI Observability — Architect's NotesMD Architect-Level AI Fine-Tuning Interview DrillMD MRC: How OpenAI Built a Network for 100,000+ GPUsMD AI Monitoring — Architect's NotesMD Context Window — 5-Minute Architect GuideMD Decoding Strategies — 5-Minute Architect GuideMD Fine Tuning — 5-Minute Architect GuideMD GPU Basics for LLMs — 5-Minute Architect GuideMD KV Cache — 5-Minute Architect GuideMD LLM Model Serving & APIs — 5-Minute Architect GuideMD Quantization — 5-Minute Architect GuideMD Transformers — 5-Minute Architect GuideMD
🔌mcp
1▼
Notion's Vector Search — 10× Scale, 1/10th CostMD
📋cover all this
3▼
Agentic AI — Interview NotesHTML MCP — Interview NotesHTML IDFC Coder RAG — Interview NotesHTML
Study Topic Overviews