FDP 01 — AI-Native Full-Stack Product Engineering (60-Hour Faculty Programme)

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Course content

•Module 1: Product Thinking & the AI-Native Spine(15m)
•Session 1: What "AI-Native" Actually Means — The Spine, Not the Feature(150m)
•Session 1: What "AI-Native" Actually Means — The Spine, Not the Feature — Evaluation Rubric(10m)
•Session 2: Vertical Slices — Shipping Something Complete and Small(150m)
•Session 2: Vertical Slices — Shipping Something Complete and Small — Evaluation Rubric(10m)
•Session 3: Evals Before Features — Defining "Working" Without Determinism(150m)
•Session 3: Evals Before Features — Defining "Working" Without Determinism — Evaluation Rubric(10m)
•Module 1 Teaching Kit: Product Thinking & the AI-Native Spine(45m)

•Module 2: Frontend — React & Next.js(15m)
•Session 4: Rendering Models & the App Router — Server, Client & Where AI Lives(150m)
•Session 4: Rendering Models & the App Router — Server, Client & Where AI Lives — Evaluation Rubric(10m)
•Session 5: Data on the Client — Mutations, Forms & Optimistic UI(150m)
•Session 5: Data on the Client — Mutations, Forms & Optimistic UI — Evaluation Rubric(10m)
•Session 6: Streaming AI UX — Latency You Cannot Hide, Uncertainty You Must Show(150m)
•Session 6: Streaming AI UX — Latency You Cannot Hide, Uncertainty You Must Show — Evaluation Rubric(10m)
•Module 2 Teaching Kit: Frontend — React & Next.js(45m)

•Module 3: Backend & the API Layer(15m)
•Session 7: Choosing a Backend — Node, Django & Spring Boot on One Requirement(150m)
•Session 7: Choosing a Backend — Node, Django & Spring Boot on One Requirement — Evaluation Rubric(10m)
•Session 8: The API Contract — Resources, Errors, Idempotency & Long Work(150m)
•Session 8: The API Contract — Resources, Errors, Idempotency & Long Work — Evaluation Rubric(10m)
•Session 9: Identity, Authorisation & Multi-Tenancy for a Campus Product(150m)
•Session 9: Identity, Authorisation & Multi-Tenancy for a Campus Product — Evaluation Rubric(10m)
•Module 3 Teaching Kit: Backend & the API Layer(45m)

•Module 4: Data — SQL & NoSQL(15m)
•Session 10: Modelling the Domain in SQL — Schema, Constraints & Migrations(150m)
•Session 10: Modelling the Domain in SQL — Schema, Constraints & Migrations — Evaluation Rubric(10m)
•Session 11: When Not to Use Postgres — Documents, Blobs, Caches & Vectors(150m)
•Session 11: When Not to Use Postgres — Documents, Blobs, Caches & Vectors — Evaluation Rubric(10m)
•Session 12: Query Performance & the Access-Pattern Audit(150m)
•Session 12: Query Performance & the Access-Pattern Audit — Evaluation Rubric(10m)
•Module 4 Teaching Kit: Data — SQL & NoSQL(45m)

•Module 5: The LLM Layer(15m)
•Session 13: Calling a Model Like an Engineer — Prompts, Schemas & Structured Output(150m)
•Session 13: Calling a Model Like an Engineer — Prompts, Schemas & Structured Output — Evaluation Rubric(10m)
•Session 14: Tools, Agents & Bounded Autonomy Inside a Product(150m)
•Session 14: Tools, Agents & Bounded Autonomy Inside a Product — Evaluation Rubric(10m)
•Session 15: Cost, Latency & Model Choice — Routing, Caching & the Bill(150m)
•Session 15: Cost, Latency & Model Choice — Routing, Caching & the Bill — Evaluation Rubric(10m)
•Module 5 Teaching Kit: The LLM Layer(45m)

•Module 6: Retrieval — RAG & Vector Databases(15m)
•Session 16: Chunking, Embeddings & the Vector Store Decision(150m)
•Session 16: Chunking, Embeddings & the Vector Store Decision — Evaluation Rubric(10m)
•Session 17: Hybrid Retrieval, Reranking & Answers You Can Cite(150m)
•Session 17: Hybrid Retrieval, Reranking & Answers You Can Cite — Evaluation Rubric(10m)
•Session 18: When RAG Fails — Retrieval Evaluation, Freshness & Confident Wrongness(150m)
•Session 18: When RAG Fails — Retrieval Evaluation, Freshness & Confident Wrongness — Evaluation Rubric(10m)
•Module 6 Teaching Kit: Retrieval — RAG & Vector Databases(45m)

•Module 7: AI Dashboards & the Feedback Loop(15m)
•Session 19: Instrumenting an AI Feature — Traces, Spans & What to Log(150m)
•Session 19: Instrumenting an AI Feature — Traces, Spans & What to Log — Evaluation Rubric(10m)
•Session 20: The Quality Dashboard — Metrics That Change a Decision(150m)
•Session 20: The Quality Dashboard — Metrics That Change a Decision — Evaluation Rubric(10m)
•Session 21: Human Feedback, Labelling & the Loop That Improves the Product(150m)
•Session 21: Human Feedback, Labelling & the Loop That Improves the Product — Evaluation Rubric(10m)
•Module 7 Teaching Kit: AI Dashboards & the Feedback Loop(45m)

•Module 8: Ship It — Containers, Cloud & Operations(15m)
•Session 22: Docker & the Reproducible Environment(150m)
•Session 22: Docker & the Reproducible Environment — Evaluation Rubric(10m)
•Session 23: Kubernetes & Cloud (AWS/Azure) — What You Need and What You Don't(150m)
•Session 23: Kubernetes & Cloud (AWS/Azure) — What You Need and What You Don't — Evaluation Rubric(10m)
•Session 24: Security, Cost & Go-Live + Capstone Product Review(150m)
•Session 24: Security, Cost & Go-Live + Capstone Product Review — Evaluation Rubric(10m)
•Module 8 Teaching Kit: Ship It — Containers, Cloud & Operations(45m)