Project walkthrough, a real LLM application end to end
What you’ll learn
Section titled “What you’ll learn”You built the components in lessons 1-4. This lesson reads a real LLM application end-to-end against them, so the parts have a worked-example shape and the decisions baked into them become visible. The source curriculum is the Full Stack Deep Learning LLM Bootcamp (Spring 2023), by Charles Frye, Sergey Karayev, and Josh Tobin, freely available at fullstackdeeplearning.com/llm-bootcamp with recorded lectures on the Full Stack Deep Learning YouTube channel.
The worked example is askFSDL, a Q&A app over the FSDL course materials. You will identify the production decisions it embeds (knowledge-source scoping, chunking for content’s natural unit with metadata, source-carrying retrieval, a scope-honest citation-asking system prompt, streaming generation with citations, and logging enough to debug); apply a read-this-design checklist to any LLM app’s pipeline; recognize what a worked example deliberately defers (sophisticated UX to lesson 6, production observability to lesson 7, agentic flow to lesson 10); and develop the “production-decision eye” that distinguishes builders who ship from builders who tinker. The reframing worth carrying: a real LLM app of this shape is a few hundred lines, the complexity is in the decisions, not the line count.
Where this fits
Section titled “Where this fits”This is lesson 5 of 11, the second lesson of Phase 2 (building production apps). It is the worked-example for the phase: it brings the lesson-1 five-component pipeline and the lesson-4 RAG-plus-tool patterns together against one real application, names what is in scope for this lesson, and points at where each deferred piece (UX, ops, agents) gets covered.
Before you start
Section titled “Before you start”Prerequisites: lesson 4 of this track (the RAG pipeline whose seven moving parts you will now see embedded in a real application). Familiarity with lessons 1-3 helps for the five-component framing and the prompt-engineering discipline. No code to run.
About the math
Section titled “About the math”None. This is a read-the-design lesson: identify and judge the production decisions in a real LLM application. The skill is recognition, not derivation.
By the end, you’ll be able to
Section titled “By the end, you’ll be able to”The single capability this lesson builds: read a real LLM application end-to-end and identify the production decisions it embeds. Concretely, you will be able to:
- Identify the production decisions embedded in a real LLM application
- Apply a read-this-design checklist to any LLM app’s pipeline
- Recognize what a worked example deliberately defers (UX, observability, agentic flow)
- State the “five hours, not five weeks” reframing and what it implies
- Develop the production-decision eye that distinguishes shipping from tinkering
Time and difficulty
Section titled “Time and difficulty”- Read time: about 11 minutes
- Practice time: about 10 minutes (catalog the decisions in a one-paragraph app sketch, plus flashcards)
- Difficulty: standard (no math; the work is reading a design with the production-decision eye)