01. Week 15 — Capstone Project¶
What this module must prove¶
By Sunday, your project should demonstrate: - Clear product scope and target user. - A written system design with contracts between components. - One working end-to-end path. - A first-pass eval suite that catches system failures. - Latency and cost visibility. - A believable deployment path. - A portfolio story worth showing recruiters and hiring managers.
Capstone scope guardrails¶
Good scope¶
- One use case.
- One primary user persona.
- One measurable success definition.
- Four to six meaningful components.
- Two weeks of believable effort.
Bad scope¶
- Full platform ambitions.
- Three unrelated features.
- Multi-agent for prestige only.
- No eval plan.
- No path to demo.
Deliverables before Module 16¶
- [ ] Problem statement and target user locked.
- [ ] Architecture diagram drawn.
- [ ] API / component contracts written.
- [ ] MVP demo works on one happy path.
- [ ] First system eval suite exists.
- [ ] Latency and cost budget exists.
- [ ] README skeleton exists.
- [ ] Module review completed.
🧠 Mental models¶
- System design: "draw the blueprint before pouring concrete"
- One end-to-end path: "prove one train line runs before adding more stations"
- Eval suite: "building inspection, not demo applause"
- Deployment path: "plan move-in day, not just construction photos"
- Scope control: "one sharp spear, not a bag of gadgets"
- Observability: "dashboard gauges that tell you the engine is failing before smoke appears"
⚠️ Common traps¶
- Trying to impress with too many personas or features instead of one defensible user workflow.
- Building components in isolation and discovering too late that the full request path is slow or brittle.
- Shipping a demo without an eval suite that catches retrieval misses, tool failures, or hallucinated outputs.
- Ignoring latency and cost until the last week, when architecture changes become expensive.
- Adding agent loops or multi-agent coordination for prestige instead of clear product need.
- Presenting diagrams without a believable deployment, rollback, and operations story.
🔗 Prerequisites & connections¶
Builds on: Modules 00-14 across models, prompting, RAG, agents, evals, reasoning, multimodal systems, and diffusion.
Feeds into: Module 16 engineering principles, where your capstone trade-offs become explicit lessons about reversibility, quality gates, and technical leadership.
💬 Interview phrasing¶
- What is the smallest version of your capstone that still proves user value?
- Where can the system fail end to end even if each individual component looks healthy?
- Why did you choose this architecture instead of a simpler pipeline or a more agentic one?
- What metrics told you the project was ready to demo or deploy?
- If you had to cut half the scope tomorrow, what would remain and why?
⏱️ Difficulty markers¶
- 🟢 MVP scoping
- 🟡 component contracts
- 🟡 end-to-end integration
- 🟡 first-pass eval suite
- 🔴 deployment and rollback design
- 🔴 balancing quality, latency, and cost across the full system
Health check questions¶
- If traffic doubled tomorrow, what breaks first?
- If the model got slower tomorrow, how would users feel it?
- If retrieval fails, what does the system do instead?
- If an interviewer asks "why this architecture," can you defend it clearly?
- If Module 16 forced you to cut half the scope, what would remain?
Bridge to Module 16¶
Next module — 20_engineering_leadership_judgment — formalizes the engineering judgment you developed here into principles: how to make technical decisions, manage complexity, and lead AI teams.