Title: Course Review & Reflection
Course: AIINFRA 200: Production Inference Serving & GPU Orchestration > Section: Week 16 — Capstone Project & Course Review

💬 Course Review & Reflection (20 pts)

You've spent 16 weeks going from "why does inference need its own infrastructure?" to designing a full GPU-orchestrated serving system. Let's close the loop. Your initial post should answer:

- What is the single biggest shift in how you think about running AI models in production, compared to how you thought about it before this course?
- Which week or topic changed your thinking the most, and why — be specific (a tool, a tradeoff, a failure mode, a mental model).
- Looking at your capstone, what's the one skill from Weeks 1–15 you leaned on most heavily?

Then respond to two peers. For each reply, engage with something concrete they said — ask a follow-up question, share how your own experience compared, or point them to something relevant from your capstone. Graded with the Discussion Rubric (20 pts).

🎉 This is the last graded item in the course. Thank you for putting in the work — production inference serving is a genuinely hard, genuinely valuable skill, and you've built real proof that you can do it.