Module 07 / 08
Production AI
Turn a working demo into a system people can rely on.
The point
Production AI is mostly product engineering: reliability, cost, latency, observability, feedback, and iteration.
Start with
Read next
Understanding check
You should be able to…
- identify the failures users actually feel
- track cost, latency, quality, and feedback
- design fallbacks for model and retrieval failures
- know what must be monitored after launch
Practice with an agent
Make your product observable
intermediate · the evolving course product, hosting logs, analytics
Make
a deployed product slice with error logs, a usage ceiling, feedback capture, and one recovery path
You know it works when
another person can trigger the feature, you can explain one failure from evidence, and the system fails safely at its limit
Go deeper by building
Ship a small AI product slice
advanced · next.js, model API, database, auth provider, logging
Make
a deployed AI feature with auth, usage limits, feedback capture, and basic observability
You know it works when
include a demo link, failure-mode notes, and one iteration driven by feedback or evals