In this lesson
- 01Learning Objectives
- 02The Problem
- 03The Concept
- 04Build it
- 05Use it
- 06Exercises
- 07Key Terms
- 08Further Reading
About 800 words of reading, with code, 7 quiz questions and the tutor.
The full lesson opens with an access code
You can see what this lesson covers and the milestone it sets. The full text, code, quizzes, the tutor and the AI reviews come with the K850 practice, along with weekly build sessions and code review.
Milestone forAn observable back-office agent
Operate it from the traces
Trace every run with spans for each state, tool call, retry, escalation and approval, with cost in ZMW. Build the view a finance manager needs: what was matched, what waits for approval, what failed and why.
Done when
- Spans for every state, tool call, retry, escalation and approval, with ZMW cost
- A manager’s view of matched, pending and failed items
- One incident diagnosed from traces alone and written up
Stretch: Export traces in OpenTelemetry GenAI format
Reviews open with an access code.
Interview practice
Questions on this topic that AI engineering interviews ask, with the companies reported to ask them. Answer the way you would out loud; Jev scores it and DeepSeek tells you what to add.
Scoring opens with an access code. You can still read the questions and prepare.
Adapted from open-source work: AI Engineering from Scratch by Rohit Ghumare (MIT, lesson text, code and quizzes); Awesome LLM Apps by Shubham Saboo (Apache-2.0, starter code); AI Engineering Interview Questions by Outcome School (Apache-2.0, interview questions). Capstones, milestones, data packs and Zambian context by Zambrite.