Learn · AI Engineering
The job, not the prompts.
An opinionated track on what AI engineering actually is in 2026. Six modules, each paired with a challenge set on the platform.
Modules
Six modules.
01
The decision-shaped job
What changes when an AI pair joins every commit. A taxonomy of the new decision points and where judgment moves.
02
Tool design for tool-using agents
Naming, contracts, idempotency, error surfaces. How to make tools the model actually composes correctly.
03
Retrieval boundaries
What goes into context, what stays out, and how to draw the line. Failure modes when the boundary is wrong.
04
Evaluation that survives a quarter
Building evals that don't rot. Golden sets, drift detection, and the trap of optimizing for the eval.
05
Production failure modes
Silent regressions, plausible-but-wrong outputs, prompt-injection-as-RCE. What pages on-call at 2 a.m.
06
Replay-driven code review
How to review an AI-authored PR. What questions to ask the author. What to send back.