AI Engineering

You will learn to ask what breaks if a role stays empty, sort the answer into a fire, gap or bet, and re-aim your interview stories and follow-up note to match it.

You will learn what an eval actually is, why large generated test suites miss the failures real users hit, and how to turn each incident into a small regression case with the cheapest check that catches it.

One team took 40 minutes to fix a 2am incident, the team next door took 10 seconds for the same severity — and the gap wasn't skill, it was a boolean someone remembered to build in advance.

It's not your prompt, your retriever, or your reranker — it's the embeddings you set once and never looked at again, and here's the diagnostic that catches it before it becomes an incident.

A 10-minute audit of your actual query pattern — recall, corpus size, filters, writes — will tell you whether you need Pinecone or just Postgres, and for most RAG features the honest answer isn't the one every stack diagram assumes.