Applied AI / Forward Deployed Engineer · The Role: Applied AI & Forward Deployed Engineer · Lesson 5 of 5
How to actually win the loop (+ the capstone)
Across every company, the same handful of behaviors separate offers from rejections. Internalize these — they're the meta-strategy this whole course is built to deliver.
- Lead with evals. The single most-tested signal is: "How do you know your AI system is actually working?" Never answer "I tested it manually." Talk golden sets, LLM-as-judge (validated against humans), and regression gates. Module 6 makes this automatic.
- Start with the customer, not the tech. In any open-ended scenario, clarify before you architect. The #1 failure mode is jumping straight to a vector DB. Ask about users, data, constraints, and success first.
- Know the decision tree cold: Prompt → RAG → Fine-tune → Distill. "Fine-tuning is for form, not facts." This exact question appears at OpenAI, Anthropic, and Mistral.
- Speak in production primitives: token cost, latency budgets, prompt/prefix caching, model routing, guardrails, observability — not just "call the model."
- Own it. Say "I will," bring a 30/60/90-day mindset, and have a "deployment that failed" story ready.
The capstone that proves everythingThe best single prep artifact (recommended across every source): build one end-to-end project — a RAG or agent app on real data, with chunking, embeddings, hybrid search + rerank, an eval harness (golden set + LLM-as-judge), guardrails, tracing, and a short video walkthrough. It's evidence for nearly every interview module at once. Plus prepare 4–6 STAR stories.
How to use this trainerWork the modules in order, answer every retrieval check, and let the flashcards resurface concepts on schedule. When your readiness meter hits ~100% and you can pass the mock interview cold, you're loop-ready. Then go build the capstone.
◆ Lock it in
- The two universal winners: lead with evals and start with the customer, not the tech.
- Memorize the Prompt → RAG → Fine-tune → Distill tree and speak in production primitives.
- Build one end-to-end evaluated capstone + 4–6 STAR stories — it covers almost every round.
Feynman drill — say it out loudRecite the two universal interview winners and the four-step adaptation decision tree from memory.
Step 1 rate your confidence · Step 2 pick your answer
An interviewer asks an open-ended 'design an AI feature for our customer' question. Your very first move should be:
Step 1 — how sure are you?