Phase 10: Career, Portfolio & Interview Engineering · 45 min · Claude Code · Python

Interview Engineering: Live AI-Native Coding

Anyone can prompt an AI assistant and accept the first output. The interview signal is in what happens before the prompt (stating the spec) and after the output (reviewing it before running it) — not in the prompt itself.

Hiring signal: Demonstrating spec-first prompting and reviewing generated code before running it, live, is the concrete behavior that separates 'engineers with AI' from 'prompts an AI and hopes' — exactly the distinction this course opened with in c12-00.

What you will learn

Explain what a 'vibecoding assessment' evaluates in 2026 hiring and why it's distinct from a traditional algorithmic coding screen
Demonstrate spec-first prompting live: stating acceptance criteria before prompting an AI assistant, not after
Review AI-generated code against the stated spec before running it, rather than accepting the first output
Show (not just claim) engineering judgment by catching and explaining a real issue in AI-generated code during a live session

Introduction

Interview Engineering: Live AI-Native Coding

A live coding interview allows an AI assistant. The first candidate reads the prompt, immediately types "build a rate limiter for this API" into the assistant, gets working-looking code back, runs it, and moves on. When the interviewer asks "what happens if two requests arrive in the same millisecond," the candidate doesn't know — they never looked closely enough at the generated code to have an opinion. The second candidate, given the same prompt, first states out loud what "correct" means here (fixed window or sliding window, what happens at the boundary, what the concurrency model is), then prompts the assistant with those constraints stated explicitly, then reads the returned code line by line before running anything, and catches that the assistant's implementation has exactly the boundary bug the interviewer was about to ask about — before being asked. Same tool available to both candidates. Completely different signal produced.

What a live AI-native coding round actually evaluates

This kind of round has become a distinct, named hiring signal in 2026 — often called a vibecoding assessment — specifically because a traditional algorithmic screen (with no AI assistant) misses exactly the skill this course teaches. The evaluation isn't "can this person type a prompt," it's whether they guide the assistant effectively, critically review its output, iterate intelligently when something's wrong, and maintain scope and code quality throughout — the same spec-first, validation-driven discipline from c12-01 and c12-03, just performed live under observation instead of alone at a desk.

The assistant is available to everyone in the room; the discipline is not
Every candidate in a live AI-native round has access to the same tool. The interview isn't measuring who can operate the assistant — everyone can. It's measuring who has the habit of stating a spec before prompting, and the habit of reviewing before running, baked in deeply enough that it shows up automatically under interview pressure rather than only when there's time to think.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Showing spec-first prompting, not just claiming it, Reviewing before running, and catching what the assistant misses, Two failure modes to avoid, not just one, Build It — plus a hands-on lab, quiz, and project artifact.

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