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Recorded Walkthrough of a Past AI Project and Your Own Role in It

CrestaSoftware Engineer · Online Assessment
MediumSoftware EngineerOnline AssessmentBehavioral & Leadership

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A recorded behavioral item from a timed online assessment for a forward-deployed AI engineering role: walk through an AI project you built and explain exactly which parts you owned. It tests concise technical storytelling, clear ownership, evaluation and outcomes without a live interviewer to prompt you.

Record a short video in which you walk through an AI project you worked on in the past: what the project is and does, and which parts of it you were personally responsible for.

This is the first item of a timed online assessment for a forward-deployed engineering role focused on AI agents, and 10 minutes are allotted to it. It works as a brief project and behavioral screen, not a coding task.

Constraints and Clarifications

  • The item is recorded, not live: nobody can interrupt to ask what you meant, so the recording itself has to answer the questions a live interviewer would ask.
  • The 10 minutes are the time allotted to the whole item. How much of it is preparation, and whether the video has a minimum or maximum length, is not stated; check the on-screen instructions before you start.

Clarifying Questions

Because there is no interviewer, settle these from the instructions, or decide them yourself, before recording:

  • Do the 10 minutes include preparation time, and is there a length limit for the video itself?
  • Can you share your screen to show a diagram, a demo or code, or is it a camera-only recording?
  • Must the project come from professional work, or does a side project or academic project qualify?
  • Is there a single take, or can you re-record?

Hints

Hint 1

Pick the project for the role: Choose the project where you can speak in the most detail about decisions you made yourself, and where you can say who used it and what changed for them.

Hint 2

Make your part unmistakable: A reviewer watching the video cannot ask follow-up questions. Plan the exact sentences that separate what you built and decided from what teammates, libraries or hosted models provided.

Follow-up questions

  • What was the hardest technical decision in the project, and which alternative did you reject?
  • How did you know the model's output was good enough, and what did you do about the cases where it was wrong?
  • If a customer wanted this project running inside their own environment next month, what would you change first?
  • What would you do differently if you started the project again today?