Prove you can learn.
That is the whole interview.
We do not start with resumes. We do not care about your degree, your job title, or how many years you have been doing this. We care about one thing: can you learn a new system quickly with AI as your partner? The tests below take about an hour. And worst case scenario, you walk away with hands-on experience in VS Code, GitHub, and vibe coding that you can put on your resume. You have nothing to lose.
Why We Do It This Way
The gatekeepers had their turn.
Traditional hiring filters for credentials. We filter for capability. The three tests below are your interview. They should take about an hour and they are designed so that anyone with the right mindset can pass, regardless of background.
What does not matter
Your degree. Your previous job title. Whether you have 10 years of experience or 10 weeks. Whether you went to Stanford or never went to college. Whether you can pass a whiteboard interview.
What matters
How quickly you learn new systems. How comfortable you are using AI as a building partner. How clearly you communicate. Whether you can get from zero to something working without someone walking you through it.
Screencast Format
Show us VS Code and GitHub. Side by side.
Your screencast should be split screen. VS Code on one half, GitHub on the other. We want to see how your local work connects to the remote artifacts. This is how we demo our product and it is how you will demo it too.
your-screencast.mp4
■ VS Code
- AI scaffolding the project
- Terminal running commands
- AI creating issues via CLI
- You prompting, iterating
● GitHub
- Repo created with code
- Commits showing up
- Issues appearing live
- The proof of your work
Why split screen? Because we need to see the connection between what you build locally and what shows up on GitHub. The left side is the work. The right side is the proof. That linkage is exactly how we operate at Mault.
Screencast Format
Show us VS Code and GitHub. Side by side.
Your screencast should be split screen. VS Code on one half, GitHub on the other. We want to see how your local work connects to the remote artifacts. This is how we demo our product and it is how you will demo it too.
Test 1 of 3
The Cold Start
Download VS Code if you do not already have it. Using any AI assistant (Claude, Copilot, Cursor, ChatGPT, whatever you prefer), scaffold a small project from scratch. It can be anything: a to-do app, a simple API, a CLI tool, a personal website. You pick the stack. You pick the project.
Record your screencast (split screen, VS Code + GitHub) showing you and the AI building it together. We want to see how you prompt, how you react to the output, and whether you can get from zero to something working.
Bonus: Enable thinking / extended thinking
Test 2 of 3
Builds on Test 1
Source Control Setup
Now that you have scaffolded the project, work with your AI to set up a GitHub repository and authenticate the GitHub CLI from inside VS Code. Push your project to the repo.
This should be visible in your screencast. The left side shows you pushing from VS Code. The right side shows the repo appearing on GitHub with your code.
Test 3 of 3
Builds on Test 2
Feature Planning
Using AI, create 3-5 GitHub issues for features that would enhance your application. Create the issues from inside VS Code using the GitHub CLI or an extension.
Make the issues specific. “Add dark mode with system preference detection” is good. “Add features” is not. We should see the issues appear on the GitHub side of your split screen as you create them.
Extra Credit
The Video Intro
Record a short video, under 2 minutes. Introduce yourself, tell us where you live, your favorite hobby, and mention at least one thing you have built using AI. This does not need to be a coded project. Low-code, no-code, an automation, a workflow, anything tangible counts.
Do not practice more than 3 times. Keep it natural. We are not looking for a polished production. We are looking for a real person.
What to Send
Two links. One email. That is it.
Google Drive Folder
Create a folder with your screencast(s) covering Tests 1-3 (one video or three separate ones) and your video intro if you did the extra credit. Set sharing to “anyone with the link.” Name your files clearly so we know what we are looking at:
Folder: FirstName-LastName-Mault-SA
Screencast: FirstName-LastName-Technical.mp4
Video intro: FirstName-LastName-Intro.mp4
GitHub Repo Link
The public repo with your project code and 3-5 issues. We will check that the code is pushed and the issues are real.
Folder: FirstName-LastName-Mault-SA
Screencast: FirstName-LastName-Technical.mp4
Video intro: FirstName-LastName-Intro.mp4
What we are NOT judging
We are not judging the quality of the code, the complexity of the project, or what language you chose. We do not care if it is a 10-line script or a full-stack app. We care about whether you are comfortable using AI as a building partner and whether you can get from zero to something working without someone walking you through it. If you have never used VS Code, GitHub, or the terminal before, that is completely fine. Use AI to help you learn. That is literally the test.
Ready?
Email both links (Google Drive folder + GitHub repo) to the address below. No Google Drive link, no interview. No GitHub repo link, no interview.
Your email must include your full name, location, and contact information. Two links and nothing else.