DoorDash's AI-assisted engineering interview

DoorDash told candidates what its new engineering interview looks like. I read the post line by line. Below is what it says, and what it leaves out.

What DoorDash says

In March 2026, DoorDash published Why DoorDash is rebuilding its engineering interviews around AI. It says it is replacing traditional coding rounds with a 60-minute, AI-assisted working session.

You join a realistic project, get oriented, and start contributing. Sample tasks include implementing and extending an order dispatch system and building a smart menu composer.

You work on your own machine, in your own editor. You use AI tools the way you would at work: chat, inline suggestions, planning, agent modes and running commands. DoorDash says free-tier tools such as Cursor, Claude Code and Codex are enough.

You share your screen and narrate. In DoorDash's words, you describe what you are doing, what you plan to try next, and why.

The five signals

DoorDash names five things it looks for:

• How you get oriented.
• How you use AI and verify what it gives you.
• How you debug.
• How you manage scope.
• How you communicate tradeoffs.

It also says finishing every task matters less than a tight loop and good judgment. Speed still counts, it adds.

Two more details. In an early pilot, many candidates needed 15 to 20 minutes just to explore and understand the code. And DoorDash now sends candidates a detailed guide ahead of time.

What the post does not say

The post does not name the job levels or teams that use this round. It does not say where the round sits in the loop. I won't guess at either.

If your recruiter gives you those details, trust the recruiter over me and over any blog. For the wider process, StrongYes keeps a DoorDash company page.

Before the session

Three details in the post change how I would prepare.

You work on your own machine. So I would check the setup the day before: editor, terminal, and the AI tool, all running and signed in.

DoorDash says free-tier tools are enough. So I would pick one assistant and learn it well. A new tool on the day is a new variable.

You ramp up on a realistic project. The pilot note says exploring the code took many candidates 15 to 20 minutes. So I would spend practice time reading unfamiliar code, not only writing fresh code.

How I would prepare for each signal

These are my habits, not DoorDash's instructions.

• Oriented. The pilot note tells me where the time goes. Before any prompt, I read the project and say what each piece does. On an unfamiliar repo, I write three sentences on how it fits together.
• Using AI and verifying. I predict what the assistant's change will do, then run it. I read the diff before I accept it. My notes on AI-assisted rounds go deeper.
• Debugging. I reproduce the bug first. Then I say my guess out loud and test it. I change one thing at a time.
• Scope. I pick the smallest slice that works from end to end. I say what I am leaving out.
• Tradeoffs. I name two options and say why I chose one. "Faster to build" is a reason. "Easier to change later" is another.

What narrating sounds like

Here is the narration I mean. The project is made up, and it is not DoorDash's code.

I see three folders: orders, dispatch and menus. Dispatch calls orders, so I'll read orders first. I'll check the tests before the main function. My plan is to add one rule, run the tests, then handle the empty case.

Say that out loud and the listener knows where I am, what I will try next, and why. The post asks for exactly those three things.

Practice the narration

Narrating is the part you can drill alone. The other signals need a project to work in. This one needs only a voice and a screen.

StrongYes does not recreate DoorDash's session. It trains the narrating. Coco is an AI study partner, not a person. She listens while you explain your code and asks one question at a time. She never hands you the fix.

The editor and the code runner are free. Open the editor and explain a problem you already solved, from the first line to the last.

These are not DoorDash questions. They are small systems to extend and explain: LRU Cache, Design Twitter and Task Scheduler.