An AI assistant for coding interviews that reads the problem, not your IDE.
Interview Assistant AI watches the editor, terminal, or whiteboard you're sharing and listens to the interviewer's question, then streams a written answer — with real, syntax-highlighted code — into a separate overlay window.
What an AI coding interview assistant actually helps with
Coding interviews mix a stated problem, constraints given out loud, and code you're expected to write live. An AI coding interview assistant's job is to keep up with all three: read what's currently on screen, factor in what was just said, and produce a structured answer — approach, complexity, and code — fast enough to be useful mid-interview.
Interview Assistant AI does this generally rather than through a coding-specific mode: the same screen-plus-audio pipeline that handles a behavioral question handles a coding one. What changes is what's on screen and what you ask.
How it handles a coding question
- 01
Share the editor or problem tab
Pick the window with the problem statement, your code, or both. A live preview confirms exactly what the model will see before you arm it.
- 02
Let it hear the constraints
With meeting audio on, a constraint the interviewer adds out loud — can you do this in O(n)? — reaches the assistant the same moment it reaches you.
- 03
Get a structured answer
Responses render as real Markdown: an approach, the complexity, and a fenced, syntax-highlighted code block with a copy button — not a wall of escaped text.
- 04
Keep asking as it evolves
The rolling context keeps the last few exchanges, so a follow-up about a changed constraint builds on the previous answer instead of starting over.
What it doesn't do
It doesn't run or test your code. There's no execution sandbox — the answer is the model's reasoning about the problem and your code as text, the same as if you asked a knowledgeable person to look at your screen.
It doesn't autocomplete inside your editor. The answer streams into its own overlay window, not as inline suggestions in VS Code, IntelliJ, or whatever you're coding in.
It doesn't know a target company's exact question bank. It reasons about whatever appears on the shared screen or gets said out loud, generally, using the AI provider and model you've connected.
Languages and problem types
Because analysis works from a screenshot of whatever's shared plus the transcribed conversation, it isn't limited to a fixed language list — Python, Java, Go, SQL, or a system-design whiteboard all arrive the same way, as an image and a question. Response quality depends on the vision/text model you connect (OpenAI or Anthropic) and the model you pick within it.
Go deeper on a specific round
- Technical interview assistant
The full loop, not just the coding round.
- System design interview assistant
Requirements, trade-offs, and a worked example.
- AI interview assistant
The full product overview.
- How to prepare for a technical interview
A study plan, not just a tool.
Questions about the coding interview assistant
Does it write code for me automatically?
It answers the question you ask or the problem it reads on screen with a written response, including code where relevant — you still read, adapt, and type it yourself; nothing is injected into your editor.
Does it work for whiteboard-style system design questions too?
Yes — it reads whatever's on the shared screen, including a diagramming tool or a physical whiteboard on camera, the same way it reads an editor. See the dedicated system design interview assistant page for that workflow.
Which languages does it support?
There's no fixed language list. It reasons over a screenshot and the conversation transcript, so any language or notation that can appear on screen — Python, Java, Go, SQL, pseudocode — is handled the same way.
Can it see my whole codebase, or just what's on screen?
Only what's on the screen or window you selected for capture, plus whatever's been said in the current call and the last few exchanges in the rolling context. It has no separate access to your filesystem or repository.
Run it against a mock coding interview first.
Download for Windows, connect your own OpenAI or Anthropic key, and try it on a practice problem before it matters.