AI-Assisted Interviews allow interviewers to observe how candidates interact with an AI assistant in real time. This provides deeper insights into the candidate’s coding behavior, technical thinking, and ability to work with AI tools.

The interview takes place in a modern integrated development environment (IDE) that includes AI features such as inline code completions, file-aware chat, and agent mode. These features closely resemble real-world developer tools such as GitHub Copilot and Cursor.

Interviewers can evaluate not just problem-solving skills, but also how effectively candidates leverage AI to build solutions. 

Key benefits

AI-Assisted Interviews offer signal-rich insights by enabling the following:

• Real-world simulation: Mirrors a modern IDE where AI support is part of the development workflow.

• Enhanced interviewer visibility: Displays how and when a candidate interacts with the AI assistant during the interview.

• Post-interview transparency: Provides a complete chat transcript for interviewers to review and use when making informed hiring decisions.

Enable AI Assistant for Interviews

To enable the AI Assistant in your interviews:

1. Log in to your HackerRank for Work account using your credentials.

2. Go to Settings.

3. Select Interview Settings from the left panel under the Company section.

4. Scroll to the AI Assistant in IDE section.

5. Select the checkbox to enable AI Assistant in the IDE.

   

6. Click Save.

Disable AI Assistant for a specific question

You can disable the AI Assistant for specific questions if you do not want candidates to use it.

To disable the AI Assistant for a specific question:

1. Import the supported question type during the interview.

2. Locate the AI Assistant toggle.

3. Turn off the toggle to prevent the candidate from using it.

   

Candidate experience

When you enable the AI Assistant for a supported question, candidates can interact with it in the following ways:

• Chat interface: Candidates can ask questions about the problem, code, or specific files. Candidates must tag the problem statement to provide context. The AI Assistant uses the tagged content to generate accurate responses.

  This helps you assess how well a candidate understands the task and how effectively they use the AI Assistant to plan their implementation. It also enables the AI Assistant to apply the same context throughout the interview.

• Inline code completions: As candidates type, the AI Assistant offers code suggestions directly in the editor. Candidates can choose to accept or ignore these suggestions.

• Agent mode: Candidates switch to a mode designed for longer, multi-turn conversations. In this mode, candidates can ask the AI Assistant to write code, edit files, and perform actions directly from prompts. This mode is useful for complex tasks and step-by-step guidance.
  The system displays a Pending tool call dialog while it prepares the requested action. Candidates can choose to Allow or Cancel the action.

  • When candidates select Allow, the AI Assistant proceeds and generates code suggestions. Candidates can then Accept or Reject the suggestions.

  • When candidates select Cancel, the system stops the action, and no changes occur.

• Model switching: Candidates toggle between available models based on their preference or the task requirements. Currently, the AI Assistant supports Claude-sonnet-4.6, Gemini-3 Flash, Gemini-3 Pro, and GPT-5.2. Candidates can also select Auto Mode, which automatically chooses the best model based on response speed.

  

Interviewer experience

During an interview, the interviewer can monitor the candidate’s interaction with the AI Assistant in real time.

• The chat panel remains fully visible to the interviewer, displaying both the candidate’s prompts and the assistant’s responses as they occur.

• Inline code completions accepted by the candidate appear directly in the shared code editor.

• The interviewer retains full control of the session and can ask questions, add comments, or navigate files as usual.

• In Observation mode, the interviewer can view all AI Assistant interactions in real time. Live assistant edits and shared diff views remain synchronized between the interviewer and the candidate.

  

This visibility helps interviewers understand what changes occur, why they occur, and how the candidate responds. It also enables interviewers to assess the type of assistance the candidate seeks, such as syntax help, conceptual guidance, or full implementation suggestions.

The interviewer can disable the AI Assistant for specific questions, if needed. They can ask the candidate to explain their AI interactions to better understand their problem-solving approach.

Post-interview report

After the interview, the candidate report includes a detailed Chat Transcript, which provides a complete record of the conversation between the candidate and the AI Assistant.

These insights offer transparency into the candidate’s support-seeking behavior, coding independence, and AI fluency—key factors in evaluating developer readiness.

Frequently Asked Questions (FAQ)