Creating an AI Interview Agent

An interview agent is a mock-interview persona you configure once: the role, its difficulty, the job context, and who can practise with it. Learners then take realistic interviews and get scored feedback. Create one from Veda AI → AI Interviewer → Create New Agent.

The form is one page with four sections. Save with Save Changes (or Cancel to discard).

1. Basic setup

Interview Agent Name (required): up to 50 characters, for example "Senior Software Developer mock interview".
Duration: 15, 30, 45, or 60 minutes (default 30).
Agent Description (required): a short brief about the role.
Max attempts allowed (required): how many times a learner can take this interview (1 to 10, default 3).
Difficulty (default Beginner):
- Beginner: fresher-level questions on fundamentals.
- Intermediate: applied questions for 1 to 3 years of exposure.
- Hard: challenging questions on problem-solving and trade-offs.
- Expert: senior-level questions on system design, edge cases, and mastery.

2. Role Details

Job Description (required): the job context, written in a rich-text editor (up to 5000 characters). This keeps interviews on-topic and grounded in your material.

3. Custom Instructions

Custom Instructions (optional): tell the interviewer how to behave, respond, and evaluate.
Fixed Question Mode: turn this on to supply the exact questions to ask.

With Fixed Question Mode on, the AI asks only your listed questions and will not improvise or generate its own. Leave it off for adaptive interviews that follow up on answers. At least one question is required when it is on.

4. Audience

Choose who can use this agent:

All Learners
Course Selection: pick courses (required) and optionally batches.
Segment Selection: pick saved segments.

A live Total Learners Selected count shows your reach as you choose.

Save

Click Save Changes. If something required is missing you will be prompted to complete all mandatory fields, and you are returned to the agent list on success.

Create one agent per role and seniority (for example, "Frontend Developer, Intermediate"), so learners practise at the right level, and use the description to set expectations.