🏴‍☠️ Master Job Interviews with NotebookLM

Simulate the Hiring Manager’s Brain

Author

Captain YAR
December 09, 2025 • Estimated Reading Time: 8 minutes

The days of walking into a job interview with only a few Google searches behind you are over.

Instead of cramming mission statements and guessing what a hiring manager might ask, an AI professional has outlined a workflow using Google’s NotebookLM that turns it into a rigorous, personalized interview simulator.

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The Mechanism of Automated Preparation

The key idea is shifting most of the research and roleplay work from you to the AI. Many candidates use Large Language Models (LLMs) for resumes and cover letters but rarely for realistic practice. By using NotebookLM’s ability to “ground” itself in specific documents, you can create a closed ecosystem of facts that apply only to the role and company you’re targeting.

Instead of relying on a general chatbot that may hallucinate or use outdated data, this approach forces the AI to reference specific, current materials—job descriptions, press releases, and industry news—before it generates questions. Interview prep becomes a structured, data-driven process rather than a vague to-do.

Automating the Intelligence Gathering

One of the hardest parts of preparation is building a deep understanding of the company. That usually means hours of tabs, reports, and articles. The LinkedIn creator highlights NotebookLM’s “Discover Sources” feature as a shortcut. By asking for sources tailored to a role and company, the tool becomes an autonomous research assistant.

NotebookLM can automatically collect company research, role details, and recent news. This gives the AI a rich context, so when it quizzes you, it asks about the company’s real strategic challenges and recent moves, not generic interview questions. The result is practice that closely reflects what a top-tier candidate should know.

The “Tough Coach” Simulation

The workflow also relies on customizing the AI’s persona. The expert recommends instructing NotebookLM to act as a “tough interview coach.” Friends may be too gentle, and standard AI often leans supportive instead of critical.

With a stricter persona, the AI reviews your spoken or written answers and highlights where you were vague, missed a key competency, or failed to demonstrate impact. It recreates some of the pressure of the real conversation and provides a feedback loop that sharpens your responses before the actual interview.

Personalizing the Knowledge Base

The last major element is integrating your own material. The guide suggests uploading your resume, portfolio, project documents, or LinkedIn profile alongside the company research.

Once NotebookLM has both the external data (what the company needs) and your internal data (what you offer), it can help you craft targeted answers. It may suggest specific projects from your history that align with pain points revealed in recent reports, turning the AI into a strategic partner that understands your background in context.

Nuances and Limitations

This method depends heavily on source quality. If the company has little public information, you may need to upload your own research. And while AI can simulate tough questioning, it cannot practice non-verbal communication, rapport, or presence. It is best used to refine content and confidence, not as a full replacement for human interaction skills.

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Your AI Training Plan

If you have an interview coming up, here is the condensed workflow from the original guide:

  1. Set up the Environment: Open NotebookLM and create a new notebook.

  2. The Research Prompt: Use “Discover Sources” with: “I need sources to prepare for my [JOB TITLE] interview at [COMPANY NAME].”

  3. Define the Persona: In settings, choose a custom style and instruct the AI to act as a “tough interview coach.”

  4. The Simulation: Ask it to generate role-specific questions and use the feedback on your answers to iterate.

  5. Integration: Upload your resume and portfolio so the AI can cross-reference your skills with the job requirements.

This approach takes the guesswork out of preparation!

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