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Abigail Wattley prepared for her podcast interview by feeding an LLM past episodes and asking it to simulate a practice session. The AI correctly identified the host's conversational style and love for anecdotes, effectively acting as a presentation coach and demonstrating a practical use for the technology.
A profoundly underutilized feature of AI is its ability to teach. Instead of just delegating tasks, professionals should ask LLMs to train them in new skills, create practice assignments, and evaluate their performance, unlocking rapid personal development.
Instead of manually crafting a system prompt, feed an LLM multiple "golden conversation" examples. Then, ask the LLM to analyze these examples and generate a system prompt that would produce similar conversational flows. This reverses the typical prompt engineering process, letting the ideal output define the instructions.
Instead of simply commanding an AI, a team first instructed it to ask clarifying questions about their company's mission and selection criteria for podcast guests. This "interview" step forced the AI to understand deep context before generating outputs, leading to a much more effective and customized database of ideas.
To simulate interview coaching, feed your written answers to case study questions into an LLM. Prompt it to score you on a specific rubric (structured thinking, user focus, etc.), identify exact weak phrases, explain why, and suggest a better approach for structured, actionable feedback.
Notebook LM is a powerful tool for interview preparation. A Google AI PM uploaded a four-hour investor video and the target job description, then asked the AI what she needed to know. It distilled the content into 15 key points, enabling her to master the material and excel in the interview the next day.
Beyond transcription, advanced AI tools can analyze an interviewer's live performance. They offer feedback on tonality, vocabulary, use of open vs. closed questions, and even body language, turning the AI into a powerful tool for improving human soft skills and communication.
Go beyond using AI for simple research. Feed it public data about a specific executive (from blogs, interviews, etc.) and instruct it to act as that person. This allows you to practice conversations, refine arguments, and master their specific communication style before a critical meeting.
GitHub COO Kyle Daigle feeds his daily communications (emails, interviews) into a private AI model to receive critical feedback on his clarity and style. He finds it powerful because humans are more receptive to direct criticism from a bot than from another person.
Rehearse difficult conversations by having an AI adopt the persona of your boss, partner, or employee. This allows you to practice your approach, refine your messaging, and anticipate reactions in a safe environment, increasing your confidence and effectiveness for the real discussion.
A powerful personal AI use case is creating interview prep materials. By feeding a tool like Google's NotebookLM with the job description, company info, and market context, you can generate a personalized audio summary that coaches an applicant, boosting their preparedness and confidence.