2025 Women in AI Expert Series: Prompt Like a PrO

WAI CONTENT TEAM
1 day ago
3 min read

Principal author: Karen Jensen

Welcome to the 2025 Expert Series from the Global Ethics and Culture office of Women in AI.

In 2025, we continue our global initiatives in Education, Entrepreneurship, Innovation, and Research to make AI accessible and inclusive for everyone, with a special focus on women and girls.

Like the 2024 Speaker Series, this year's Expert Series aims to boost opportunities for women and girls in AI. We'll feature global women experts sharing practical AI skills that could help you launch a new AI career or reskill for AI roles.

In our first session, titled "Prompt Like a Pro: AI Skills for Students and Young Professionals," our expert offers practical guidance on the essential skill of prompt engineering.

Our expert for today is Charlotte Tao. Charlotte is the Chief Data Scientist at Gruve AI and is currently serving as a volunteer at the Global Ethics and Culture office as our AI Community Specialist.

The presentation began by tackling common misconceptions about prompt engineering. While there are many definitions of what prompt engineering is, our definition emphasizes the human in the loop value where a series of thoughtful and well-designed inputs (prompts), entered into an AI model, produces a well-supported and accurate output, aligned with human-centric values. Charlotte also introduced the concept that prompts should not be understood as scenarios with a one-time perfect question and answer, but an iterative process where a series of value-added and/or challenge questions can provide more enhanced output results.

The session was structured around three key scenarios demonstrating how targeted prompting can enhance AI interactions:

The Learner – Prompting for Research: Addressing the challenge of getting AI to provide structured, in-depth responses to research queries. The proposed solution was Single/Few-Shot Prompting, providing the AI model with examples of the desired output format (e.g., a specific summary structure including title, findings, arguments, limitations) to guide its generation and ensure all key points are covered. This technique is ideal for summarizing research papers, improving writing style, or generating high-quality research questions.
The Job Seeker – Prompting for Mock Interviews: This section identifies and provides solutions to the challenge for AI models in handling multi-role conversational scenarios like mock interviews effectively. The recommended technique is Role-Play Prompting, instructing the AI to act as a specific persona (like a hiring manager) and giving it clear instructions on how to evaluate responses, ask follow-up questions (like using the STAR method or asking for metrics), and refine the interaction to simulate a realistic scenario. This is particularly useful for practicing interviews, salary negotiations, or any scenario requiring realistic conversational simulation and targeted feedback.
The Professional – Prompting for Product Analysis: Discussing the challenge of getting AI to perform complex analyses without making false assumptions or providing generic answers. The solution presented was Chain-of-Thought (CoT) Prompting, which involves breaking down the task into sequential steps for the AI to follow (e.g., identify factors, compare strategies, provide recommendations). This approach guides the AI's reasoning process, leading to a more thorough evaluation and making it effective for complex decision-making, management issues, and strategic planning.