August 5, 2025

In 5 Steps: Upskill Your Team in AI with ChatGPT Study Mode

If you’re looking for a lightweight, self-led way to get your team thinking more clearly about how they use AI, this is a great place to start.
Evelyn Le
By
Evelyn Le
Strategic Product Lead, Stay Ahead, FlexOS

Presented by

Study Mode in ChatGPT helps people build real understanding of core concepts.

Prompting is a useful entry point: it’s hands-on, immediately applicable, and sets the foundation for more advanced topics like automation, retrieval, or model evaluation.

Try this as a team learning activity: each person explores prompting using Study Mode, then shares a takeaway or quick demo in your next sync. It’s a simple way to turn everyday AI use into shared learning.

Step 1: Open the “Study and Learn” tool in ChatGPT

From the dropdown under Tools (⚙️) or enter /, select “Study and Learn.” This mode turns ChatGPT into an interactive tutor that would give you instructions, instead of jumping straight to answers.

Step 2: Ask it to teach you prompt engineering

Type:

“Help me understand prompt engineering and how to write a good prompt for work tasks.”

ChatGPT will ask questions to tailor the lesson, like what you want to use prompting for (emails, reports, strategy, etc.).

Step 3: Follow the interactive flow

Study Mode will:

  • Break down the concept clearly
  • Ask you questions to check understanding
  • Invite you to practice by writing prompts
  • Give you feedback and build upon your answers
  • Quiz you at the end (yes, a real quiz)

This keeps you engaged and helps the learning stick.

Step 4: Expand the lesson

Once you’ve grasped the basics, try asking:

“How would prompting differ if I want to summarize a report vs. write a cold email?”

“What are examples of good vs. bad prompts for brainstorming ideas?”

This turns the lesson from generic theory into something practical for your day-to-day.

Step 5: Explore more topics with Study Mode

Prompting is just the beginning. You can use Study Mode to learn:

  • What “retrieval-augmented generation” actually means (without the jargon)
  • How to give feedback to AI models
  • The difference between fine-tuning and custom instructions
    How to evaluate AI outputs critically in your workflows

Let each team member choose one and share their insights, it’s a simple way to grow collective intelligence, without formal training overhead!

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