Lesson 6.2 – Training your Team on AI

🎯 Learning Objectives

By the end of this lesson, your team will be able to:

• Understand how prompting impacts AI output

• Learn the basics of effective prompt design

• Use structured language to improve Agent accuracy and usefulness

• Apply prompting in real-world daily workflows

• Build confidence and habits around AI interaction as a skill

📌 Why Prompting Matters More Than You Think

AI Agents are not all-knowing—they’re context-sensitive tools. What you ask shapes what you get.

Unlike traditional software that follows buttons and rules, AI follows language.

A slight change in phrasing can:

• Improve clarity

• Reduce hallucinations

• Surface more relevant data

• Encourage longer or more concise answers

✅ Teaching your team to speak AI is one of the most important steps in successful adoption.

🧠 The Science of Prompting

Every AI interaction starts with a prompt—a question, instruction, or command.

The better your prompt, the better the result.

Prompting affects:

• What sources the AI retrieves from

• How much detail it includes

• Whether it stays grounded in known information

• Whether it needs to call a function or workflow

✍️ Prompting Basics for Your Team

Here’s a simple framework for building better prompts:

💡 Prompting Tips to Teach Your Team

🧪 Prompting Is a Skill—Practice Makes Proficient

Just like writing good emails or giving good presentations, prompting gets better with:

• Repetition

• Review

• Feedback

Encourage your team to experiment, iterate, and review results. Over time, they’ll develop intuition for what works best.

🔁 Prompting + Feedback = Continuous Improvement

Good prompting doesn't just improve the answer—it improves the Agent over time.

Every time your team:

1. Prompts the AI

2. Rates the response as GOOD/BAD

3. Suggests a better version

→ The system learns. Your AI Agent evolves.

This turns your entire team into collaborators in training the Agent, not just users.

📘 Reinforced in [Lesson 5.2 – Human Feedback with raia Copilot]

🛠 Training Employees to Use AI in Their Workflow

Don’t just tell employees how to use AI—show them where to use it.

Common use cases:

• Drafting responses (support, email, follow-up)

• Searching policy or procedural knowledge

• Creating summaries or reports

• Asking for next steps based on specific roles

• Triggering automated tasks via functions or workflows

Encourage team members to:

• Use Copilot or embedded chat regularly

• Log prompts that worked well

• Share “favorite prompts” or time-saving examples

• Track what areas the Agent is helpful (or not yet helpful) in

🧪 Real-World Prompting = Real Training

Every time someone uses the AI Agent to:

• Solve a real problem

• Ask a recurring question

• Test a live task

→ They’re helping train it better.

This is how AI becomes embedded in operations—not just tested in isolation.

📝 Prompt Training Exercise

Have team members try the following:

1. Think of a task they do regularly (e.g., “Answering product questions”)

2. Write 3 prompts for the Agent to help with that task

3. Evaluate the responses

4. Refine and retry using what they learned

5. Submit one “most effective” prompt to the team wiki

👥 Prompting Training Do’s & Dont's (Summary Card)

✅ Key Takeaways

• Prompting is a critical skill that drives AI quality

• The more specific and structured the prompt, the better the answer

• Encourage real-world use to train the Agent and improve workflows

• Build prompt fluency across the team to maximize value

• AI is a collaborator—treat interactions as training, not transactions