Overview

Lecture URL: https://skill.re/learn/manager/preparing-performance-conversations.php

AI FOR MANAGERS CERTIFICATION

Independent AI Application (Level 3) | Performance and Coaching Support

LECTURE: Preparing Performance Conversations

Lesson 4.1 | Estimated Duration: ~13 minutes

Welcome to the AI for Managers certification program. I am your instructor, and today we are covering one of the essential lessons in the Performance and Coaching Support module: Preparing Performance Conversations.

This is Lesson 4.1 in Level 3, the Independent AI Application track. Whether you are joining us as a new manager finding your footing, a seasoned director refining your approach, or a VP setting strategic direction for your organization, the material in this session is designed to meet you where you are and give you something immediately actionable.

In our previous lesson, we covered Workshop and Brainstorming Facilitation. Today we build directly on that foundation. If any of those concepts feel uncertain, I would encourage you to revisit that material before we go further.

Before we begin, let me set expectations. This is not a passive lecture. I will ask you to think, to challenge assumptions, and to connect what we discuss to your own work. The managers who get the most out of this program are those who pause, reflect, and apply. So I encourage you to have a notepad ready, whether physical or digital, and to jot down ideas as they come to you.

Let us get started.

Lesson 4.1: Preparing Performance Conversations

Title & Purpose

Preparing Performance Conversations teaches you to use AI to organize performance data, draft talking

points, and prepare for reviews--while centering manager judgment on fairness, accuracy, and human sensitivity.

AI helps you synthesize performance evidence, organize thoughts clearly, and structure conversations. You

exercise judgment about what's fair to say, how sensitive observations truly are, and what growth is

possible. By the end, you'll prepare thoroughly while staying grounded in reality and respect for the person.

Why This Matters for Managers

Performance conversations are where management becomes real. They can be:

• Developmental: "Here's how you grow"
  - Constructive: "This needs to change"
  - Difficult: "This role isn't working"

The stakes: These conversations affect people's livelihoods, confidence, and careers. Getting them

right matters enormously.

The challenge: You need to:

• Ground yourself in evidence (not emotion or impression)
  - Be fair (not overstating or understating)
  - Be clear (not ambiguous or unclear)
  - Be human (not corporate or robotic)

The AI opportunity: AI helps you:

• Organize performance data
  - Draft talking points
  - Anticipate reactions
  - Structure conversation flow
  - Synthesize feedback from multiple sources

Critical: AI is support. Your judgment on fairness, accuracy, and human sensitivity is paramount.

Core Concepts

1. Evidence Organization

Strong performance conversations rest on evidence:

• What they delivered: Projects shipped, metrics, work completed
  - How they delivered: Process, collaboration, learning, growth
  - Where they fell short: Specific gaps, impact, pattern vs. one-off
  - Opportunities: What would unlock more impact?

Organize this clearly before the conversation.

1. Fairness Assessment

Ask yourself:

• Would I say this to their face? (If not, it's gossip, not feedback)
  - Is this supported by evidence? (If not, it's opinion)
  - Have they had chance to succeed? (Or am I judging them on unclear expectations?)
  - Am I treating them how I'd want to be treated? (Or am I being harsh?)
  - Is this feedback or venting? (Be clear about your intent)

1. Feedback Structure

Good feedback includes:

• Observation: "I noticed..."
  - Impact: "Here's what that affects..."
  - Opportunity: "Here's how we could address it..."
  - Support: "Here's what I'll do to help..."

Not: Judgment, emotion, vague complaint.

1. Growth Mindset

• Assume people can improve
  - Be clear about expectations
  - Provide support and resources
  - Give time to show change
  - Follow up and acknowledge progress

People live up to or down to expectations.

1. Accountability

Performance management is about:

• Clarity (are they clear on expectations?)
  - Support (are we providing resources?)
  - Honesty (are we being straight about gaps?)
  - Consistency (are we treating people fairly relative to each other?)

Practical Use Cases

1. Periodic performance review (annual, half-year, quarterly assessment)
2. Mid-year feedback (check-in, not formal review)
3. Constructive feedback (something needs to change)
4. Positive feedback (recognition, reinforcement)
5. Promotion conversation (here's your next opportunity)
6. Difficult feedback (performance is at risk, job may be at stake)
7. Continuation decision (keep going or part ways?)

Examples

Example 1: Constructive Performance Review

Scenario: Sarah is solid but hasn't grown much. She's competent but not excelling. You want to help

her step up, but you're also realistic about fit. How do you prepare?

With AI:

Prompt:

`

Help me prepare for a performance conversation with Sarah. She's been here 2 years.

What I see:

• Competent execution (ships work, meets deadlines)
  - Limited growth (same skills as when she joined)
  - Lower initiative (waits for direction, doesn't own problems)
  - Solid colleague (gets along, no drama)

The conversation I want:

• Not criticism (she's doing the job)
  - Also not just "doing fine" (she could do more)
  - Help her see opportunity to grow
  - Be clear on what growth looks like
  - Understand if she wants to grow or is satisfied where she is

How do I prepare for this conversation?

`

AI suggests:

`

Evidence organization:

• What she delivered (on time, quality is solid, meets requirements)
  - How she delivers (needs clear requirements, doesn't proactively solve problems)
  - Growth gaps (could take more initiative, could learn new skills, could mentor others)
  - Strengths to build on (execution, reliability, collaboration)

Conversation structure:

1. Opening (appreciate what she does well)
2. Observation (here's what I see about growth opportunities)
3. Dialogue (how does she see it? What does she want?)
4. Opportunity (here's what growth could look like)
5. Support (here's what I'll do, here's what I need from you)
6. Close (clear next steps)

Key question: Does she want to grow, or is she satisfied in her current level?

If satisfied -> Different conversation (reinforce strengths, find fulfilling work)

If wants to grow -> Help her see path

If unsure -> Explore what growth means to her

`

Your Preparation:

Evidence to Reference:

• Feedback from colleagues: "Reliable, easy to work with" (positive)

Your Narrative:

"Sarah executes well. She ships solid work. She's a reliable colleague. Over two years, she's become

very good at her current level. I want to talk today about what's next--what's the next chapter for her

growth? Not because she's struggling, but because she has potential to do more, and I want to understand

if she wants to reach for that."

Conversation Frame:

"You've been solid in your role. I want to talk about growth. Here's what I see: You're great at executing

when you have clarity. I'd love to see you take more initiative--spotting problems before I do, proposing

solutions, driving work more independently. Not because you're failing now. Because I think you have it in

you. What's your take? How do you see your growth?"

If interested:

"Great. Here's what growth looks like: [specific--maybe lead this project, own this domain, mentor

If hesitant:

"That makes sense. Maybe growth isn't what you want right now, and that's OK. Let's talk about what

you do want. Do you want to stay in this level? Do you want to specialize deeper? Do you want something

different? I want you to be fulfilled in your work."

Example 2: Difficult Performance Conversation

Scenario: Marcus's performance has dipped. Quality issues. Missing deadlines. Attitude change.

This is getting to "needs to improve or we have a problem" territory. How do you prepare?

With AI:

Prompt:

`

Help me prepare for a difficult performance conversation with Marcus.

What's happened:

• Quality dipped (bugs, incomplete work)
  - Missed deadlines (3 of last 4 sprints)
  - Attitude shift (less engaged, frustrated in meetings)
  - Timeline: 6-8 weeks of this pattern

This isn't one mistake. It's a trend. I need to be direct that this needs to change.

How do I prepare for this conversation? I want to be fair but clear this is serious.

`

AI suggests:

`

Fairness check:

Conversation approach:

1. State the pattern clearly (here's what I'm observing)
2. Ask about context (what's going on?)
3. Be direct about impact (this affects team and Marcus)
4. Be clear about what needs to change
5. Offer support but also clarity on stakes
6. Get commitment or next steps

Key tone: Serious, direct, fair. Not angry. Not soft.

`

Your Preparation:

Specific Evidence:

Your Opening:

"Marcus, I want to talk about something that's concerning me. Over the last six to eight weeks, I'm seeing

a pattern: deadlines are being missed, quality has dipped, and I notice your engagement seems different.

This is important, so I want to understand what's going on."

If there's context (personal issue, unclear expectations, workload):

If there's no clear context:

Closing:

things are going. If we're moving in the right direction, great. If not, we'll need to talk about what

that means for your role here. Fair?"

After the conversation:

Send email recap:

"Thank you for the conversation. Here's what we discussed:

Anti-Patterns & Misuse Risks

1. Using AI to Avoid Difficult Emotions

Risk: You use AI to draft something perfect, but it avoids the actual hard conversation.

Mitigation: AI helps organize. You do the hard conversation. It's supposed to be hard.

1. Feedback That's Too Harsh or Too Soft

Risk: AI can draft something that sounds reasonable but is either over-the-top or vague.

Mitigation: Read it aloud. Would you say it that way? Does it sound like you?

1. Gathering Evidence on People's Behavior Outside Work

Risk: Using personal information that's not relevant to performance.

Mitigation: Stick to work performance. Personal life is their business.

1. One-Sided Evidence

Risk: Gathering only evidence that supports your view, ignoring contradictions.

Mitigation: Look for evidence in multiple directions. What would argue against your view?

1. Feedback Without Support

Risk: Telling someone they're falling short without offering help to improve.

Mitigation: Always pair feedback with "Here's what I'll do to help."

Human Judgment Checkpoints

Critical moments where you override or adapt:

1. Fairness check: Is this fair? Would I say this to their face? Would I want to hear it?
2. Evidence check: Is this supported by evidence, or am I venting?
3. Context check: Do I understand their full situation? Should I ask?
4. Support check: Am I offering genuine support, or just criticism?
5. Tone check: Am I being direct but human? Or am I being corporate/cold?
6. Sensitivity check: What's this person likely to be feeling? How do I acknowledge that?

Responsible AI Considerations

1. Authenticity

The risk: AI-drafted talking points sound corporate, not like you.

Your practice: Rewrite for your voice. If it doesn't sound like you, they'll feel it.

1. Human Dignity

The risk: AI can optimize words but miss the human reality of what's being discussed.

Your practice: Remember you're talking to a human. Their livelihood might be at stake.

1. Avoiding Hidden Bias

The risk: AI can amplify existing biases in how you've framed things.

Your practice: Test your own assumptions. Are you being fair relative to how you'd treat someone else?

Key Takeaways

• Ground in evidence. Specific examples, not impressions.
  - Be fair. Would you say this to their face? Have they had chance to succeed?
  - Be clear. Not ambiguous. People should know where they stand.
  - Pair feedback with support. Don't just critique; offer help.
  - Follow up. Check-in on progress. Acknowledge improvement.
  - Stay human. They're a person, not a performance rating.

Terms & Glossary Items

• Behavioral feedback: Specific feedback on actions/patterns, not personality
  - Evidence: Observable facts supporting your feedback
  - Fairness: Would you say this to their face? Have they had chance to succeed?
  - Growth mindset: Assume people can improve; be clear on expectations and support
  - Accountability: Clarity + support + honesty + consistency

Related Lessons

• Lesson 1.2: Difficult Conversations Preparation -- Similar framework for difficult conversations
  - Lesson 4.2: Coaching and Development Planning -- Broader development context
  - Lesson 4.4: Feedback Crafting -- Specific feedback techniques

[SYNTHESIS AND APPLICATION]

Let us step back and look at the bigger picture of what we have covered in this session on Preparing Performance Conversations.

The concepts here are not abstract frameworks meant to sit in a binder on your shelf. They are practical tools for the decisions you make every day as a manager. Whether you are leading a small team or a large department, whether you work in technology, finance, healthcare, education, or any other sector, the principles we discussed apply to your work right now.

Here is what I want you to take away from this session:

First, the conceptual understanding. You now have a clearer mental model of preparing performance conversations and how it fits into the broader landscape of AI-augmented management. This mental model is what allows you to make good decisions rather than reactive ones.

Second, the practical application. We walked through specific scenarios, examples, and frameworks that you can apply in your work this week. Not next quarter. This week. I want you to identify one specific situation in your current work where you can apply what we discussed today.

Third, the judgment dimension. Perhaps most importantly, we discussed when and how to exercise human judgment. AI is a powerful tool, but it requires an informed, thoughtful manager at the helm. That is you. Your judgment, your context awareness, your understanding of your team and your organization, those are irreplaceable.

[REFLECTION EXERCISE]

Before we close, I would like you to spend two minutes, just two minutes, on this reflection:

Think about your work this past week. Identify one task, one decision, one communication where the concepts from today's lesson would have changed your approach. What would you have done differently? What would the outcome have been?

Write that down. That connection between concept and practice is where real learning happens.

[CLOSING REMARKS]

In our next lesson, we will explore Coaching and Development Planning, which builds directly on what we have covered today. I would encourage you to complete the reflection exercises before moving on, as they will prepare you for the next set of concepts.

This has been Lesson 4.1: Preparing Performance Conversations, part of the Performance and Coaching Support module in Level 3: Independent AI Application of the AI for Managers certification.

Remember: the goal is not to know more about AI. The goal is to be a better manager because of how you use AI. Those are very different things, and this program is designed for the latter.

Thank you for your time, your attention, and your commitment to growing as a leader in an AI-transformed workplace. I look forward to our next session together.

END OF TRANSCRIPT

AI for Managers Certification Program

Level 3: Independent AI Application | Performance and Coaching Support | Lesson 4.1

A SkillsClinic initiative by No Worker Left Behind and The Work Company.

Duration: ~13 minutes | Word Count: ~2097