AI Driven PM: S2E8 - Resistance, Revenge, Resentment

 

Stop Counting. Start Leading.

Let me tell you something I learned that changed the way I lead.

Around 2012, I got serious about personal development. I joined the John Maxwell team. I had phenomenal coaches and mentors around me. And one teaching from Paul Martinelli hit me in a way I wasn't expecting.

He was talking about relationships. And he said:

"The danger in relationships is counting."

Once you start counting—that's the third time they've done that, that's the fourth time that's happened—you've started keeping score.

And once you're keeping score, three things happen. He called them the Three R's.

Resistance. You start pulling back. Cutting the person off a little. Creating distance.

Revenge. You start doing the same thing back to them. They're going to do that to me, I'll do it to them.

Resentment. And this is the dangerous one. This is emotional withdrawal. Leadership doesn't care. Nobody's paying attention. I'm done.

Once resentment sets in, that relationship is over.

Here's what hit me: I'm data-driven. I count everything. And when I traced the roots of some of my most difficult client relationships, I could see exactly when I had started counting their failures instead of solving their problems.

I was tracking the wrong metrics. And it cost me relationships.

But that's not why I'm telling you this story.

I'm telling you this because those same Three R's? They're happening on your change initiative right now.

Your Tool Isn't Failing. Your Change Management Is.

Three months after rollout, 60% of people are still using spreadsheets.

Teams are calling the new PM tool "Rick's surveillance tool."

Two departments are openly hostile. Leadership announced the rollout and then disappeared. Training was a 90-minute session with no follow-up.

Sound familiar?

Here's the sequence:

• Resistance: Passive non-compliance. "I'll just keep using spreadsheets until this blows over. Every few years they try something new. I'll wait them out."
• Revenge: Active demonstration that it doesn't work. "You want me to use this? Fine. I'll use it. And I'll make sure everyone knows how painful it is."
• Resentment: Emotional withdrawal. "Leadership doesn't actually care. Nobody reads these reports anyway. I stopped doing it six weeks ago and nobody noticed."

And here's the painful truth that Claude told me in our live demo and I couldn't have said it better:

"This is not a training problem or a tool problem. It is a trust problem with a workflow mismatch layered on top."

You didn't fail at selecting technology.

You failed at managing the human side of change.

People Don't Resist Change. They Resist Being Changed.

This is where DISC blew my mind.

I mentioned DISC in Episode 7. But here's the stat that changed the way I think about every rollout I've ever managed:

69% of the population is High S.

High S personalities love routine. They thrive on predictability. They come in, everything is in its place, and they do their best work.

They will change. But they don't like being changed.

And most organizations manage change initiatives like High D personalities designed them—fast, decisive, bullet point, done.

You announce it. You train them. You expect adoption.

And then you wonder why 60% of people are still using the old system three months later.

Here's the other piece nobody says out loud: People won't change unless they hurt enough that they have to, or care enough that they want to.

That's it. Those are the only two change levers.

Most change initiatives activate neither.

Why Change Initiatives Really Fail

It's almost never about the tool.

Here's what I've seen in 150+ implementations:

We focus on the WHAT. We ignore the WHO.

New tool. New process. New org structure. We spend 90% of our time configuring, integrating, testing, and training on the what—and about 10% on the people who have to actually change their behavior.

And then when adoption fails, we schedule more training.

More training on a tool people don't trust won't fix a trust problem.

What actually triggers the Three R's:

• Change is done to people, not with them
• No clarity on why the change matters
• No voice or input in how the change happens
• Broken trust from past change initiatives that went nowhere
• Leaders who disappear after the kickoff

And I want to call out one thing that kills me in every large-scale implementation I've ever seen:

They cut training. They cut change management. They cut project management.

The ERP costs 2 million. The configuration runs over. And when they need to find money, they cut the things that ensure the whole thing actually works.

"We have people internally who can handle that."

No. You don't. Not because your people aren't capable—but because change management is a discipline, not a checkbox. And it requires time, intentionality, and someone who isn't also trying to do their day job.

AI Change Management Is Different

Here's what makes the current AI rollout wave particularly dangerous:

AI change is personal in a way that a new PM tool isn't.

When you roll out monday.com, people are annoyed. When you roll out AI tools, people are scared.

They're wondering: Is this the beginning of my replacement? Are they tracking my productivity to justify headcount reduction? Am I being automated out of relevance?

I've answered some version of "Will AI replace project managers?" dozens of times. The answer is the same every time: AI won't replace project managers, but you will be replaced by a project manager who knows how to leverage AI.

But when you're rolling out AI to a team that doesn't believe that? When leadership is absent, training was insufficient, and people don't see "what's in it for me"?

The Three R's hit faster and harder than with any previous technology adoption.

If you're not actively managing the people side of your AI rollout, you're watching the clock count down to resentment.

The Clarity Tool Lesson

Let me tell you one more story.

I used to do a lot of project rescue work. Organizations would call me when their implementation had gone wrong and they needed someone to come in and fix it.

For years, I supported CA Clarity—one of the most powerful PPM tools on the market. You could automate almost any process imaginable. Incredibly configurable.

But I'd walk into these organizations and feel the resentment the moment I walked in the door.

The tool hadn't been deployed well. The adoption had failed. People hated it. And the damage was done.

We could rebuild it. We could redesign it. We could deploy it properly this time, do real training, proper change management.

But the resentment gap was nearly impossible to overcome.

People had already decided. The tool was garbage. Leadership couldn't be trusted. Nothing would change.

So I had to transition my business from rescue work to implementation work.

Because trying to recover from resentment? That's a nearly impossible project.

This is why I say: Catch resistance early. Address it at resistance. Don't let it become revenge. And don't let revenge become resentment.

The Three Prompts That Help You Diagnose and Act

I ran three prompts live today using a scenario most of us recognize: A PM tool rollout three months in, with 60% still using spreadsheets and two departments calling it "Rick's surveillance tool."

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Prompt 1: Change Readiness and Engagement Diagnostic (Your Non-Negotiable)

What it does: Assesses where your team sits on the change readiness spectrum, identifies what stage of the Three R's you're in, surfaces root causes, and gives you a 30-day action plan to shift sentiment and build ownership.

What the AI told me:

ChatGPT's change readiness diagnosis:

• Most of the organization: between understanding and acceptance (they know the tool exists but don't believe in its value)
• Hostile departments: at awareness only (they know it exists and actively reject it)

Three R's signals:

• Resistance: Monday.com is being used as a reporting layer, not a system of work. Spreadsheets still run the actual business.
• Resentment: Calling it "Rick's surveillance tool" signals distrust of leadership intent. They believe this serves leadership control, not team productivity.
• Revenge: Double work creates visible friction. Teams signal frustration through inefficiency without open confrontation.

Claude's action plan:

Move 1: Co-creation with resistant departments.

"Do not push more training or communications into hostile departments. Go in and listen first. Facilitate working sessions where they redesign their monday.com boards to match how they actually work. Give them ownership of the configuration.

This is the only credible counter to the surveillance narrative. When they build it, it stops being yours."

That last sentence is everything.

Move 2: Activate the 40%.

"Identify two or three visible, respected people per department who are already using it effectively. Make them peer coaches—not ambassadors. Peer-to-peer adoption is faster and more credible than top-down instruction. Document one concrete time-saver or meeting eliminated per team as a proof point."

And the metric I loved most from Claude:

Number of times leadership references monday.com data in informal settings.

Because if leadership doesn't use it publicly, nobody believes it matters. That's not a usage metric. That's a trust metric.

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Prompt 2: Resistance Root Cause Analyzer

The behaviors I gave it:

• People say yes in meetings, then don't change behavior
• Slack is full of "this tool is stupid" comments
• One manager told their team: "Just keep using the spreadsheet. This will blow over."
• Multiple IT tickets requesting to be removed from the system
• Poor training participation (multitasking, minimal questions)
• One senior engineer said publicly: "This is just another fad. Remember when we tried [previous tool]?"

What the AI diagnosed:

Type of resistance:

• Passive: Yes in meetings, no behavior change
• Active: Slack complaints and vocal opposition
• Avoidance: Low training engagement
• Sabotage: The manager telling their team to keep using spreadsheets

Underlying fears:

• Fear of demonstrated incompetence (low training engagement = they don't want to look like they can't figure it out)
• Fear that this change signals something about their future (Big Brother tracking)
• Fear of workload increase without compensation ("You're increasing what I have to do without increasing what you pay me")

Unmet needs:

• Need for input and co-authorship
• Need for competence and psychological safety
• Need for a manager who's actually aligned

The senior engineer's comment is the most important signal of all. When someone says, "Remember when we tried [previous tool]?"—they're not complaining about this tool. They're telling you: "I've been through this before. Nothing changed. Why would this be different?"

That's broken trust from past failures. And no amount of training fixes that.

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Prompt 3: Co-Creation and Ownership Strategy

Here's the key reframe Claude gave me before building the strategy:

"The worst version of participatory change is pretending people have input they do not have. Name the constraint honestly before you invite collaboration."

What I could actually open up for input (even though the tool decision was final):

• How boards are configured
• What the required fields look like
• Automation rules and permission structure
• Update frequency and check-in norms
• Who owns each board

That's not a small thing. When people design how their system works, it becomes their system. Not the tool leadership forced on them.

The pilot experiment approach: Run a 30-day experiment with one willing team, not to prove the tool works—to learn what actually makes it work for them. Then share those wins peer to peer.

The communication principle: Don't claim you're listening if you're not prepared to act on what you hear. Performative co-creation is worse than no co-creation. It validates the cynicism.

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Your Non-Negotiable Experiment This Week

Run the Change Readiness and Engagement Diagnostic (Prompt 1) on a current or recent change initiative.

Then take one action: either invite co-creation or directly address a root cause of resistance.

Here's what I want you to notice:

1. Does giving people a voice shift sentiment—even when the change itself is non-negotiable?
2. Do you discover root causes you hadn't seen before?
3. Where on the Three R's spectrum is your team, really?

Because here's the truth:

You can have the best tool in the world. If you skip the people side, it will fail.

And once resentment sets in, you're not doing a rescue. You're doing a replacement.

Catch it at resistance. That's where change is recoverable.

Stop counting their failures. Start co-creating their success.

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Next time: Coaching First, PM Second—why facilitation is one of your most valuable skills in the AI era, and how to lead without being the one with all the answers.

Check out the live episode on YouTube: 

Now go find out where your change initiative really is.

— Rick A. Morris

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The Prompts (Copy/Paste Ready)

Prompt 1 - Change Readiness and Engagement Diagnostic

You are an organizational change management consultant.

First, ask me 5–7 questions about the change initiative, the people affected, their current behavior and sentiment, past change history, and leadership engagement.

Then provide a diagnostic and strategy that answers:

1. Where is the team on the change readiness spectrum? (awareness, understanding, acceptance, adoption, or advocacy)
2. What signs of resistance, revenge, or resentment am I seeing?
3. What are the root causes of resistance? (lack of clarity, fear, broken trust, no input, poor execution)
4. What change management strategy should I use? (communication, co-creation, small wins, leadership modeling)
5. What specific actions should I take in the next 30 days to shift sentiment and build ownership?
6. How do I measure progress in change adoption beyond the number of people trained?

Change initiative context: [Enter Context]

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Prompt 2 - Resistance Root Cause Analyzer

You are a behavioral psychologist specializing in organizational change.

Ask me 3–5 questions about specific resistance behaviors, what people are saying or not saying, and what happened leading up to the resistance.

Then analyze the root causes by answering:

1. What type of resistance am I seeing? (passive, active, avoidance, or sabotage)
2. What are the underlying fears or concerns driving the resistance? (fear of job loss, loss of control, incompetence, increased workload)
3. What unmet needs are people expressing through resistance? (clarity, input, support, or trust)
4. What past experiences are influencing current resistance? (previous failed changes, broken promises)
5. How do I address root causes rather than just symptoms?

Resistance behaviors observed: [Enter Context]

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Prompt 3 - Co-Creation and Ownership Strategy

You are a change management facilitator specializing in participatory change.

Ask me 3–4 questions about the change initiative, who's affected, and where I could invite input or co-creation.

Then design a co-creation strategy answering:

1. Where in the change process can I invite people to shape HOW—not just accept WHAT?
2. What decisions can I delegate or open up for input?
3. How do I identify and empower change champions within resistant groups?
4. What pilot or experiment can I run WITH the team (not TO the team) to build ownership?
5. How do I communicate that input is genuinely valued and not just performative listening?

Change initiative and constraints: [Enter Context]

 

AI Driven PM: S2E7 - The Greatest Lie Ever Told in Project Management

Why Influence Is the Only Skill That Actually Matters

Somebody told me early in my career that I owned my project.

Owned it. Like it was mine.

Like I could make decisions, adjust budgets on the fly, tell people what to do, and hold the team accountable because—hey—it's my project.

Let me tell you what I actually owned:

The blame. When things went wrong, I owned that.

Here's the reality of project management that nobody puts in the job description:

• The people don't report to me
• It's not my money
• It wasn't my idea
• I don't set the timeline
• I don't control the strategy

And yet somehow, when the project goes sideways, everybody looks at the PM and says, "Why didn't you see this coming?"

That's the contradiction at the heart of our profession. And it's exactly why influence is the number one skill you need to develop.

Not scheduling. Not risk management. Not Agile certification.

Influence.

You Can't Make Anyone Do Anything

Let me be really clear about something:

As a project manager, you cannot make anyone do anything.

You can't make your team work faster. You can't make your sponsor change the date. You can't make your executive adjust the budget. You can't make your stakeholders show up prepared.

All you can do is influence the outcome.

Here's how I describe our actual job: We increase the percentage chance of hitting a date or budget by doing analysis, building plans, framing decisions, and then influencing whoever we're speaking with—team, sponsor, executive, customer—toward the outcome the project needs.

PMs operate in the influence space between silos.

We're the connective tissue. We're the translators. We're the ones standing between engineering's reality and the sponsor's dream, trying to close the gap without anyone getting hurt.

That's not authority. That's influence. And they require completely different skill sets.

The Three Currencies of Influence

If you haven't read Cialdini's Influence: The Science and Practice of Persuasion, go get it today. It feels like a sales and marketing book. But think about what we do every day:

• Selling a position to move a date
• Marketing the case for a budget adjustment
• Persuading a skeptical stakeholder to trust the process

We are in sales. We just don't call it that.

From my experience, PMs work primarily in three influence currencies:

1. Credibility

People trust your judgment because you've earned it.

Not because of your title. Not because of your certification. Because of your track record, your preparation, your follow-through.

Credibility is the currency you build over time. And it's the one that gets spent fastest when you overpromise, underdeliver, or show up unprepared.

2. Reciprocity

You help others achieve their goals—and they help you achieve yours.

I think this is the most powerful influence lever PMs have access to. When you go to bat for someone, cover for them, solve a problem before they ask, create opportunities for them to shine—you build something that no org chart can give you.

Real influence is banked through real acts of service.

One important note though: Don't explicitly remind people of what you did for them and then ask for something back. I'll come back to this—Claude made this mistake in our live demo, and it's worth discussing.

3. Vision

You paint a picture of success so compelling that people want to contribute.

This is why we develop dream statements, mantras, and team motivation stories. We covered this in Episode 1. The reason I invest so heavily in clarifying the why behind every project is because people don't get inspired by Gantt charts.

They get inspired by a destination they believe in.

When they can see the win—when they can feel what success looks like—influence becomes almost effortless.

Three Common Influence Mistakes (That Kill Your Credibility)

1. Over-Relying on Logic

You build the perfect case. The math is airtight. The risk analysis is complete. You walk into the meeting absolutely certain that any reasonable person will see it your way.

And then the sponsor says, "We're making that date no matter what."

Logic without emotional intelligence isn't influence. It's a monologue.

2. Positional Pleading

"The CEO said so." "This is what the executive team wants." "I have authorization from leadership."

That's not influence. That's borrowed authority. And it erodes trust every time you use it, because people know you're not actually speaking for yourself.

3. Passive Aggressive Escalation

"I guess I'll just have to escalate this to the executive team." "I'll let them know we're going to miss the date."

This is an influence killer. Nobody rallies around a PM who threatens escalation. They shut down, get defensive, and you lose the relationship.

Real influence doesn't require threats. It creates alignment.

The DISC Secret Weapon

Here's something that transformed how I communicate with stakeholders:

One message. Four different ways to say it.

DISC is a behavioral assessment framework with four communication styles:

• High D (Dominant): Bullet points, get to the point fast, no fluff
• High I (Influential): People-focused, enthusiastic, what's exciting about this?
• High S (Steady): Change-resistant, needs context, what's the impact on the team?
• High C (Conscientious): Data-driven, detail-oriented, show me the facts

If you bring a five-paragraph explanation to a High D, they check out at sentence two.

If you lead with data and logic for a High S who's worried about their team, you miss the real concern.

Meeting people where they are isn't manipulation. It's respect.

And when you combine that with Socratic AI prompting—where you give the AI context about the stakeholder's style and ask it to help you craft the message—you unlock something powerful.

The Three Prompts (And What the AI Actually Gave Me)

I ran three influence prompts live using our Social Wishing app scenario: We need to cut three MVP features—AI recommendations, in-app messaging, and payment integration—to protect the launch date and save the team from burnout.

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Prompt 1: Influence Network Mapper (Your Non-Negotiable)

What it does: Maps the key influencers and decision makers, identifies their positions and motivations, recommends influence tactics for each, and builds you a conversation sequencing strategy.

What I got:

ChatGPT opened with:

"You're not trying to win an argument. You're trying to align incentives around a shared risk. The hidden risk isn't feature loss. It's execution failure."

That reframe alone is worth the price of admission.

The sequencing strategy it gave me:

1. Engineering manager first — Meet privately, turn frustration into structured input. Ask them to quantify velocity trends, estimate burnout risk, and calculate realistic delivery probability. "I need your help protecting the team and protecting the date. I don't want this to become an engineering versus business fight."
2. Product owner second — Pre-align before the CEO meeting. Convert engineering evidence into risk framing.
3. Marketing director third — Build the narrative that gives the CEO something to say publicly.
4. CEO last — Walk in with the engineering risk doc, the product owner's alignment, and the marketing director's framing already in hand.

And then Claude gave me the closing guidance that absolutely nailed it:

"You're not building consensus. You're building a sequence of aligned conversations so that by the time you reach the CEO, the decision feels inevitable rather than contentious. Each conversation should leave the stakeholder feeling heard—not managed. The goal is that no one walks into the CEO meeting as a surprise voice of opposition."

That's the playbook. Pre-wire every conversation so the final meeting is a confirmation, not a confrontation.

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Prompt 2: Stakeholder Persuasion Message Crafter

The specific situation: Convincing the executive sponsor—who loves AI and sees it as a market differentiator—to launch without AI recommendations.

What the AI gave me:

The core message:

"Launching AI recommendations before the user base exists to train them guarantees this feature underperforms at the exact moment it needs to impress the board."

The analogy:

"Netflix didn't launch with a recommendation engine. They launched with the catalog. The recommendation engine came after they had enough viewing data to make it work. An AI feature trained on zero user behavior doesn't differentiate you—it could embarrass you."

And then the strategic opportunity flip:

"A post-launch AI reveal gives you two press moments instead of one. We launched clean. We proved traction. Now we're releasing AI 1.1 with real usage data. That's a story—not a patch."

ChatGPT offered a different analogy:

"Launching without data-driven AI is like launching a Tesla without Autopilot enabled."

Both are strong. Both give the sponsor something to say in the boardroom. Leaders love a reference story that makes their decision sound precise, not reactive.

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Prompt 3: Reciprocity & Coalition Builder

Here's where I want to be honest about the tool differences—because one of the most valuable things I can do in this series is show you where AI gets it right and where it gets it wrong.

Claude's suggestion for the engineering manager:

"I backed their QA resource request. Now I need to go to them first, privately, and name it directly: 'I went to bat for you on QA. I need you to go to bat for me—and for the team—now.'"

I pushed back on that.

Don't explicitly call out the favor. The moment you say "I did this for you, now you do this for me," you've turned reciprocity into a transaction. And the next time you do something generous for that person, they'll wonder what you're banking it for.

Real reciprocity doesn't need to be verbalized. It should be felt.

ChatGPT handled it better:

"You backed their QA request. That built trust. What they want now is team stability and credibility. Help them by making sustainable scope the official position—not a quiet concern. If you carry the political weight, they don't have to."

That's the difference. You're not reminding them of a debt. You're aligning your ask with their interests and removing a burden from their plate.

That's influence.

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The Big Picture

Here's what I want you to take away from this episode:

You'll never have authority over the things that determine project success. Budget, people, strategy, timeline—none of it is yours.

But influence? That's entirely within your control.

Map your influence network. Understand what each person cares about. Sequence your conversations. Build reciprocity through genuine acts of service. Craft messages that meet people where they are.

And then watch what happens when a PM walks into a final decision meeting where the outcome is already inevitable.

That's not manipulation. That's masterful leadership.

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Your Non-Negotiable Experiment This Week

Use the Influence Network Mapper (Prompt 1) on a real decision you need to influence this week.

Then have at least one conversation using the strategy or message AI helps you design.

Here's what I want you to notice:

1. Did mapping the influence network reveal leverage points you hadn't considered?
2. How did stakeholders respond when the message was framed around their priorities?
3. Did the sequencing strategy change how the final conversation landed?

Because here's the truth: The most effective PMs I've ever met don't win by being the loudest or the most technically correct. They win by knowing exactly who to talk to, in what order, with what message.

And now you have a thinking partner that helps you figure all of that out in minutes.

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Next time: The Three R's—Resistance, Revenge, and Resentment. Why change initiatives fail, what happens when people get caught in the Three R's, and how to use AI to navigate your way out.

Want these prompts ready to copy/paste? Head to PMThatWorks.com for the full library.

Now go map your influence network. The decision is waiting.

— Rick A. Morris

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The Prompts (Copy/Paste Ready)

Prompt 1 - Influence Network Mapper

You are an organizational influence strategist and stakeholder engagement expert.

First, ask me 4–5 questions about the decision I need to influence, who's involved, what their interests are, and what resistance I expect.

Then provide an influence strategy answering:

1. Who are the key influencers and decision makers in this situation?
2. For each person, what do they care about, what motivates them, and what concerns might they have?
3. What is each person's current position? (supporter, neutral, or blocker) and their level of influence?
4. What influence tactics should I use with each person? (credibility, reciprocity, vision, data, coalition building)
5. What is my sequencing strategy? Who do I approach first, and how does that set up the next conversation?
6. What message framing will resonate most with each stakeholder type?

Decision and context: [Enter Context]

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Prompt 2 - Stakeholder Persuasion Message Crafter

You are a communication strategist specializing in persuasive stakeholder messaging.

Ask me 3–4 questions about the stakeholder, the message I need to deliver, their priorities, and what objections I expect.

Then craft a persuasive message by answering:

1. What is the core message in one sentence?
2. What framing will resonate most with this stakeholder's priorities? (data, vision, risk mitigation, opportunity)
3. What story or analogy makes the message memorable?
4. What objections will they raise, and how do I preempt them?
5. What ask or call to action do I make, and how do I make it easy for them to say yes?

Provide the message in an email or conversation script format.

Stakeholder and situation: [Enter Context]

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Prompt 3 - Reciprocity & Coalition Builder

You are a relationship strategist helping PMs build reciprocity and coalition.

Ask me 3–4 questions about the people I need to influence, what they care about, and how I've helped or could help them.

Then provide a reciprocity and coalition strategy answering:

1. What have I done (or could I do) to help each stakeholder achieve their goals?
2. How do I frame my ask as aligned with their interests—not just my project needs?
3. Who are the natural allies I should recruit first to build a coalition?
4. How do I leverage early supporters to create momentum with skeptics?
5. What specific conversation should I have this week to build reciprocity and alignment?

Situation and key people: [Enter Context]

 

AI Driven PM: S2E6 - Net Operating Value

Your Project Isn't Competing Against a Standard. It's Competing Against Everything Else.

Have you ever had a project going really well—hitting milestones, staying on budget, team is energized—and an executive pulls the plug?

You're furious. You're confused. You think, "How could they kill this? We were succeeding."

Here's the uncomfortable answer: Because they weren't evaluating your project. They were evaluating your portfolio.

And those are completely different conversations.

Most project managers optimize in isolation. We focus on our project. Our timeline. Our velocity. Our scope. We find our lane and we stay in it.

But executives? They're not optimizing your project.

They're optimizing across a dozen projects competing for the same people, the same budget, and the same strategic window.

And without a shared language for value—one that accounts for all the trade-offs—PMs and executives talk right past each other.

Your project looks green. Their portfolio looks broken.

That's the gap. And that's exactly what Net Operating Value is designed to close.

What Is Net Operating Value?

Net Operating Value (NOV) is a metric I helped develop to tell a more complete story about project value.

Here's the formula:

NOV = Expected Value − Effort Cost − Risk Cost − Opportunity Cost

Let's break that down:

Expected Value: Revenue, cost savings, strategic positioning, user impact. Everything you gain if the project succeeds.

Effort Cost: Budget, team capacity, person-months, timeline. Everything you spend to get there.

Risk Cost: Probability of failure or underperformance × the financial impact of that failure. What you might lose.

Opportunity Cost: What you are not building because you're building this.

That last one is the one most business cases never include. And it's the one that changes everything.

ROI asks, "Is this worth doing?"

NOV asks, "Is this the best thing we could be doing with these resources right now?"

That's a completely different question.

The AI Capacity Trap

Before we get into the prompts, I want to call out something I'm seeing happen in organizations right now.

They're seeing AI increase team velocity. Story points per sprint are going up. Delivery speed is improving.

And their first instinct is: Let's throw more projects at the team.

I've already had clients say, "If our team's capacity was 270 points before AI, shouldn't it be 390 now? Let's plan accordingly."

And look—maybe. You might see velocity increases. But here's the question you're not asking:

Can we build it? That's the wrong question. The right question is: Should we build it, given everything else we could build?

More capacity doesn't mean more projects. It means more opportunities to choose poorly.

The 2-1-0 philosophy exists precisely for this moment: You need to be two full quarters ahead in ideas competing for quarterly planning, and two full sprints ahead in fully defined, designed, and architected user stories.

Not so you can do more. So you have the tension to choose better.

Can we do this feature? Sure. Should we—given what else is in the queue? That's the real conversation.

Now Let's Do the Math

I ran three prompts live against our Social Wishing app—the bucket-list social platform we've been building throughout this season.

And the results were... illuminating.

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Prompt 1: NOV Calculator (Your Non-Negotiable)

What it does: Calculates a full NOV assessment—expected value, effort cost, risk cost, and opportunity cost—and compares your project to a baseline threshold for approval.

I gave it this context:

• 10,000 users in 90 days
• 4.99/month premium, 10% conversion)
• $300,000 budget, six months, eight people
• Fully dependent on Facebook API
• Opportunity cost: A flagship product feature we're not building that could drive $500,000 in upsell revenue with 80% confidence

ChatGPT asked me:

• "What's your gross margin on subscription revenue?" (70%)
• "What's your expected monthly churn rate?" (30%)
• "Are you planning paid acquisition or assuming organic?" (Paid, $11 CAC)
• "If Facebook API access is restricted, what percent of core functionality breaks?" (Total shutdown)

Then it ran the math.

Unit economics summary:

• Monthly price × 70% margin ÷ 30% churn = $11 lifetime value per premium user
• CAC = $11
• Net unit contribution per premium user: 63 cents

ChatGPT's verdict:

"You're spending 50,000 in premium lifetime contribution. This is deeply negative unit economics."

Claude's NOV calculation: Negative $702,000.

"This project has a strongly negative NOV. Your alternative project produces positive expected contribution of $280,000 with far lower uncertainty. Build the flagship feature."

And just like that—in under four minutes—we had a business case analysis that would have taken a finance team days to produce.

That's the power of the NOV calculator.

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Prompt 2: Value Assumption Stress Test

This is the one I love most.

It doesn't just tell you what your project is worth. It tells you which assumptions, if wrong, kill the entire value case—and what you can do about it.

I gave it the Social Wishing business case with these underlying assumptions:

• 10,000 users in 90 days via viral Facebook sharing
• 30% wish fulfillment rate
• 10% premium conversion
• Users will trust the platform with personal bucket list information
• Facebook maintains stable API access
• Organic network effects keep CAC low

Then I answered honestly:

• Never launched a consumer social product before
• No evidence users will share wishes—just a hunch
• No waitlist, no beta, no validated demand
• Not solving an urgent problem—creating new behavior
• No relationship with Facebook's API team

Claude's response:

"Good. Now we're thinking clearly. You just removed most of the illusion from the business case."

Then it walked through each assumption with best case, expected case, and worst case scenarios.

And then it said something I think every PM needs to hear:

"This is not a 25,000 behavior experiment."

It recommended a 45-day validation sprint instead:

• Build a landing page, spend $3-5K in ads, measure cost per email signup
• Start a private community of 100 people manually, see who posts wishes and who engages
• If cost per signup exceeds $5-7 or organic growth assumptions weaken, you have your answer

Then it gave me the framing for the sponsor conversation:

"The question you should be bringing to your sponsor isn't 'Should we build this?' It's 'Can we spend 285,000?'"

That one reframe changes the entire conversation.

You're not saying no to the idea. You're saying yes to being smarter about how you validate it.

How many of us have had a CIO come back from a conference with a "cool thing" they saw? And six months and $300K later, we find out nobody actually wanted it?

This is how you avoid that.

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Prompt 3: Portfolio Trade-Off Analyzer

Now let's zoom out. Three projects. One six-month window. Capacity for two.

The options:

• Option A: Social Wishing (new product) — 300K cost, high risk
• Option B: Flagship product feature (upsell to existing customers) — 200K cost, low risk
• Option C: Infrastructure modernization (tech debt reduction) — 250K cost, medium risk

Which two do you choose?

ChatGPT and Claude gave me the same answer:

Option B + Option C. Kill Option A in its current form.

And here's the framing that I would use in the executive meeting:

"Option B is the cash generator. Option C is the capability builder. Together they fund growth AND protect our future velocity. That's a balanced portfolio."

That's not a financial argument. That's a story. Two sentences. Executives get it immediately.

For communicating the trade-off on Social Wishing, both tools gave me the same counsel:

"Don't frame this as killing creativity. Frame it as disciplined capital allocation."

Script:

• "Our priority this year is predictable revenue growth and operational stability."
• "For every dollar invested in the flagship feature, we get approximately $2 in risk-adjusted value. Social Wishing does not meet that threshold today."
• "Social Wishing is interesting—but unvalidated. We will test demand with a capped experiment before committing full capital."

That's not a no. That's a responsible yes.

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The Full Circle Moment

We spent all season building the Social Wishing dream. We clarified the vision. We wrote the team motivation story. We built the backlog. We ran the health diagnostic.

And now the NOV says: Don't build it. Not yet. Validate it first.

That's not failure. That's exactly how great project management works.

Dreams deserve data before dollars.

And the PMs who can have that conversation with their sponsors—who can say "here's the math, here's the risk, here's the smarter path forward"—those are the PMs executives trust with their most important projects.

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Your Non-Negotiable Experiment This Week

Run the NOV Calculator (Prompt 1) on a current project.

Then identify: What is the one assumption that, if wrong, kills the entire value case?

Test it. Find the cheapest way to validate or invalidate it before committing more resources.

Here's what I want you to notice:

1. Does calculating NOV change how you talk about your project's value?
2. How do executives respond when your business case includes opportunity cost?
3. Did the stress test surface an assumption you've been avoiding?

Because here's the truth: Protecting your project isn't about defending it. It's about proving it deserves the resources over everything else competing for them.

That's thinking like a portfolio manager.

And that's how you earn a seat at the table.

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Next time: Influence without authority—how to lead when you can't command. It wasn't your idea. They're not your people. It's not your budget. So how do you actually move a project forward?

Want these prompts ready to copy/paste? Head to PMThatWorks.com for the full library.

Now go run the math. Your dream deserves to know if it can stand up to the numbers.

— Rick A. Morris

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The Prompts (Copy/Paste Ready)

Prompt 1 - NOV Calculator

You are a portfolio strategist and financial analyst for project investments.

First, ask me 5–7 clarifying questions about the project's expected benefits, costs, risks, and what else the organization could be doing with the same resources.

Then calculate a net operating value assessment by answering:

1. What is the expected value of this project? (revenue, cost savings, strategic value, user impact — quantify as much as possible)
2. What is the total effort cost? (budget, team capacity, person-months, timeline)
3. What is the risk cost? (probability of failure or underperformance × financial impact)
4. What is the opportunity cost? (what alternative projects or initiatives are we not doing because of this?)
5. What is the calculated NOV, and how does it compare to a baseline threshold for project approval?
6. What assumptions are most uncertain, and how would changing them affect the NOV?

Project context: [Enter Context]

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Prompt 2 - Value Assumption Stress Test

You are a critical thinking coach and risk analyst.

Ask me 3–4 questions about the value assumptions underlying my project's business case.

Then stress test those assumptions by answering:

1. What are the 3–5 core assumptions that must be true for this project to deliver its expected value?
2. For each assumption, what is the best case, expected case, and worst case scenario?
3. How sensitive is the project's NOV to changes in each assumption?
4. What evidence or data exists to validate or challenge each assumption?
5. What experiments or MVPs could we run to de-risk the biggest assumptions before committing fully?

Project business case: [Enter Business Case and Assumptions]

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Prompt 3 - Portfolio Trade-Off Analyzer

You are a portfolio management consultant helping executives make investment decisions.

Ask me 3–4 questions about the competing projects or initiatives in our portfolio and the organization's strategic priorities.

Then provide a trade-off analysis answering:

1. How do the competing projects compare on NOV?
2. What projects are must-dos (strategic imperatives) vs. nice-to-haves?
3. What is the optimal portfolio mix given current capacity and risk tolerance?
4. What projects should we greenlight, pause, or kill based on NOV?
5. How do I communicate trade-offs to stakeholders in a way that builds alignment rather than resentment?

Portfolio context: [Enter Competing Projects and Constraints]

 

AI Driven PM: S2E5 - Data Rules 2.0

Let me tell you something I learned from Six Sigma that changed the way I run projects:

If you can't measure it, you can't improve it.

I came up through the DMAIC era—Define, Measure, Analyze, Improve, Control. I love data. I live for metrics. Give me a spreadsheet and a story to tell, and I'm happy.

But here's the uncomfortable truth I've discovered after 30+ years and 150+ implementations:

Most of the metrics we track don't tell the story we actually need to tell.

We obsess over story points. Velocity. Task completions. Hours logged. Burn rate.

And then an executive asks, "Are we going to hit the launch date?"

And we stare at our dashboard.

And it doesn't answer the question.

That's not a data problem. That's a framing problem.

The Activity Metrics Trap

Here's what most PMs measure:

• Story points completed
• Task closes
• Hours logged
• Budget spent to date
• Number of commits to repo

You know what all of those have in common?

They measure busyness. Not achievement.

Activity doesn't equal value. And executives—even if they can't always articulate it—don't actually care about activity. They care about outcomes that drive business value.

I was working with a client recently who said their goal was a 2% net sales lift.

I asked, "If you land Walmart, do you win?"

They said, "No."

I said, "Okay—walk me through what this 2% net sales lift actually means."

And here's what was wild: They were using that metric to justify building a data warehouse, but they had no idea what data they were going to put into the warehouse to measure it.

The metric was real. The measurement plan was nonexistent.

That's the trap.

We pick metrics because they're easy to track, not because they answer the questions that actually matter.

We Are Lawyers. Our Sponsors Are Judges.

Here's a frame I use all the time that completely changes how PMs think about data:

Your job is to build a case. Your sponsor is the judge.

You gather evidence. You analyze the data. You present your recommendation. You let the judge decide.

And if you don't like the ruling? You don't argue in the courtroom.

You appeal.

You go back, review your data, figure out why it didn't tell the compelling story you needed, and you come back better prepared.

And here's the thing: If I have more data than you, I'm going to win the conversation.

Not because I'm louder or more senior or more confident.

Because data tells a story. And the PM who tells the better story wins.

The problem is we keep bringing the wrong data to court.

What You Should Actually Be Measuring

Here's what I suggest you measure instead of activity:

1. Value Delivered

Not "features shipped"—features in production being used.

I worked on the GrowthDay app build. We had all these features planned, but at the last minute, the founder said, "Wouldn't it be cool if we had a daily motivational segment—something that fires people up every morning?"

We almost cut it. Time pressure. Scope pressure.

We didn't cut it.

That tiny, last-minute feature became one of the stickiest in the whole app.

But here's the key: We only knew it because we measured how people were actually using the app. How many times. How long they stayed. Whether they came back.

If you're not measuring features being used, you don't know if you're delivering value or just shipping code.

2. Time to Impact

How fast do you go from idea to user value?

What's your average cycle time from "we need this" to "users are using this"?

That's a story executives actually care about.

3. Quality Signals

Defect rates. Technical debt. User satisfaction.

But here's the nuance: When you compress testing due to date pressure, defect growth becomes exponential—not linear.

I had this exact conversation in a live demo. The data showed:

• Sprint velocity dropped
• Defect rate rising
• Testing coverage shrinking

I told the team: "If testing continues to erode, expect 15 to 18 defects per sprint within four to six weeks. The rework alone will cost more time than the testing would have."

That's the conversation a PM should be having with a sponsor. Not "we're at 80% of story points." But: "We're trading short-term velocity for long-term quality debt. Here's what that actually costs us."

4. Team Health

Velocity stability (not just velocity), morale, attrition risk, sentiment analysis.

A velocity drop after adding a team member? That's normal. Expected, even.

Knowledge transfer consumes senior capacity. Code review loads increase. A 20% velocity drop after onboarding one person is common in the first two to four sprints.

But if it hasn't recovered in three sprints? That's structural. That's something else.

Know the difference.

5. Stakeholder Confidence

Sponsor engagement. Clarity of vision. Meeting attendance.

When your sponsor starts missing meetings, that's a leading indicator—not a footnote.

The Metric I'm Most Proud Of: Scope Stability Index

Here's one I love that most teams don't track:

Scope Stability Index = New story points added ÷ Total committed story points

If that number exceeds 15% mid-sprint, execution predictability collapses.

Let me make that concrete. You committed to 30 story points for the sprint. During the sprint, 10 new points get added. That's 10 ÷ 30 = 33%.

Your sprint just broke.

Not because the team is failing—but because the input changed faster than the output could absorb it.

This is the conversation you bring to a sponsor: "Every time we add scope mid-sprint, we pay a compounding tax. Here's what that tax looks like in data."

That's a case. That's a lawyer walking into court prepared.

How AI Fits Into All of This

Here's the piece most people miss:

AI can automate all the activity tracking.

I have agents that pull data from JIRA, Microsoft Planner, ServiceNow, spreadsheets—normalize it, format it, and report it. Automatically.

That means I'm not spending 60% of my week staring backwards at what already happened.

I'm spending it on outcome measurement, impact analysis, and inventing new metrics that tell the parts of the story nobody else is telling.

AI can correlate your leading indicators (velocity, quality, team sentiment) with your lagging indicators (revenue, retention, delivery dates). It can isolate trends across data sources you'd never have time to manually connect.

But here's the catch, and I said this right at the top of the episode:

AI can't do for you what it can't do through you.

The metrics it surfaces are only as good as the questions you're asking. You have to know what story you're trying to tell before AI can help you tell it.

That's what these three prompts are designed to do.

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Prompt 1: Metrics Dashboard Designer

Start here. This builds you a dashboard that actually answers the questions your executives are asking.

What it creates:

• 3-5 outcome metrics that prove value delivery
• 3-5 activity health metrics as leading indicators
• Data sources and measurement approach for each
• Green/yellow/red thresholds
• How to present differently to executives vs. team vs. sponsor

What I got when I ran it for the Social Wishing app:

ChatGPT asked:

• "What would cause leadership to declare this a failure at month six or nine?"
• "How does this app make money in the first 12-18 months?"
• "Do you have any analytics tooling selected?"

That first question? Bring it to your sponsor. Seriously. Ask them: "What would cause you to declare this a failure at month six?" You'll learn more in that 10-minute conversation than in three weeks of status reports.

The outcome metrics it generated:

• New user signups per week
• 90-day active user rate
• Wish progress rate
• 30-day retention

The leading indicators:

• Visitor-to-signup conversion rate
• Invite rate (% of users who invite at least one friend)
• Time to first wish (median time from signup to first wish created)
• Sprint predictability

The dashboard format for founders: Single slide, three rows.

• Row 1: Growth (signups, conversion)
• Row 2: Engagement (wish progress, invite rate)
• Row 3: Retention (30-day retention, trend arrow)

Simple. Powerful. Tells the dream story.

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Prompt 2: Predictive Risk Indicator Finder

This one is for when you feel something is wrong but can't quite articulate it yet.

What it does:

• Identifies leading indicators that predict trouble
• Correlates team health metrics with outcome metrics
• Surfaces data you're NOT capturing (but should be)
• Sets intervention thresholds
• Coaches you on how to communicate risk without panicking the room

I gave it this project context:

• Sprint velocity dropped from 35 to 28 points
• Defects up from 7 to 12 per sprint
• Code review cycle time averaging 2.3 days
• Sponsor missed last 2-3 meetings
• Team sentiment dropped from 8.0 to 6.5
• 8 new feature requests added this month, 3 original features cut

What AI told me:

"Velocity drop after adding a person is classic onboarding drag. A 20% drop is common in the first two to four sprints. If it doesn't recover within three sprints, the issue is structural—not onboarding."

"Your defect increase combined with shrinking testing coverage is the highest risk signal in your data. When testing coverage drops due to date pressure, defect growth becomes exponential, not linear. Expect 15 to 18 defects per sprint within four to six weeks if nothing changes."

And then—the one I loved most—it surfaced metrics I wasn't tracking:

Code review comment density per PR.

"High comment density means complexity or standards drift. Low comment density with long cycle times means avoidance. These require completely different interventions."

I would never have thought to track that. That's AI as a thinking partner.

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Prompt 3: Vanity vs. Value Metrics Audit

This is the one that will save you from the most painful meeting of your career.

You know the meeting. Twenty executives in the room. You walk through your status report. They eat you alive.

Because your report answered "Are we busy?" instead of "Are we going to succeed?"

I've been in that meeting. I never want you to experience it.

I gave AI this list of my current metrics:

• Tasks completed this week
• Story points burned
• Budget spent to date
• Team utilization
• Number of commits to repo
• Lines of code written
• Meetings held
• Risks identified

And I told it: "Executives keep asking if we'll hit the launch date and user targets. My metrics don't answer that question."

Claude's response was brutal. And perfect:

"Why are you asking me questions, Rick? You've already diagnosed the problem yourself. Your metrics answer 'Are we busy?'—not 'Are we going to succeed?'"

"You have six vanity metrics out of eight. The executives are asking the right question. Your dashboard is giving them the wrong answer. It's not a data problem. It's a framing problem. You're reporting inputs when they're asking about outcomes."

Couldn't have said it better myself.

Then it gave me the swap:

Vanity Metric	Why It's Vanity	Replace With
Story points burned	Doesn't predict completion without trend	Forecasted completion date based on velocity trend
Team utilization	Measures busyness, not throughput	Scope stability index
Commits to repo	More commits can signal churn, not progress	Defect escape rate
Lines of code	More code often = more defects	Time to value / time to first wish

That table is a career-saver.

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Your Non-Negotiable Experiment This Week

Two challenges:

1. Build your outcome metrics dashboard using Prompt 1. Take your current project and identify 3-5 metrics that actually answer your executive's burning questions.

2. Replace at least one vanity metric in your next status report with a value metric.

Just one swap.

Here's what I want you to notice:

• How do stakeholders react when your report answers their actual questions?
• Does better data help you spot risks earlier?
• Do you feel more confident walking into that executive meeting?

Because here's the truth: The PM who tells the better story with better data wins.

Not because they're louder. Because they came prepared.

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Next time: Net Operating Value—the metric I use for portfolio decisions. How to stack-rank your portfolio, make trade-off decisions, and help executives choose between good ideas using data that actually reflects business value.

Want these prompts ready to copy/paste? Head to PMThatWorks.com for the full library.

Now go build that dashboard.

— Rick A. Morris

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The Prompts (Copy/Paste Ready)

Prompt 1 - Metrics Dashboard Designer

You are a data-driven PM coach and metric strategist.

First, ask me 4–5 questions about the project goals, stakeholders, team, and what success means in business terms.

Then help me design a metrics dashboard by answering:

1. What are the 3–5 outcome metrics that prove the project is delivering value?
2. What are 3–5 activity health metrics that are leading indicators of those outcomes?
3. For each metric, what is the data source and how do we measure it?
4. What thresholds or targets indicate green, yellow, red status for each metric?
5. How should I present these metrics to executives vs. the team vs. the sponsor?

Project context: [Enter Context]

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Prompt 2 - Predictive Risk Indicator Finder

You are a predictive analytics expert for project management.

Ask me 3–4 questions about current project metrics, team dynamics, and any early warning signs I'm seeing.

Then analyze potential risk patterns by answering:

1. Based on the metrics I'm tracking, what are the 3–5 leading indicators that typically predict project trouble?
2. What correlation exists between team health metrics (velocity, morale) and outcome metrics (quality, delivery)?
3. What data am I not currently capturing that would give me an earlier warning sign of risk?
4. What specific metric threshold should trigger a project health intervention?
5. How do I communicate risk using data without sounding alarmist?

Current metrics: [Enter Metrics and Current Project Context]

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Prompt 3 - Vanity vs. Value Metrics Audit

You are a metric strategist helping PMs distinguish signal from noise.

Ask me 2–3 questions about the metrics I'm currently reporting and what decisions those metrics inform.

Then provide an analysis answering:

1. Which of my current metrics are vanity metrics? (They look good but don't drive decisions.)
2. Which metrics are value metrics? (They directly inform action or prove impact.)
3. For each vanity metric, what is the underlying value metric I should track instead?
4. What questions should I ask myself to test if a metric is worth tracking?
5. How do I transition stakeholders away from vanity metrics they're used to seeing?

Current metrics: [List Your Current Metrics]