AI Driven PM: S2E2 - What Do Project Managers Actually Do?

 So AI can write your status reports now.

It can take your meeting minutes. Update your project schedule. Do resource forecasting. Some tools even claim they can manage your risks and predict your delays.

Cool.

So what's left for us?

I'll tell you what's left: Everything that actually matters.

Here's the uncomfortable truth most PMs don't want to hear: Right now, you're probably spending about 60% of your time on coordination and busy work. That means only 40% of your job is focused on creating real value.

You can't avert a risk you didn't see coming if you're busy documenting what happened last week.

You can't clear roadblocks if you're stuck in your third status meeting of the day.

You can't anticipate needs or generate new ideas if you're staring at a screen updating who said what in yesterday's standup.

So if AI can handle status updates, meeting notes, risk logs, timeline adjustments, and all that other stuff—what's our actual job?

Let's talk about it.

We Make Dreams Come True (But What Does That Really Mean?)

I've said it before: Project managers are dream translators. But what does that actually look like in practice?

Here are the four things PMs do that AI will never replace:

1. Sense Making

We translate chaos into clarity for stakeholders.

Think about it: You've got twenty moving pieces, five competing priorities, three sponsors who all want different things, and a team trying to build something nobody's fully defined yet.

Your job is to be the centralized storyteller.

You take an abstract idea and turn it into concrete requirements. You hear a technical problem and frame it as a business value problem so a sponsor can actually make a decision.

AI can summarize. But it can't make sense of the why behind the chaos.

2. Decision Architecture

We design how decisions get made and by whom.

I don't know if anyone's ever said it that way before, but think about how often people try to force project managers to make decisions. That's not what we do.

Nowhere in the PMBOK does it say the project manager makes the decision.

What we do is:

• Analyze options
• Present trade-offs
• Go for decision
• Enforce the decision that was made

We don't own the decision. We own the process that gets to the right decision at the right time with the right people in the room.

AI can suggest options. But it can't read the room when a sponsor is about to overrule their entire leadership team because of a personal bias.

3. Energy Management

We keep teams motivated and aligned on what matters.

This isn't scope control. It's energy regulation.

Have you ever walked into a room where people are proactive, enjoying each other, having fun, being creative? You can feel that momentum. That's positive energy driving innovation.

I've also walked into rooms where you literally can't walk in because it's so tense. The air is frigid. People are angry. You can feel the toxicity.

We regulate that energy. We create the conditions where innovation can thrive.

AI can tell you morale is low. But it can't facilitate the conversation that gets the team back on track.

4. Conflict Resolution

We navigate competing priorities and personalities.

I once worked on a project where the CIO, CTO, CFO, and CEO all came to me separately and told me not to listen to the other three—just them.

You can't automate your way out of that.

AI can highlight the conflict. But it can't build the trust or influence the relationships that resolve it.

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So here's the mantra for this episode:

AI Handles the Transactional. PMs Handle the Transformational.

AI does the reports, tracking, transcripts, and data analysis.

PMs do the vision, relationships, judgment calls, and influence.

That's the augmentation model. And if you get that balance right, you're not just surviving the AI era—you're thriving in it.

Today's Focus: Use AI to Surface What Actually Needs Your Attention

If AI is going to free up 60% of your time, you need to spend that time on high-value work.

So today, I'm giving you three prompts designed to help you think like a strategist, not a secretary:

1. Project Health Diagnostic (your non-negotiable experiment)
2. Decision Architecture Mapper
3. Energy Audit

I ran all three live in ChatGPT and Claude. And honestly? Claude surprised me with how good its coaching was in this round.

Let me show you.

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Prompt 1: Project Health Diagnostic (The Non-Negotiable)

This is your weekly experiment. I want you to run this on a real project.

Here's the prompt:

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You are an experienced PMO director reviewing project health.

First, ask me 3–5 clarifying questions about the project's current state, team dynamics, and stakeholder concerns.

Then, using my answers, provide a diagnostic report that answers:

1. What are the top 3 risks that need PM attention right now?
2. Which stakeholder relationships need strengthening and why?
3. What decision is being avoided or delayed that's creating drag?
4. Where is the team's energy or morale most vulnerable?
5. What one action would have the highest impact on project momentum this week?

Current project context: [Enter Context Here]

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What I Tested It On

I used our fictional Social Wishing app project (the bucket-list social network from Episode 1).

Here's the context I gave it:

• Month 2 of development
• 5 engineers, 2 designers, 1 QA
• Sprint velocity dropped 20% in the last two sprints
• Daily standups feel perfunctory
• Sponsor keeps asking about launch date, but MVP scope isn't finalized
• One senior engineer just gave notice
• 4 months and $200K left in budget

Both ChatGPT and Claude asked clarifying questions:

ChatGPT asked:

• Who owns MVP scope decisions?
• Are stories entering sprint fully defined or being clarified mid-sprint?
• Has the sponsor agreed on success criteria for launch?

Claude asked:

• Is the MVP not finalized because of genuine disagreement or because no one's forcing the decision?
• Do you know why the senior engineer is leaving?
• When stand-ups feel perfunctory, what's actually happening?

Here's Where Claude Crushed It

ChatGPT gave me a solid diagnostic. Top risks: uncontrolled MVP expansion, architectural fragility, team disengagement. Good stuff.

But Claude gave me coaching.

Check out this section on stakeholder relationships:

"The sponsor—urgently, but carefully.

Core problem here is a shared reality gap. They're operating in a world where their feature ideas are refinements. You're operating in a world where those are scope additions with real cost.

This isn't malicious. Sponsors often genuinely don't see the downstream impact of small additions.

What you need is a direct, structured conversation that makes trade-offs visible: Here's what's in MVP. Here's what each addition costs in time and money. Here's what we must cut to accommodate it.

The goal isn't to win an argument. It's to get them into the same decision-making frame as the rest of the team."

That's the kind of coaching I'd give a junior PM.

It's not just identifying the problem. It's framing how to talk about it in a way that doesn't create defensiveness.

And then it ended with this:

"The good news is none of this is fatal yet. Month 2, budget intact, and a team that's disengaged but not yet departed is recoverable. The window is short, but it's open."

That's empathy. That's perspective. That's what a senior PMO director would say.

Both tools recommended the same highest-impact action: Run a 90-minute MVP reset session with the sponsor and core team.

And both gave me an agenda for it.

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Prompt 2: Decision Architecture Mapper

This one's for when decisions aren't getting made—or they're getting made by the wrong people.

Here's the prompt:

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You are a project governance consultant.

First, ask me 2–3 questions about how decisions are currently being made on this project.

Then help me design better decision architecture by answering:

1. What categories of decisions exist on this project? (strategic, tactical, technical, resource, scope)
2. For each category, who should make the decision, who should be consulted, and who just needs to be informed?
3. What decision rights are currently unclear or creating bottlenecks?
4. What decision-making process should I establish for the most critical category?

Project context: [Enter Context Here]

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What Happened

I told it:

• Sponsor requests features mid-sprint and goes directly to developers
• Senior engineer (who just left) had final say on architecture
• Sponsor is also acting as product owner

ChatGPT told me I had a "governance vacuum."

Claude built me a full RACI chart and told me:

"The critical shift here is that scope moves to you. With a fixed budget and no senior engineer buffer, ungoverned scope is an existential threat."

Then it gave me the script for the hardest conversation:

"This isn't designing the architecture. It's the single conversation where you tell the sponsor that scope authority is shifting to you."

Again—coaching, not just output.

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Prompt 3: Energy Audit

This one's for when something feels off with the team, but you can't quite articulate it.

Here's the prompt:

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You are a team dynamics coach working with project managers.

Ask me 3–4 questions about team morale, motivation, and alignment with project goals.

Then provide an analysis answering:

1. Where is team energy highest right now? (What's motivating them?)
2. Where is energy lowest? (What's draining them?)
3. What misalignment exists between team priorities and leadership priorities?
4. What story or narrative could I reinforce to re-energize and re-align the team?
5. What one conversation should I have with the team this week?

Team context: [Enter Context Here]

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What I Learned

Claude asked me:

• "When the team talks about Social Wishing, what specifically lights them up?"
• "How did the team react to the senior engineer's resignation?"
• "Outside of stand-ups, where's the real conversation actually happening?"

That last question is phenomenal. Is it Slack? Hallway conversations? Lunch groups?

Because if the real conversation isn't happening in your ceremonies, you've got a trust problem.

Claude's narrative recommendation:

"We're two months in, and we just learned something expensive but valuable. The project needed better architecture before it could move. We're not behind. We're resetting with clear rules. People still here chose to stay. Now we're going to build the thing we actually believe in—with scope we can defend—and ship something we're proud of."

I would use that exact language in a team meeting.

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Your Non-Negotiable Experiment This Week

Run the Project Health Diagnostic on one current project.

Use transcripts from your last few team meetings. Use emails. Use status reports. Give it real context.

Then act on at least one insight it surfaces.

Here's what I want you to notice:

1. Did AI surface something you were avoiding or hadn't articulated yet?
2. How much time did you save by having AI organize your thinking?
3. How much faster could you move if you had this clarity every week?

None of this is about status reports or meeting minutes.

This is about surfacing what actually needs your attention so you can spend your time on the transformational work that only you can do.

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The Takeaway

Project managers aren't project secretaries.

We're sense makers. Decision architects. Energy managers. Conflict navigators.

AI should handle the busy work so we can focus on the stuff that actually moves the needle.

So stop spending 60% of your week looking backwards.

Start spending 80% of your week looking forwards.

Because that's where dreams come true.

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If you would like to see the podcast live, check out this link: https://youtu.be/3sE6ynNyjIg

Next time: We're talking about the Halo Effect—why we keep promoting the wrong people into project management—and how AI can help you become the transformational leader your team actually needs.

Now go run that diagnostic. Your project is waiting.

 

AI Driven PM: S2E1 - Stop Asking AI to Write. Start Asking AI to Think.

How to Turn Fuzzy Sponsor Dreams Into Clear Project Vision in Under 10 Minutes

Here's the thing nobody tells you at your PMP certification: You're not really a project manager.

You're a dream translator.

Every app you've ever loved, every bridge you've crossed, every streaming service you've binged—all of it started as somebody's dream. Your job? Make that dream come true without burning out your people or blowing up the budget.

But somewhere between the kickoff meeting and Sprint 37, we forget about the dream. We get obsessed with the date. The budget. The feature list. The Gantt chart that nobody reads.

And that's where projects go sideways.

The Elephant in the Room

Let's talk about the fear that's keeping half of you up at night: Will AI replace project managers?

Short answer? No.

Long answer? AI will never replace project management. But here's what I tell my consulting clients: You will absolutely be replaced by a project manager who knows how to leverage AI.

That's not a threat. That's reality.

I just read that IBM—the same IBM that said they'd stop recruiting for entry-level jobs because AI would handle it—just reversed course. They're doubling down on human hiring. Why? Because AI is effective, but human augmentation is where the real value lives.

AI can write your status report. It can't read the room when your sponsor's dream is dying and nobody wants to say it out loud.

The Value Paradox: Where Project Managers Actually Add Value

I ask my clients this all the time: What percentage of your week do you spend looking backwards versus looking forwards?

Looking backwards is updating documents, running status meetings, writing meeting notes, chasing down timesheets. There's some value there, but not much. You're reporting on things that already happened.

Looking forwards is anticipating needs, clearing blockers, mitigating risks, framing decisions, finding efficiencies. That's where all the value is.

So here's the real question: How is AI impacting project management?

It's shifting that percentage. It's letting you spend 80% of your time looking forward instead of 20%.

That's not automation. That's amplification.

The Problem With How You're Prompting AI Right Now

Most people treat AI like an intern.

"Rewrite this." "Summarize that email." "Make this sound more professional."

Commands. Tasks. Output.

And you know what? AI will do it. It'll give you exactly what you asked for—which is usually mediocre.

But here's what I've learned after 30+ years and 150+ PMO implementations: The best project managers don't command. They coach.

And if you want AI to actually help you think—not just type—you need to treat it like a thinking partner, not a typing service.

That's where Socratic prompting comes in.

What Is Socratic Prompting? (And Why It Changes Everything)

Instead of telling AI what to do, you ask AI to ask you questions first.

Here's the pattern:

Give AI a role (You're an expert project manager)

Ask AI to ask YOU clarifying questions (First, ask me 3 questions to understand the dream)

Tell AI to answer specific questions (Then answer: What's the vision? What are the outcomes? What are the risks?)

Ask for reasons, options, and trade-offs (Not just a single output)

This does two things:

You get better output because AI understands the context

You think better because the questions force you to clarify your own thinking

So instead of "rewrite this charter," you say:

"First ask me three questions. Then answer: What's the dream story? How does it motivate the team? What business outcome does this support? What mantra will keep us aligned?"

See the difference?

One gives you a document. The other gives you clarity.

Let Me Show You: From Fuzzy Idea to First Backlog in Three Prompts

I'm going to walk you through three prompts I use all the time. I ran these live in both ChatGPT and Claude (always use multiple tools—you'll get different ideas).

The example? An app idea I've had in the back of my head for years called Social Wishing—where people post bucket list items and their friends help make them happen.

Vague? Yes. That's the point.

Prompt 1: Vision Clarifier (Fuzzy Idea → Clear Vision)

Here's the prompt to copy:

You are an expert project manager and business analyst. I will share a vague idea from a sponsor.

First, ask me up to 3 clarifying questions to better understand the dream behind this idea.

Then, using my answers, help me think through the idea by answering these questions:

What is the clear project vision in 2–3 sentences?

What specific, measurable outcomes would show this dream came true?

Who are the key beneficiaries and how does this idea help them?

What are the top 5 risks or unknowns we should explore early?

Vague idea from the sponsor: [Paste Idea Here]

What happened when I ran it:

ChatGPT asked me:

When you picture this succeeding in 5 years, what's changed in people's lives?

Is this mission-first or venture-backed?

Who do you want to serve first?

Claude gave me a survey-style interface with options to select. Both made me think differently about the idea.

Then they gave me measurable outcomes:

"60% of posted wishes receive at least one concrete offer within 7 days"

"40% of wishes marked complete within 6 months"

I didn't come up with those. AI did. In about 90 seconds.

That's the power of asking AI to think with you, not just for you.

Prompt 2: Charter to Dream Story (Vision → Team Motivation + Mantra)

Once I had clarity, I needed to turn that into something my team could rally behind. Not just executives. The people actually building it.

Here's the prompt:

You are a senior project manager. I will share a project charter.

First, ask me up to 3 clarifying questions about the project and audience.

Then format the charter so that it explicitly answers these questions for executives and the team:

What is the dream story? (What are we ultimately trying to make true in the world?)

How does this dream motivate the team? (Why would they care about building it?)

What is the business outcome this supports? (How does it move a key metric or strategy?)

Is there a mantra or quick saying we can use to keep everyone aligned on the goal?

Present your output as:

1 short "dream story" paragraph

3–5 bullet points on team motivation

3–5 bullet points on business outcomes

3–5 candidate mantras/slogans

Project charter: [Paste Charter Here]

What I got back:

ChatGPT gave me this dream story: "Social Wishing exists to turn idle scrolling into human progress. We're building a platform where college students and retirees use their existing social networks to bring meaningful goals to life through shared skills, time, and encouragement."

Claude gave me: "For too long, social media has trained us to watch each other's lives instead of participate in them. Social Wishing flips that script."

I would use that line. I didn't write it. AI gave it to me because I asked the right question.

Mantras?

"Dreams deserve action"

"Scroll less, live more"

"Wishes are better out loud"

Again—10 minutes in, and I've got a vision, a team motivation story, and three mantras I can use in every standup to keep people anchored.

Prompt 3: Dream to First Backlog (Vision → Prioritized Features)

Now I need to get my product owner and team moving. I need an initial backlog that delivers early value and builds momentum.

Here's the prompt:

You are a product owner. I'll share a project vision.

Ask me 2–3 clarifying questions about scope, constraints, and what "first value" means to us.

Then help me think through the first backlog by answering these questions:

What are the 3–5 value themes that organize this work?

What 10–15 initial backlog items best deliver early value in those themes?

Why did you choose these as "first" items instead of others?

Vision statement: [Paste Vision Here]

What happened:

Both tools asked me:

What does "first value" mean? Someone posts a wish, or a wish gets fulfilled?

What's the absolute core if you had to cut everything else?

Then they gave me value themes:

Trust & Identity

Wish Clarity & Commitment

The Wish Loop

And 10-15 backlog items with rationale:

"First, completion requires clarity. Without structured wishes and a definition of 'done,' fulfillment rates will stall."

"Second, trust must precede action. If users don't trust identity controls, they'll only post safe or shallow wishes."

That's not a feature list. That's strategic prioritization.

And I didn't have to think it all up myself. I just had to ask the right questions.

Your Non-Negotiable Experiment This Week

Here's what I want you to do:

Use the Vision Clarifier (Prompt 1) on one real, fuzzy sponsor idea this week.

Not a fake example. A real one.

Notice:

How does the sponsor react when you ask clarifying questions?

How much faster do you get to the "why" instead of arguing about the "what"?

How much easier is it to explain the project once the dream is clarified?

Because here's the truth: When you talk to sponsors about their dream—not their project—the connection grows stronger, faster.

And that's where the real value of project management lives.

The Takeaway

AI won't replace you. But a project manager who knows how to think with AI instead of just commanding it? That person is going to run circles around you.

So stop asking AI to write.

Start asking AI to think.

And remember: You're not here to fill out forms. You're here to make dreams come true.

Want the full walkthrough with live demos? Check out Episode 1 of Season 2 of AI Driven PM on YouTube or wherever you get your podcasts.  YouTube Link: https://youtu.be/_Sz-GR-t9qk

Now go make a dream come true.

 

— Rick A. Morris

The Quiet Failure Killing Your Transformation

Your teams are not failing in the sprint.  They're failing two sprints earlier.

Every time a sprint goes sideways, leadership asks: "What happened in execution?"

Wrong question.

Most delivery failures don't start in build. They start upstream, in the work you thought was ready but wasn't.

The Pattern Leaders Keep Missing

Here's what I've been seeing across every client engagement, every industry, every methodology: Organizations adopt fast. They execute slow. And the gap between the two is massive.

Look at these numbers:

Domain	Adoption Rate	Success/Scale Rate	The Gap
AI implementations (McKinsey)	88%	10%	78 points
AI production deployment (Stanford)	78% of businesses	Low deployment	~60-70 points
Automation initiatives (Stonebranch)	98%	Persistent challenges	50+ points
Agile transformations	80%+ adoption	10-30% effective	50-70 points

This isn't coincidence. This is readiness debt at scale.

What's Really Happening

The pattern looks like this across every organization I work with:

1. Adopt quickly because modernization pressure demands it
2. Skip readiness because upstream preparation takes time
3. Fail during execution as readiness debt compounds
4. Declare success anyway while quietly missing business outcomes

"We're doing Agile."
"We implemented AI."
"We completed the sprint."

But the business impact never materializes.

That's not execution failure. That's readiness failure.

Loud Failure vs. Quiet Failure

Most leaders can spot loud failure:

• Project cancelled
• Team disbanded
• Initiative shut down

But quiet failure? That's everywhere, and it's invisible.

Quiet failure looks like this:

• Initiative declared "successful" but delivers no measurable outcome
• Framework adopted but discipline lacking
• Teams busy but not effective
• Technical success but business failure

The organization doesn't admit failure. It redefines success downward. Motion replaces progress. And the gap between adoption and results keeps widening.

Why This Keeps Happening

Multiple independent sources—across AI, automation, Agile, and ERP transformations—confirm the same root cause:

Implementation failures stem from inadequate upstream preparation, not technology limitations.

Forty-six percent of AI initiatives fail between proof-of-concept and production. That's not a technology issue. That's a readiness gap between "works in theory" and "scales in practice."

Automation studies highlight orchestration and governance gaps. That's upstream ownership failure.

Agile struggles rarely stem from stand-ups or retrospectives. They stem from unclear backlog ownership, unfinished decisions, and poor readiness discipline.

Different domains. Same pattern.

No one owns readiness before execution begins.

The Leadership Discipline That Closes the Gap

This is exactly why I created the 2-1-0 Execution Mantra. It's not just for Agile. It applies to any execution methodology.

2 means two units of work ready ahead. Product owns this.

1 means one unit fully designed and decision-complete. Architecture or enablement owns this.

0 means zero blockers when execution begins. Delivery owns this.

If you're not 2 ahead, 1 ahead, and 0 blocked, you're transferring risk into execution.

And execution is the most expensive place to discover risk.

The Real Executive Question

Stop asking:

• "What's the velocity?"
• "Why did we miss the sprint?"
• "Can we commit to more?"

Start asking:

• "Is the work truly ready before we commit?"

Because that 78-point adoption-execution gap isn't a methodology problem. It's a readiness discipline problem.

Until leadership owns readiness upstream, execution will continue to absorb avoidable risk.

The Bottom Line

Your organization doesn't struggle because it adopts too slowly. It struggles because it executes before it's ready.

Adoption is easy. Execution is hard. Discipline is what separates the 88% who adopt from the 10% who scale.

Before your next portfolio review, ask yourself one question:

Why are we allowing unready work into execution?

That's where predictability begins.

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What's one thing your team committed to this sprint that wasn't truly ready? I'd love to hear your stories—hit me up in the comments or reach out directly.