While working for the BMW Williams F1 team from 1999 to 2001, I had some amazing experiences.

I went to several Grand Prix, including two at Silverstone. I also visited during testing days at various tracks, including Circuit de Catalunya, where I hung out in the pits.

But maybe the coolest were the driver days. For these, we invited our best Accenture clients to Brands Hatch. In addition to my driving around the track in various race cars, I got to sit in the passenger seat with Jenson Button one year and Juan Pablo Montoya the next. Each time, we were in a modified BMW M5.

The year Button drove me around, it was raining and the course was slick. He was still going at a fast pace and his hands never stopped moving to keep the car on the track. He seemed calm. I wished I were wearing Depends.

When Montoya took me around the track, it felt like he was pushing the car to its absolute limits. I couldn’t imagine going any faster without ending up in a ditch. But apparently, he thought there was plenty of room to go faster.

I asked him what the biggest difference was between an F1 car and a road car. I thought it might be the acceleration or downforce. But he told me, “It’s the brakes.”

He continued, saying the BMW he was driving was a beast that could accelerate well and grip the road relatively well. But the main reason he couldn’t push it to full throttle was that he knew the car couldn’t decelerate quickly enough.

An F1 car can go from 100 miles per hour to a full stop in about 2 seconds. Most sports cars, like a Porsche 911 or a BMW M5, take approximately 3.5 to 4 seconds, depending on conditions. Nearly twice as long.

Going fast depends on being able to slow down.

And the same is true in business.

Sometimes the key to moving faster isn’t a bigger engine. It’s better brakes.

Learn more about my keynote, Stability in an Uncertain World.

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I tend to approach it differently. I usually already know what I want to accomplish and I use AI to remove whatever is standing in the way.

In an earlier article, I talked about how I needed to cut my 60-minute Personality Poker speech down to a 12-minute experience for a showcase I was doing. I could have asked AI what to cut, but that would have meant letting AI decide what a good Stephen Shapiro speech should look like. I know what works. I know what’s important. I can remember audience reactions and questions they ask after an event.

So instead of asking AI to edit, I gave it a time-coded transcript from the full-length 60-minute version that I knew worked well. That became the baseline. Then I rehearsed the new version over and over, feeding each time-coded transcript (an SRT file) into AI and asking it to compare my performance against the baseline. Where was I spending too much time? Where was I speaking faster? What sections had expanded? What could I tighten without changing the experience? Where was I stepping on the punchlines?

On the day of the event, I delivered the experience in 11 minutes and 55 seconds. AI didn’t create the speech. It coached me on something I had already created. That’s an important distinction.

Another example started with an audience member’s question after I gave a Personality Poker speech. He asked me if I had looked at the best way to configure teams.

I’ve been researching this topic for two decades. I’ve looked at when teams outperform individuals, when individuals outperform teams, and how the complexity and ambiguity of work influences how we configure the people doing it. I had already written numerous articles on the research and had several chapters in You’re Not Playing with a Full Deck about how the nature of the work influences team configuration.

While flying back home, I started playing with the idea of how I could “automate” the decision-making process. Sitting in the airport lounge, I laid out the strategy. What did I want the system to do? What were the inputs? What were the outputs? What was the process?

On the plane, we had Wi-Fi, so I started developing the app with Claude Code while flying at 30,000 feet. By the time I landed, I had a working interactive application that let people explore the concepts and apply them to their own work. Ten years ago, that probably would have required finding a developer, explaining what I wanted, getting a proposal, spending thousands of dollars, waiting weeks or months, testing it, and making revisions. More likely, I simply wouldn’t have built it.

Now, instead of binge-watching Netflix on the plane, I build a fully functioning app.

The point is that the idea wasn’t created by AI. The research wasn’t created by AI. The intellectual property wasn’t created by AI. AI simply allowed me to go from idea to implementation in one afternoon.

My favorite example goes back even further. More than a decade ago, I envisioned taking my Personality Poker experience and creating a system that could “read” people’s hands. The idea was simple: take a photo of your five Personality Poker cards, upload the image, and then interpret what it meant. Who you are. Who you are not. Who you need. Your blind spots. And more.

More importantly, I wanted to aggregate all of that information in real time so I could provide insights into the composition of the teams and organization while on the stage, and then provide the data to the client after the event.

Twelve years ago, I spoke with a developer about this idea. Some of what I wanted wasn’t technically practical at the time. Other parts would have cost well into six figures. So the idea sat there. The idea didn’t suddenly become better twelve years later. My ability to get it done did.

Today, I’ve built what I call the “Full Deck IQ” system. It does all of the things I imagined years ago and quite a bit more. During a live event, hundreds of people can participate, receive individualized insights, and collectively create organizational data that I can use in real time.

Again, AI didn’t give me the idea. It made the idea possible.

These experiences and others have changed the way I think about AI.

I see three particularly powerful roles for it.

1. It can be a coach, helping us improve things we already do. For example, it helped me improve the timing and pacing of my speech.
2. It can be a builder, helping us turn our ideas, expertise, and intellectual property into things that previously required technical skills, significant money, or large teams. The configuration software I built on the plane is one example.
3. It can also be an amplifier, extending the value of what we do beyond a single interaction, meeting, workshop, or speech. My Full Deck IQ system does this well and has also enabled me to find new revenue opportunities.

But there is another side to this. As AI makes creation easier, the ability to create something becomes less differentiating. Judgment becomes more important. Anyone can generate an app. Anyone can create an assessment. Anyone can produce a framework that looks polished and impressive. That doesn’t mean it’s good.

You still need to know what problem is worth solving. You need experience, expertise, and a point of view. You need to know what you are trying to accomplish before you start building. And perhaps most importantly, you need the judgment to recognize when something AI produces looks impressive but isn’t actually useful. I’ve seen plenty of AI-generated output that looks fantastic on the surface but falls apart once you start examining what’s underneath.

That’s why I don’t think the most interesting question is, “What can AI create for me?” I think a much more interesting question is, “What have I always wanted to create that I couldn’t?”

Maybe it was too expensive. Maybe it required technical skills you didn’t have. Maybe it was too complicated or too time-consuming. Maybe you had the idea years ago but couldn’t justify the resources required to make it real.

Go back and look at those ideas again.

AI may not give you your next great idea. It may make one of your old great ideas possible.

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I ask this as someone who loves AI. I use it in nearly every aspect of my business, from coding and analysis to strategizing and research. It has changed how I work, and I suspect we are still in the very early stages of what it will eventually do. But that is also what got me thinking. If I have access to these capabilities, so do you. And increasingly, so do our competitors.

The models will keep getting better. The tools will get easier to use. What feels extraordinary today will eventually become expected. We’ve seen this movie before. Technologies start out as an advantage because only a few people have them. Then access spreads, prices fall, and eventually everybody has them. AI is just getting there very quickly.

So I don’t think the interesting question is, “Should we use AI?” Of course we should use it. The more interesting question is, “What still makes us different when everyone is using it?”

That question has led me to something I’m calling Human-Driven Innovation. It isn’t a rejection of AI. Actually, it is probably the opposite. It is about figuring out what people need to drive so that AI can be used where it has the greatest value.

The Problem with Everyone Getting Smarter

More than a decade ago, I wrote a book called Best Practices Are Stupid. The title was intentionally provocative, but the idea behind it was pretty straightforward. If you copy what everyone else is doing, you might improve, but you probably won’t become different.

There is nothing wrong with best practices when the goal is efficiency or consistency. But if every company studies the same competitors, hires the same consultants, follows the same benchmarks, and adopts the same practices, eventually everyone starts to look alike.

AI can magnify that problem. It is incredibly good at giving us access to what is already known. Ask for a strategy, an idea, an analysis, or a solution and you can get something useful in seconds. But your competitors can ask too.

That is why I don’t think AI decreases the importance of people. I think it increases the value of the things your people can make uniquely yours.

It’s Less About Having the Answer

For years, expertise was valuable partly because experts had answers other people didn’t have. Now answers are becoming cheap. If I can generate 100 possible solutions in a few seconds, the hard part is no longer producing solutions. The hard part is deciding which problem is actually worth solving.

If AI can identify dozens of opportunities, someone still has to decide which ones matter enough to pursue. And if AI can provide different viewpoints, we still need actual people with different perspectives to challenge one another, make choices, and do something together.

AI can help with all of this. I hope it does. But there are certain decisions I don’t think organizations should outsource.

Three Decisions

The first is where do we actually need to be different? Most companies spread innovation everywhere. I think that is a mistake. Some things simply need to work. Some things need to be efficient. And then there are a few things that actually influence why somebody chooses you instead of somebody else. Those are the places where being distinctive matters.

The second decision is what problem are we really trying to solve? I have spent years talking about the importance of the questions we ask. That becomes even more important when AI can give us an almost unlimited number of answers. A great answer to the wrong question is still the wrong answer.

The third decision is who needs to be involved? We tend to surround ourselves with people who think like we do because it is easier. Meetings move faster. There is less friction. But the person who sees the world differently may see something the rest of us are missing. Sometimes the person who drives you crazy is exactly the person you need.

Why I’m Bringing This Together Now

I’ve been working on these ideas for years, but mostly as separate pieces. PIVOTAL is about knowing where to differentiate. Invisible Solutions is about asking better questions. Personality Poker is about getting people who think differently to work together.

But the rise of AI forced me to look at these ideas through a different lens. As more of what we once considered uniquely valuable becomes available through technology, I started asking myself what people bring to the table that becomes even more important in an AI-driven world. That’s when I realized these weren’t three separate ideas. They were three parts of the same philosophy.

That is why I am bringing them together under the umbrella of Human-Driven Innovation.

I’m not suggesting we put humans on one side and AI on the other. That makes no sense to me. Use AI wherever it helps. Let it handle routine work, analyze information, challenge your thinking, and help you move faster.

But the faster the technology moves, the more intentional we need to be about what we want our people to own. Access to intelligence is becoming easier. Being distinctive isn’t.

That is the idea behind Human-Driven Innovation.

Innovate where humans differentiate.

Learn more at HumanDrivenInnovation.com

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Sometimes it does. Sometimes it does the opposite.

Recent research highlighted by Knowledge at Wharton found that teams performed as much as 60% better than the strongest individual on some tasks. But on others, teams performed three times worse.

That’s a huge difference. The question, then, isn’t whether teams outperform individuals. It’s: When do teams make us better, and when do they make us worse?

The answer appears to depend heavily on the nature of the work and the conditions under which people are asked to collaborate. And that closely mirrors something I’ve been teaching for years through Personality Poker: before deciding who should do the work, understand the environment in which the work will be done.

In other words, rules before roles.

Rules Before Roles

We tend to focus on putting the right people on the right tasks. But performance depends on something else that is often overlooked: the environment in which we ask people to do the work.

Think about two extremes. Some work is highly structured. There are clear rules, established processes, defined expectations, and perhaps even an objectively correct answer. Other work is much more open-ended. The destination may be unclear, the process needs to be invented along the way, and there may be many possible answers.

Those environments require very different ways of working.

This is one of the most interesting findings from the Wharton research. Teams tended to perform particularly well on problems where the correct answer could be recognized and verified. Under those conditions, adding people increased the likelihood that someone would discover the answer and that the group could recognize its validity.

But collaboration became less beneficial on open-ended tasks where there was no objectively verifiable best answer. Additional people could introduce more uncertainty, disagreement, and inefficiency rather than improving the result.

In other words, teamwork itself isn’t inherently good or bad. The environment changes the value of the team.

Red Cards vs. Black Cards

Years ago, a leadership program at Eckerd College in Florida conducted an exercise that demonstrated a similar principle. They tested people to see whether they liked working within rules or preferred breaking them.

In Personality Poker, red cards tend to prefer flexibility and doing things differently. Rules can feel limiting and restrictive. Black cards, on the other hand, tend to prefer structure and doing things better within rules.

You might therefore assume that the obvious approach would be to put the red cards in creative roles and the black cards in implementation roles. But the answer isn’t that simple.

Participants were divided into designers and builders. The design task was highly structured, with seven rules that had to be followed. The build task was almost completely unstructured.

One team followed the conventional wisdom: red cards designed and black cards built. Another mixed the two styles together in both roles. A third did what seemed like the opposite of what should make sense: black cards designed and red cards built.

Which combination was most effective?

The third team won by a mile.

The reason was that the environment mattered more than the label attached to the task. The design activity sounded creative, but it operated within a highly structured environment. The black cards thrived because the rules were clear. The build activity sounded like execution, but it was actually wide open. The red cards thrived because they had the freedom to figure things out as they went.

The lesson wasn’t that black cards are better designers or red cards are better builders. It was that our conventional categories of “creative people” and “execution people” can cause us to miss what really drives performance.

The task tells you what needs to be done. The rules tell you the conditions under which it will be done.

And those conditions can completely change who is best suited to the work.

The Personality Poker Connection

This is where the Wharton research and Personality Poker become particularly interesting together.

The Wharton researchers didn’t study Personality Poker, and their research shouldn’t be presented as scientific validation of the methodology itself. But their findings provide independent scientific support for a central principle behind it: You cannot determine the best way to organize people without considering the nature and conditions of the work.

Personality Poker gives leaders a practical language for doing exactly that.

The four suits represent four different orientations. Diamonds are creative and like ideas and experiences. Spades are analytical and like facts and data. Clubs plan the work and work the plan. Hearts focus on relationships and people.

But there’s another dimension that is equally important. The red suits, Diamonds and Hearts, tend to prefer more flexibility and freedom. The black suits, Spades and Clubs, tend to prefer greater clarity and structure.

This means simply matching people to tasks isn’t enough. A Diamond may be highly creative, but they can excel at execution if the usual constraints that limit their flexibility are removed. A Club may be known for execution, but put them in a brainstorming session with a well-defined process and they can be incredibly creative.

Same person. Same capabilities. Different rules. Different performance.

Stop Trying to Fix the Person

This has another important implication for leaders. When someone struggles, we often assume something is wrong with the person. Maybe they lack the necessary skill. Maybe they aren’t motivated. Maybe we gave them the wrong assignment.

Sometimes the problem is none of those things. They may simply be operating in an environment that fights against the way they naturally work.

I experienced this in my own business when I hired Sean, a black card with deep project management experience, to run a complicated client engagement. On paper, it was a perfect match. Project manager. Complex project. What could go wrong?

Quite a lot, as it turned out.

I gave Sean the kind of environment I personally love. I gave him freedom, stayed out of his way, and expected him to figure out the best approach. I thought I was empowering him. Instead, he struggled.

Eventually he told me what was missing. He needed clearer milestones, decision frameworks, expectations, and success criteria. I had given him a black-card role in a red-card environment.

Once I added the structure, his performance changed dramatically. I hadn’t changed the person or the assignment. I changed the rules.

More People Aren’t Always Better

There is another lesson here that connects directly with the Wharton findings.

One of the central principles of Personality Poker is that people who think differently from us can compensate for our blind spots. Cognitive diversity matters. But that doesn’t mean the solution to every problem is adding more people to the room.

In fact, in the Eckerd exercise, the team that mixed red and black cards in both roles performed the worst. Without the tools to understand and leverage their differences, their diversity created conflict instead of value.

That’s an important distinction. Diversity is potential. It isn’t automatically performance.

The Wharton research demonstrates something similar at the level of collaboration. Adding more minds to a problem can dramatically improve performance under the right conditions. Under the wrong conditions, the team can actually perform worse than an individual.

So the goal isn’t maximum collaboration, and it isn’t maximum diversity at every moment. The goal is the right people, working in the right way, under the right conditions, at the right time.

What It Really Means to Play with a Full Deck

This helps clarify what I mean when I tell organizations they need to “play with a full deck.”

It doesn’t mean every meeting needs an equal number of Diamonds, Spades, Clubs, and Hearts. It doesn’t mean everyone should participate in every decision. And it certainly doesn’t mean that teams are always superior to individuals.

It means recognizing that no single way of thinking or working is appropriate for every situation.

Sometimes you need the Diamonds expanding possibilities. Sometimes you need the Spades scrutinizing assumptions. Sometimes the Clubs need to stop the conversation and move everyone toward a decision. Sometimes the Hearts are essential because even the technically correct solution will fail if people don’t embrace it.

And sometimes the best thing you can do is let someone work alone.

The Wharton research gives us compelling evidence that team performance depends on the characteristics of the work and the conditions surrounding collaboration. Personality Poker adds a practical framework for understanding the people inside those conditions.

So before your next project, meeting, or important decision, don’t start by asking who should be on the team. Start with the rules.

How structured is the work? How ambiguous is the problem? Is there a verifiably correct answer, or are we exploring possibilities? Do we need collaboration at this stage, or would individuals working independently produce better results?

Only then should you move to the roles. Who thrives under these conditions? Which perspectives do we need? Who should lead? Who should contribute? And perhaps just as importantly, who doesn’t need to be involved right now?

Because playing with a full deck doesn’t mean playing every card.

It means knowing which cards to play, and creating the right conditions for them to perform at their best.

The post When Teams Make Us Worse appeared first on Stephen Shapiro.

And then you discover you’ve been reading them completely wrong.

That happened during a recent speech I gave on Personality Poker. I paired people up and asked them to do something that sounded simple: Figure out the other person’s personality style without looking at their cards.

Some of these people had worked together for years. After the exercise, I asked how they did, and one person immediately shouted, “Awful.”

That got a laugh, but it also exposed something important. Knowing someone is not the same as understanding them. We make assumptions based on the role they play, the work they do, and the version of themselves we happen to see.

And often, we get it wrong.

The Cards Are Usually Hidden

Personality Poker uses four suits to represent different ways people think and work. Spades are drawn to facts, data, and evidence. Clubs focus on plans, action, and results. Hearts pay attention to people and relationships. Diamonds are energized by ideas, possibilities, and what’s new.

When someone has five Personality Poker cards in front of them, understanding their preferences is relatively easy. But most of life doesn’t work that way.

Your customer doesn’t walk into a meeting holding five cards. Neither does the person you’re interviewing, your boss, or the employee you’re struggling to motivate. So how do you know what they need?

You read the tells.

In poker, a tell is a clue that gives you information about the hand another player might be holding. People have tells too, and they reveal them through the questions they ask, the words they use, what excites them, and what they pay attention to.

You might not see their cards. But if you know what to look for, you can often see their hand.

We’re Constantly Speaking Different Languages

Before introducing the tells, I gave the audience another challenge. I asked whether anyone spoke a language other than English as their first language, and one woman said Spanish.

I asked her to imagine that the rest of us were potential buyers and she needed to sell us something. There was only one condition: she had to make the entire sales pitch in Spanish.

She did. She was animated, enthusiastic, and persuasive. When she finished, I asked the audience how many were ready to buy.

People laughed. A few joked that they might buy because they liked her energy, but most of us had no idea what she had actually sold.

That was the point.

When someone doesn’t understand us, our instinct is often to explain it again. We add detail, speak more slowly, and sometimes practically shout. But speaking louder doesn’t help if you’re speaking the wrong language.

The same thing happens when we communicate with people who think differently from us.

Listen to the Questions

The strongest tells are often verbal. Pay attention to the questions people ask because those questions can reveal what matters to them.

A Spade tends to ask for evidence: “What’s the evidence?” “How do we know?” “What does the data show?”

A Club is more likely to focus on action and results: “What’s the plan?” “When will this be finished?” “How are we going to implement it?”

A Heart brings the conversation back to people: “Who needs to be involved?” “How will this affect the team?” “What does the customer think?”

And a Diamond starts exploring possibilities: “What if we tried this?” “Has anyone done this before?” “What else could we do?”

People rarely hide their style. They announce it. Repeatedly.

There can be physical clues too. Spades may become contained and analytical. Think of Rodin’s The Thinker. A skeptical Spade might sit with arms crossed while quietly evaluating everything being said.

Diamonds often have more movement and energy. They gesture, jump between ideas, and come alive when the conversation moves toward something new.

Clubs often show a focused intensity. One of my favorite Club tells is the karate chop: “We’re going to do this, then this, then this.”

Hearts tend to create connection. Some do it quietly through listening and steady attention, while others become highly animated when talking about people and relationships.

But this is where reading tells can become dangerous if we oversimplify it. Someone crossing their arms does not automatically make them a Spade. Maybe they’re cold.

A tell isn’t proof. It’s a clue. Look for patterns, especially in the language people use and the questions they repeatedly ask.

The Audience Made the Same Mistake We All Make

During that first exercise, people were trying to identify the suit of someone they knew, and the results were surprisingly poor. One reason quickly became obvious: we tend to confuse someone’s job with who they are.

A person may have learned how to behave in a certain role because the job requires it. That doesn’t necessarily mean the behavior is natural, and being good at something doesn’t mean you enjoy it.

I once worked with someone who was extremely good with spreadsheets. Everyone knew it, so whenever a new spreadsheet needed to be created, guess who got the assignment?

She did. Again and again.

The problem was that she hated spreadsheets. She could do the work, but it drained her. What energized her was creative work.

Her colleagues were reading her résumé rather than reading her.

That distinction matters. Capability isn’t preference. Just because you can play a card doesn’t mean you want it in your hand.

One Question Changed the Conversation

During the debrief, one participant mentioned a question his partner had asked: “What do you do when you’re not working?”

I loved that question because outside of work, some of our learned behaviors disappear. We aren’t performing a job, trying to satisfy a boss, or playing the role the organization expects us to play. Our natural preferences can become much easier to see.

Sometimes the person you know at work is only one version of that person.

Then we moved into the second round of the exercise. This time, instead of relying mainly on what they thought they already knew, participants became more curious.

They asked questions like, “What kind of projects do you most enjoy?” “What are you most proud of?” “When you start something new, what do you want to know first?” And, of course, “What do you enjoy doing when you’re not working?”

The second round went much better.

That may have been the biggest insight of the exercise. Reading tells is not about becoming better at labeling people. It is about becoming better at understanding them.

Why This Matters When You’re Trying to Persuade Someone

Once you start recognizing tells, communication changes. Imagine you’re selling an idea to a Spade. They may need evidence before they are willing to move forward.

A Club may want to know exactly how it will be implemented. A Heart may want to understand how people will be affected. A Diamond may become excited by what is new or possible.

Same idea. Four very different conversations.

I’m a Diamond. If you spend twenty minutes showing me spreadsheets, technical specifications, and statistical models, I might understand your argument perfectly well, but you probably haven’t captured my interest. Odds are, I will have fallen asleep halfway through.

Instead, tell me, “This is new. No one has tried this before. You could be one of the first.” Now I’m listening.

That isn’t manipulation. It is simply recognizing that effective communication is not about saying what you want to say. It is about saying it in a way the other person can hear.

The Real Skill Isn’t Reading People

The difference between the first and second rounds reinforced one of the most important lessons of the exercise. The real skill isn’t simply learning to recognize Spades, Clubs, Hearts, and Diamonds. It’s curiosity and learning to stop making assumptions.

Pay attention to the questions someone asks. Listen for the words they repeat and notice where their energy increases. Notice what they care about when nobody is telling them what they’re supposed to care about.

Then test your assumption. Because the biggest danger isn’t that we don’t understand other people. It’s that we’re convinced we already do.

In poker, you rarely get to see the other person’s cards. You watch, listen, look for patterns, and read the tells.

Maybe we should do the same with people.

P.S. It was correctly pointed out that the image has the suits in the wrong place. The photo used is a paid stock photo, not an AI generated one. For the purposes of the blog, I wanted to use the original image, not a doctored version. The correct format of the suits: Spades top left. Diamonds top right. Clubs bottom-left. Hearts bottom right. 

The post You’re Probably Misreading the People Around You appeared first on Stephen Shapiro.

I once worked with Rick, a city manager in Texas. When he chose his Personality Poker cards, he had a flush of Hearts: caring, people-focused, and motivational. But when his team gave him cards, they were all Clubs: disciplined, process-driven, a manager’s manager.

Their perception wasn’t wrong. But it didn’t match how Rick saw himself. Rick had adapted to what his job required and was showing up as a Club, even though that wasn’t what energized him. Once he recognized the disconnect, he shifted some of the process-heavy work to others and spent more time doing what came naturally to him.

The result? He reduced his stress, became more effective, and helped his team see a side of him they hadn’t been seeing.

Your intentions don’t determine how people experience you. Your behavior does.

But sometimes the gap reveals something positive that you don’t see in yourself.

I once did a Personality Poker gifting ceremony with a group of construction workers. One of these big, burly guys gave another the “self-sacrificing” card and explained how he was always the person who stepped up, took responsibility, and put himself on the line for everyone else.

The recipient’s eyes teared up. He thought of himself as a results guy. He had never recognized this quality in himself, but everyone else had.

That’s why one of my favorite parts of Personality Poker is “gifting.” It’s not really about giving someone a playing card. It’s about saying, “This is how I experience you.”

Sometimes that confirms what you already know. Sometimes it reveals something you’re projecting without realizing it. And sometimes someone sees a strength in you that you’ve never recognized in yourself.

Here’s something you can try today. Ask three people who know you well: “What’s one trait or strength you see in me that stands out?”

Don’t tell them how you see yourself first, and don’t defend or explain their answers. Just listen, then compare what they tell you with how you would describe yourself.

The gap is where things get interesting.

See Yourself Through Other People’s Eyes

Gifting is now built into Full Deck IQ. You create your Personality Poker hand based on how you see yourself, then invite other people to gift you cards based on how they experience you.

Now you can compare the two. What do you see that they don’t? What do they see that you don’t? And what might you want to do differently because of it?

Want to see yourself through the eyes of others? Full Deck IQ (FDIQ) lets you compare the hand you create for yourself with the cards others gift you. FDIQ is included with certification. Learn more about FDIQ.

Want to Bring Personality Poker to Others?

For years, I’ve been the one facilitating these kinds of conversations. Now, for the first time, I’m teaching others how to do it.

I’ve opened Personality Poker Facilitator Certification for trainers, consultants, facilitators, and internal leaders who want to bring Personality Poker to their own teams and clients. The first facilitators are already going through the program, and I’m offering the founding group certification for $995.

Learn about Personality Poker Certification

The post How Does the World See You? appeared first on Stephen Shapiro.

On one page, he connected ideas from several of my books into a surprisingly cohesive philosophy of innovation.

But one theme jumped out at me:

We don’t need more answers. We need better questions.

AI can generate answers in seconds. Best practices give us answers that worked for someone else. Experts have answers based on what worked in the past.

The real opportunity is to step back and ask:

Are we solving the right problem in the first place?

Pekka does a great job connecting that idea to differentiation, collaboration, blind spots, and even the people who drive us crazy.

Worth a read, and not just because he wrote nice things about me.

READ THE ARTICLE HERE

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