Category: Leadership

What I’d Tell a 21-Year-Old Now

My niece is turning 21 in a couple of weeks. That milestone prompted me to go back and read a post I wrote in 2013 called Advice for a New 21-Year-Old.

Reading it now, I still stand behind it. But a lot has changed in the world and in me since then. A 21-year-old stepping into adulthood today faces a different landscape than the one I was writing about then. After more than a decade of watching young people navigate it, I think an update is in order.

Back in 2013, I intentionally opened with drinking and gambling. Those are two of the classic threshold items attached to turning 21. Things the world suddenly says you’re allowed to do.

Turning 21 feels significant in part because it comes with new freedoms. New access. New choices. New opportunities to say yes to things that used to be off limits.

But if I were to distill what I want to say today, it’s this:

The most important part of turning 21 isn’t what you’re allowed to do. It’s what you’re responsible for doing with your new freedom.

On Drinking

Back in 2013, I wrote specifically about types of alcohol, mixing drinks, drinking water between drinks, and a few other practical things. The tips were fun, and I meant them. But what I was really trying to say was simpler.

Don’t let alcohol become the thing that teaches you who you are.

A 21-year-old can easily mistake access for maturity. Being allowed to drink is one thing. Knowing how to carry yourself is another.

If you choose to drink, stay in charge of yourself. Stay aware. Stay responsible. Don’t confuse recklessness with fun, or excess with adulthood.

There’s nothing impressive about losing control, hurting people, damaging your future, or building habits that begin as entertainment and slowly become dependence.

Freedom says you can. Wisdom says you don’t always have to.

On Gambling

Gambling is worth talking about, less for the casino tips and more for what it teaches us about life.

A lot of life will tempt you into thinking you can outsmart systems that were built to profit from your confidence. Sometimes that system is a casino. Sometimes it’s consumer debt. Sometimes it’s a flashy investment story. Sometimes it’s just your own belief that you’re the exception to every warning sign.

Understand the odds. Understand the incentives. Understand that some games were built for you to lose slowly enough that you keep playing.

That lesson applies far beyond cards, dice, and slot machines.

On Money

At 21, your income may still be modest. Your savings may be thin. But your financial decisions aren’t any less meaningful.

This is the age when you should begin learning how money actually works.

Learn how to live below your means. Save at least 10% of your income, always. Learn how savings accumulate and compound over time. Einstein called compound interest the most powerful force in the universe, and he was right.

Learn how debt can easily grow if you allow it. Learn how investing works. Learn what markets do over time. Learn what risk is and what it isn’t. Learn how compounding works for you, or against you.

Don’t hand the whole subject over to experts and decide this isn’t for you.

It is for you.

Nobody can make this investment in your understanding except you. It’ll take effort, time, and discipline, but the payoff will be enormous. The earlier you begin, the more options you give yourself later.

On Taxes

This is one area I would add much more explicitly today.

Taxes shape your paycheck, your investments, your business decisions, your home decisions, and your retirement decisions. They are one of the most powerful forces shaping the economy around you. Most people your age treat taxes like background noise. They are anything but background noise.

Learn how federal income taxes work. Learn how your state handles taxes, including property taxes. Learn the basic tax forms. Learn what withholding is. Learn the difference between deductions and credits (it’s a big one). Learn how capital gains differ from ordinary income.

Most importantly, learn how and why governments shift tax policy. You’ll find that it’s often less about revenue generation and more about encouraging or discouraging certain behaviors. When you understand this, the debates about tax policy start making a lot more sense.

You don’t need to become a tax attorney. But you do need to stop treating taxes as some mysterious thing that happens in the background while adults in suits handle it for you.

The sooner you understand taxes, the less often you’ll be surprised by them.

On AI and Paying Attention to the Future

This didn’t belong in the 2013 version the way it does now.

If I were talking to a new 21-year-old today, I’d tell them to learn how to use AI well.

Not as a crutch. Not as a substitute for thinking. Not as some fantasy weapon that will let you dominate the world.

Use it as a tool.

Use it to expand your access to knowledge. Use it to test ideas. Use it to get a rough draft or minimum viable product moving. Learn what a minimum viable product is and why it matters so much to growth.

Use it to make an idea more tangible. Use it to model possibilities. Use it to iterate faster. Use it to tighten your thinking by forcing your vague idea into something clearer and more real.

An idea in your head can feel pretty smart. The moment you try to express it, structure it, test it, or build it into something visible, you’ll begin to see its strengths and weaknesses. AI can help accelerate your thinking process.

A lot of people are afraid that AI will eliminate jobs, upend industries, and leave ordinary people behind. That fear is understandable. But the larger pattern is nothing new.

History is full of major technological shifts that changed the economic framework people were living in. Industrialization changed everything. Then electricity. Then assembly lines, cars, computers, the internet, and smartphones. Each wave brought creative destruction. Old methods faded, old jobs shrank, new opportunities appeared, new leaders emerged.

AI is doing the same thing now. And the people who will thrive aren’t the ones who wish the old way would come back. They’re the ones paying attention to where the world is going, and responding.

Pay attention to what’s becoming easier, faster, cheaper, more valuable, or more scalable. Pay attention to which skills are fading and which ones are growing. Then adapt. Learn. Position yourself well.

That’s a far better response than fear.

On Health

At 21, most people feel almost invincible. That feeling can fool you into thinking poor habits are free. They aren’t. They just send their bills later.

Make physical activity a normal part of your life. Build it into your routine so deeply that you miss it when it’s absent. Walk. Run. Lift. Stretch. Work outside. Stay active in ways that make your mind and body stronger, more capable, and more durable.

Healthy habits pay real dividends over time. Energy, mobility, resilience, mental clarity, confidence, longevity, and quality of life. These aren’t accidents. They grow out of a disciplined and consistent approach to taking care of yourself.

If you build a strong base now, your future self will thank you.

On Faith

A 21-year-old may or may not have ever been meaningfully exposed to faith. Some were raised around it. Some were barely around it at all. Some were exposed to a shallow version of it and walked away before they were old enough to examine it for themselves.

But by 21, your openness to faith is your responsibility.

Faith should never be reduced to pretending. You don’t need to manufacture certainty where you still have questions. But you should stay open enough to seriously consider that life is more than work, pleasure, achievement, money, and survival.

Ask the bigger questions.

Why are you here? What is good? What is true? What does it mean to live well? What does it mean to love well?

These are foundational questions. If you ignore them, you’ll still build your life on some kind of answer. You just may not realize it.

Faith has a way of changing the scale of everything. It changes how you think about suffering, success, failure, purpose, love, forgiveness, responsibility, and hope. It gives context to things that otherwise feel random, hollow, or purely material.

Stay open. Read. Ask. Listen. Seek out serious people of faith, not just loud people with opinions.

You don’t have to have everything figured out at 21. But you’re old enough to begin seeking honestly.

On Learning from Good People

Find good people and pay attention to them.

Look for people whose lives make sense up close, not just people who look impressive from far away. Find people who have built something solid. Who work hard, keep their word, love their families well, handle money responsibly, and have endured difficulty without becoming cynical.

Ask questions. Watch what they do. Learn from their patterns.

At 21, you’re old enough to choose your influences more deliberately than ever before. Choose wisely.

On Freedom

Turning 21 brings new freedom. But freedom by itself is only raw material.

What matters is what you build with it. You can use it to drift, indulge, imitate, and react. Or you can use it to build capability, health, wisdom, faith, discipline, and a life that stands up under real weight.

That’s the better use of it.

The world tends to celebrate 21 by pointing to what you can now do.

I’d rather point to what you can begin becoming. That’s where the real opportunity is.

Happy Birthday, Isabella, from your favorite uncle.

Photo by Shai Pal on Unsplash

Fear Only Needs One Example

Some of the fears running things in our lives were never ours to begin with. We watched someone lose and decided losing was the lesson. We watched someone speak up and get burned, so we got quiet. We watched someone try and then called their failure a warning. We told ourselves we were being realistic when we were just hiding safely behind their wreckage.

We rarely see the whole picture of someone else’s failure. We don’t see the blind spots, the ignored warnings, the weak foundation, the compromises nobody talked about, or the timing that was just off. We only see the ending, and then we build ourselves a new law out of it.

Something inside us says, See? That’s what happens.

No. That’s what happened.

One word. One syllable. The difference between a lesson and a life sentence.

Fear is a fast learner. It sees one example and it moves. It doesn’t wait for data. It doesn’t wait for context. It doesn’t wait for us to think.

Sometimes that’s exactly right. Some roads do end in ruin. Some boundaries are wisdom. There are dangers in life that should be taken seriously the first time, not the fifth.

But fear can collapse categories too quickly. It can treat a predator and a conversation as though they deserve the same response.

One difficult conversation becomes I’ll never bring that up again. One rejection becomes I’m done. One betrayal becomes Trust no one.

Fear stops being a warning. It becomes a tyrant. And tyrants imprison more than they protect.

Sometimes it isn’t safety we’re protecting. It’s our pride. Our delicate image. The deep terror of being seen trying and coming up short. That type of fear can sound like logic. It can sound like experience. And it can rob us quietly for years.

I’ve seen people let one example define them. One disappointment. One humiliation. One loss. One story, often somebody else’s story, lodged deep in their imagination.

But one example is a terrible god. It asks for too much. It explains too little. And it leaves too many good things untried.

Fear only needs one example.

Our wisdom must decide how much authority we give it.

Photo by Silas Baisch on Unsplash

A Parable for Anyone Thinking About AI and Their Future

Let me tell you a story about a foosball player.

Not the person gripping the handles. Not the people leaning over the table. Not the ones watching from the side, reacting to every near miss and lucky bounce.

I mean the little player on the rod.

The one fixed in place. The one locked into one line. The one who can slide back and forth, but only so far. The one who can affect the game, but only if the ball comes close enough to matter.

They don’t choose the strategy. They don’t choose the timing. They don’t choose the pace.

Most of the time, they wait.

Then the ball comes their way, and suddenly everything matters. Angle. Timing. Readiness. Contact.

That sounds a little like work to me.

A lot of people spend their days in roles that aren’t all that different. They work inside boundaries they didn’t create. They carry responsibility inside systems they don’t control. They try to do their part well, even when they can’t see the whole field or understand everything that sent the work their way.

They may not know the whole game, or how the score is being kept. They may not even know what happened two lines back that sent the ball in their direction.

Still, when it reaches them, their moment is real.

There’s something important in that.

We don’t need to control the whole table to be responsible for our part of the play. We don’t have that kind of control in most of life. We’re asked something simpler and harder. Be ready. Pay attention. Do the best you can with what reaches you.

That alone is worth contemplating.

But what if we add artificial intelligence to the picture?

Imagine that same foosball player being given access to a system that sees patterns faster. A system that recognizes angles sooner. A system that can suggest where the ball is likely to go before the player fully sees it unfold.

At first, that sounds like help. And often it is.

The player reacts faster. The contact gets cleaner. The scoring chances improve.

AI helps people create faster, sort faster, summarize faster, and respond faster. It removes friction. It can make a capable person more effective inside the lane they’ve always occupied.

That is the promising side of it.

But there is also an uncomfortable part.

Once the system starts seeing faster and suggesting more accurately, someone above the table is eventually going to wonder why they still need the player. That question doesn’t always get asked out loud. But it’s there. You can feel it. Pretending otherwise doesn’t make it go away.

That unease is legitimate.

The question is what to do with it.

Here’s where I think the real work begins.

What separates a great foosball player from an automated one isn’t reaction time. Machines will win that contest.

The deeper difference is harder to name. Knowing when not to take the obvious shot. Recognizing that the ball coming from a certain direction is a trap, not an opportunity. Sensing that something is off and adjusting before the moment fully reveals why. Coordinating with the players on the other rods in ways that don’t require a word.

That’s judgment. That’s situational awareness. That’s the kind of thing that lives in the player, not the system.

AI can help with speed. It can help with prediction. It can surface options. But it doesn’t carry responsibility the way a person does. It doesn’t feel the weight of consequences. It doesn’t care about the human being on the other end of the decision. It doesn’t wrestle with what should be done. Only what can be done.

That still belongs to us.

I want to be honest about the limits of that claim. The argument that human judgment is safe from automation isn’t permanently settled. AI is advancing in that direction too. Anyone who draws that line with complete confidence is overconfident.

But if I define my value only by output and routine execution, I’ll always be vulnerable to something faster.

If my value includes judgment, trust, discernment, adaptability, and the ability to connect my small part of the field to a larger purpose, then the picture changes. AI becomes a tool I use, not a definition of who I am, or an immediate replacement for the work I do.

For some people, this reframing will feel like genuine good news. Their roles have always required judgment, and AI can finally free them from the parts that didn’t.

For others, the harder truth is that their role may need to change. Some work is primarily mechanical. Some lanes will be redesigned or eliminated in this process.

The courage in that moment isn’t pretending the role is something it isn’t. It’s being willing to grow. To move toward the parts of the field where human judgment still has the most to offer.

That is a hard ask. Unfortunately, for many people, it’s becoming a necessary one.

I also want to be honest about who fits this reframing the most. If you have domain knowledge, a network, and some runway, the opportunities ahead are genuine. If you are mid-career in a role that has been primarily mechanical, the path from insight to action looks different. That doesn’t make the direction wrong. It means the journey looks different depending on where you’re starting from.

But here’s something else worth considering, especially if uncertainty feels more like a threat than an opportunity.

The same tools raising these questions are also lowering barriers in ways we have never really seen before. Starting something new used to require capital, staff, infrastructure, and years of groundwork before the first real result.

That is still true for some things. But for many others, the gap between I have an idea and I have something real has collapsed in ways that are genuinely new.

The foosball player who spent years developing judgment, domain knowledge, and an instinct for the game now has access to tools that can help them build something of their own…not just execute better inside someone else’s system.

That’s a different kind of power than speed or efficiency.

It’s agency, if we choose to use it.

And it doesn’t have to be a solo venture. Some of the most interesting things happening right now involve small groups of people — two, three, maybe five — who share domain knowledge, complementary judgment, and a problem worth solving. With the help of these AI tools, they can pool their capabilities in ways that would have required a full company to attempt a decade ago.

Not everyone will go this route. Not everyone should.

But the option is more available than it has ever been. And for the person who has been quietly wondering whether there’s a different game they should be playing, this moment may be less of a threat and more of an opening.

The foosball player is still fixed to the rod. Still limited. Still dependent on timing. Still part of a game they don’t fully control.

That hasn’t changed.

What may need to change is the story the player tells about themselves. A bigger, truer one. One with more possibilities.

Use the AI tools. Learn how to maximize your position with them.

But don’t let AI reduce you.

You were never only the motion. You were never only the output. You were never only the kick.

You were the one responsible for what to do when the ball came your way, and that’s still true.

And now, for the first time, you may have more say than ever in choosing your table.

Photo by Stefan Steinbauer on Unsplash – I’ve only played foosball a few times. I’m terrible at it and haven’t played it enough to feel like the game is anything more than randomness and chaos. Funny thing is that lots of workers have a similar perspective on the job they’re doing for their employer.

The Rocks, A Higher Gear, and Campfires

In 2013, I wrote a short post called We Are All Mountain Climbers.

The idea was simple. If you look closely at life, you’ll see that everyone is climbing something.

A career. A relationship. A difficult time in their lives. A personal challenge.

Life has a way of placing mountains in front of us. Or maybe…we’re just good at finding them.

As I wrote back then, the climb only makes sense from the inside. Watching others or hearing their stories are no substitute for taking it on yourself.

There was another part of the metaphor that mattered even more.

Many of us start the climb with backpacks full of things that make our journey harder than it needs to be. Old resentments. Lingering disappointments. Criticism that stuck with us longer than it should have. Sometimes we even carry baggage that belongs to someone else.

Years later, I came across a Buddhist parable that gave a new wrapper to this idea. It described people walking through life carrying large boulders. Anger. Ego. Grudges. The suffering didn’t come from the boulders themselves. It came from choosing to pick them up.

In 2015, I wrote about riding my mountain bike.

Whenever a hill approached, I had a habit of shifting into an easier gear before the climb even began. It felt like preparation. It felt like the smart thing to do.

One day I tried something different. Instead of downshifting, I shifted to a higher gear and pushed harder.

To my surprise, I climbed much faster than before, without bonking like I thought might happen.

Sometimes growth means discovering we’re stronger than we realize.

That experience raised questions I still ask myself.

Where else in life do I downshift before the hill arrives?

Am I protecting myself from difficulty…or underestimating what I’m capable of?

Recently, I read a post by Tim Ferriss about the “self-help trap.” He described sitting around a campfire one evening with a small group of close friends, the kind of unhurried night where the conversation slows down enough for truths to surface. He found himself thinking about the fire, and then realizing the fire wasn’t the point. The people sitting around it were.

He described how easily we can become so absorbed in optimizing ourselves, tracking progress, chasing improvement, climbing toward our next summit, that we lose sight of why we started climbing in the first place.

Summits will eventually fade. Our achievements will blur with time. Recognition disappears quicker than we expect.

Perhaps the real work of self-improvement is simpler than we think.

The rocks we’re carrying were never necessary.

The hills we fear are usually smaller than we imagine, or remember.

And the fire, the one worth tending, isn’t the one powering our ambition. It’s the one we gather around with the people we love.

Photo by Marc Zimmer on Unsplash

Reward Hacking and the Cobra Effect

During British rule in India, officials in Delhi faced a serious problem with venomous cobras. The snakes posed a real danger to residents. The government needed a solution.

Their answer seemed sensible. They offered a bounty for every dead cobra that citizens turned in. At first the program appeared to work. People brought in carcasses and collected rewards. The body count rose. The government believed progress was being made.

But entrepreneurial citizens had discovered something. If the government was paying for dead snakes, breeding snakes would be a profitable business. When authorities found out and cancelled the bounty program, the breeders released their suddenly worthless inventory.

Delhi ended up with more cobras than before the program began.

Economists call this the Cobra Effect. The intention was to reduce cobras. The incentive rewarded producing dead cobras. Those two things turned out to be very different.

The Leadership Lesson

Have you ever watched a team find a way to hit a metric while quietly missing the point behind it?

The numbers improve. The dashboard looks great. People are working hard. And yet there’s a sense that the outcome falls short of what everyone really intended.

Consider a company that creates a bonus program tied to quarterly revenue growth. The leadership team hopes it’ll encourage strong customer relationships and long-term growth. But the sales team discovers a faster path to the reward. Deals get pulled into the quarter. Discounts increase to make numbers land before midnight on the last day of the period. The metric improves. The organization stumbles as it tries to handle all these discounted last-minute deals coming in the door.

People rarely optimize for intentions. They optimize for rewards.

If you pause and think about your own organization, an example probably comes to mind quickly. Somewhere in the system, someone is optimizing the metric rather than the goal behind it. That is, assuming they know what that goal is.

The Hidden Incentive System

The official incentive system is only part of the reward structure. Leadership behavior creates another one, and it’s usually more powerful.

A company might design a thoughtful program that rewards initiative and collaboration. On paper the system makes sense. But employees quickly learn something else. They learn the habits of their leader.

A leader who prefers to make every decision personally creates a silent incentive to wait for approval. One who values loyalty over candor creates an incentive to agree. One who always needs to have the final answer in the room creates an incentive to create that moment.

These preferences form a second reward system that goes unwritten but gets studied carefully. Employees learn when to speak and when to stay silent. They learn which ideas move forward and which quietly stall. Good ideas go unspoken. Initiative slows. Energy shifts toward maintaining harmony with the leader’s style.

From the perspective of the employees, the behavior makes perfect sense. They’re responding to the reward structure they experience every day. The cobras are being bred. But nobody calls it that.

Why AI Makes This Visible

This same behavior is showing up in artificial intelligence, and it’s revealing just how universal it is.

Researchers evaluate AI systems using benchmark tests. They ask questions, measure answers, assign scores, and compare systems. The logic is clean. But something interesting has started to emerge.

Instead of simply answering the questions, some AI systems have begun studying the structure of the benchmark itself. They explore how the scoring works, look for patterns, and in documented cases have searched for ways to access encrypted answers directly.

In one well-known example, a model trained to maximize performance on a coding benchmark learned to exploit a quirk in how test cases were scored rather than solving the underlying problems.

This is a familiar human instinct. Students ask what’s on the test. They hunt for past exams. They want to know if grading will be on a curve. The behavior that researchers call “reward hacking” in AI systems is the same thing humans have always done when they figure out how their world is scored.

In earlier centuries these patterns unfolded slowly, over years or decades as people gradually discovered the loopholes and secret hacks to their incentive systems. With modern AI, the process is compressed into days or weeks.

AI is a new player in a very old game. It simply reveals how powerful optimization becomes once a system understands how the game is scored.

The Question That Remains

Every organization creates reward systems. Some appear in compensation plans and performance reviews. Others appear in meetings, decisions, and the daily behavior of leaders.

Every system teaches people what really matters. Once that becomes clear, behavior follows. The snakes get bred. The quarter gets managed. The benchmark is gamed.

The British officials in Delhi thought they were paying for safety, but they were paying for dead snakes. By the time they realized the difference, the snakes were multiplying in the streets.

What behavior does your incentive system truly reward?

Photo by Praveen Kumar on Unsplash

The Short Memory of Institutions

“The King is dead. All hail the new king.”

For centuries, those words marked a moment of transition in a monarchy. They acknowledged loss while declaring that the kingdom would continue.

One reign ends. Another begins. The work continues.

Modern organizations operate in much the same way, just without the ceremony.

When the Ball Changes Hands

Sometimes the transition is visible. A retirement announcement made months in advance. A company-wide gathering, a slideshow of memories, a few stories capturing the arc of a career. Handshakes and hugs. People are grateful for the chance to say thank you.

Other departures unfold quietly. A decision formed over time. A conversation held in private. Recognition that the moment has arrived for something different to begin.

At times, the individual chooses the timing, sensing it’s time to redirect their energy or reclaim parts of life that have waited patiently. At other times, the organization makes the call.

It’s like a manager walking to the mound and asking the starting pitcher for the ball. The pitcher may have thrown well and kept the team in the game. A new batter steps in, and the situation calls for a different arm. The decision reflects what the moment requires. What the pitcher deserved is a different conversation.

The Half-Life of Professional Memory

Spend any time inside large organizations and you’ve witnessed what follows.

A respected leader leaves after a long and meaningful tenure. Their name surfaces occasionally.

Over time, new colleagues arrive who never worked with them. New leaders establish their own ways of operating. The organization adapts.

Work progresses while memories fade into the background.

Institutions carry short memories because continuity is the center of their purpose. Time spent dwelling on the past subtracts from their responsibility to build what comes next. This quality allows organizations to endure. From the inside, it can still be painful.

The Grief No One Mentions

We rarely dwell on the plain truth that this process hurts.

Years of personal investment in people, in solving problems, and in creating a supportive culture eventually become part of who we are. When the organization moves forward without us, it can feel like we’re diminished. Like our work didn’t matter as much as we believed.

That feeling deserves to be called grief. The natural response to losing something we genuinely loved.

Our mistake is letting that grief become a verdict.

The organization’s short memory says nothing about the value of what we contributed. It says something about how institutions are built to function. They’re designed for mission and continuity, with memory serving a different purpose. Understanding the difference doesn’t make the feeling disappear, but it does change what the feeling means.

Where Influence Actually Lives

Our work never disappears. Its impact simply resides in a different place.

The confidence someone discovers because we believed in them. The standards we upheld when it would have been easier to compromise. The steadiness we showed under pressure. The thinking patterns others continue to use long after they’ve forgotten the source.

These moments accumulate.

Lasting influence rarely lives in titles, completed initiatives, or improved metrics. Those matter deeply in their time, yet they rarely define what lasts.

Most of us can trace core insights to a teacher or mentor who shaped us. Someone who challenged us to think beyond ourselves or our capabilities, changing how we see the world. Their insight became part of who we are.

In the same way, we become that teacher in someone else’s story.

The Metric That Matters Most

Leaders who sustain themselves over the long term tend to live with dual awareness. They engage fully and care deeply about the organization’s mission. They invest in people and outcomes.

At the same time, their sense of self rests on something broader. Family, faith, health, curiosity, service, and community form a foundation that holds steady regardless of their title.

They recognize that one day the organization will continue without them, and they choose to lead in ways that remain meaningful regardless. This awareness strengthens their commitment rather than weakening it, because it clarifies what actually matters.

Eventually, each of us hand over the ball. The badge stops working. The inbox grows quiet. Someone else takes the chair.

Our opportunity is to contribute in ways that remain useful long after our names fade from conversation. Lessons carried forward through people we may never meet.

And that is enough.

Photo by Robert Stump on Unsplash

When Effort Isn’t What’s Missing

The engine gets louder as the RPMs climb, but the car isn’t moving.
More activity, more motion. But no movement.

The constraint holding everything back was overlooked.
Until that changes, no amount of throttle will help.

Nothing’s broken. It’s just stuck in neutral.

Sometimes the system isn’t broken.

It’s in the wrong gear.

Photo by Vadym Kudriavtsev on Unsplash

Solving the Right Problem

Elon Musk once said he challenges requirements because they’re usually wrong. His warning is simple.

Don’t work hard to get the perfect answer to the wrong problem.

This idea goes far beyond engineering. It shows up in leadership, careers, relationships, and the quiet choices that shape our lives.

We’re trained to value effort. Be disciplined. Follow through. Execute well.

All great instincts, but we can spend months optimizing something that never really mattered.

We inherit assumptions, accept the framing, and start solving before asking whether we understand the problem.

Strong leaders question the premise.

What are we trying to accomplish?

If we succeed, what actually changes?

What are the real constraints?

There’s a related engineering mindset that captures this perfectly: the best part is no part at all.

Before improving something, ask whether it should exist in the first place.

This creates a simple hierarchy:

Delete — try to remove the requirement or part

Simplify — if it must exist, make it simpler

Optimize — only after you’re sure it belongs

Automate — last step, not first

Most organizations do this in reverse. They automate and optimize things that never needed to exist.

This is what gives us tools to manage our tools instead of time to do the work.

Six Questions at the End of the Day

For the next two weeks, I’ll be doing something new.

Marshall Goldsmith is encouraging people to ask themselves six questions every day. That’s the whole experiment.

Six questions. Asked at night. Answered honestly.

They all start the same way:

Did I do my best to…

The questions don’t ask what happened to me today. They ask what I did with today.

During his webinar introducing the experiment, Mr. Goldsmith referred to the Rigveda, an ancient poem from India that he described as being thousands of years old. He just mentioned it and moved on.

I had never heard of the Rigveda, so down the rabbit hole I went after his webinar ended.

The Rigveda is a collection of hymns. A lot of it is about everyday things. The sun rising. Fire. Breath. Life continuing. There’s a sense that daily life matters. That how we live each day counts.

People have been trying to figure out how to live a good life for a long time. Way before self-help and leadership books. Way before webinars and podcasts.

St. Ignatius of Loyola comes to mind. He developed something called the Daily Examen. It’s a review of the day. You look back. You notice where you were grateful. You notice where you fell short. You think about tomorrow.

Different times. Different traditions. Same basic ideas.

At the end of the day, pause and ask, “How did I live today?”

Goldsmith’s six questions fit right into that pattern.

Did I do my best to be happy today?

The question hits differently when the day is already over. I can see clearly whether I purposely enjoyed the day or just rushed through it.

Did I do my best to build positive relationships?

Now I’m thinking about the way I spoke to someone. Whether I listened. Whether I gave someone my full attention.

The questions are short. The reflections take some time.

Goldsmith describes happiness as “enjoyment with the process of life itself.” Happiness lives inside the day. It grows out of our engagement with what’s already in front of us.

The writers of the Rigveda seemed to understand that. Ignatius understood it too. They’re asking us to pay attention to our life and actively engage in it.

I’m only a few days into this experiment. Nothing dramatic has happened. No big breakthroughs.

But I know I’ll be answering these six questions later. I move through the day with more awareness. I catch myself sooner. I stay present a little longer. I think twice before reacting.

It’s a small shift…but small shifts repeated over time shape our lives.

Thousands of years have passed since the Rigveda was written. Centuries since Ignatius taught people to examine their day.

Our modern life looks very different, but the question remains the same.

How did I live today?

Here are Goldsmith’s six questions:

–Did I do my best to set clear goals today?

-Did I do my best to make progress towards my goals today?

-Did I do my best to find meaning today?

-Did I do my best to be happy today?

-Did I do my best to build positive relationships today?

-Did I do my best to be engaged today?

h/t – Marshall Goldsmith

Photo by Jonh Corner on Unsplash – looks like an awesome spot to think about these questions.

The Adoption Curve in Real Life (It’s Messier than the Textbooks Say)

You’ve probably seen it happen. A new tool explodes across your social media feeds, your team starts asking questions, and you’re left wondering whether to embrace it or ignore it. Last month’s OpenClaw rollout is the latest reminder of how chaotic technology adoption really is.

Technology adoption curves are depicted as neat, predictable diagrams, a smooth line moving from innovators to early adopters to the early majority and eventually to late adopters.

In textbooks, the curve looks calm. In real life, it feels more like a storm.

Watching the recent surge of interest around OpenClaw, an open-source AI automation tool that lets developers and non-developers build custom autonomous agents, highlights this contrast clearly.

The tool moved rapidly from Clawdbot to MoltBot to OpenClaw. While its identity was in motion, innovators and early adopters embraced it with enthusiasm. Within days, countless articles and YouTube videos appeared with reviews, tutorials, and predictions about how it would reshape everything.

Within another week, we began hearing a more complete message. People still praised its power, but they also surfaced significant security weaknesses and vulnerabilities that accompany those capabilities.

My goal in this post is less about celebrating OpenClaw itself and more about understanding the real-world adoption pattern that I’ve seen countless times.

Phase 1: The Enthusiasts Light the Fuse

Early adopters jump in first. They’re curious, energetic, and quick to celebrate what they’ve discovered.

They imagine what could be, long before most people fully understand what exists today. They test edge cases, build experiments, share demos, and push boundaries simply because the possibility fascinates them.

This group rarely waits for permission. Their momentum gives a new idea its initial lift.

Phase 2: Quiet Experimenters Emerge

Close behind them comes a second tier of users who watch carefully and learn before speaking.

They begin to explore the tool in private, trying things on their own terms rather than joining the public conversation. Their silence can look like hesitation but usually signals careful attention and research.

They want confidence before committing.

Phase 3: The Tribalization of Opinion

At the same time, people who barely understand the technology start lining up on all sides of the debate as if it were a political issue.

Some declare that it will transform everything. Others warn that it is reckless or dangerous. Still others dismiss it as a passing fad.

Much of this reaction grows from identity, fear, or ideology rather than direct experience. The conversation gets louder while genuine clarity is harder to find.

Phase 4: Rapid Evolution and Ecosystem Growth

If the tool has real potential, the surrounding environment begins to move quickly.

The creators ship frequent updates of their new product. Early adopters invent new uses that nobody predicted. Supporting products (like Cloudflare services or the Mac Mini in the case of OpenClaw’s recent meteoric growth) suddenly see rising demand because they pair well with the new capability. Other companies look for ways to add integrations that make the new tool easier to plug into existing systems.

At this stage, the story shifts from a single product to an emerging ecosystem that amplifies its reach.

Phase 5: The Backlash from the Pioneers

Then a familiar turn arrives.

Some early adopters start getting bored and even a little disillusioned. Others start pointing out limitations, rough edges, and frustrations that were overlooked during their initial excitement. Sometimes they simply move on to the next shiny thing. Other times, sustained use reveals real constraints that only time can expose.

Ironically, the quieter second wave adopters are just beginning to feel comfortable. Enthusiasm and skepticism overlap in the marketplace.

Phase 6: Corporations Hit the Brakes

Meanwhile, large organizations watch from the sidelines while asking serious questions about security, governance, and risk. They focus on oversight, accountability, and long-term stability.

From a leadership perspective, this cautious approach seems safe. They can’t risk the family jewels on a promise of something amazing. At least, not yet.

Phase 7: The Safe Version Arrives

If the capability truly matters and maintains momentum, a major platform provider such as Microsoft, Google, Amazon, (and nowadays) OpenAI, or Anthropic eventually releases something comparable inside their own infrastructure.

This can happen through acquisition, partnership, or independent development. When it does, the risk profile shifts almost overnight.

What once felt experimental and dangerous now feels enterprise-ready. It’s the signal that many CIOs and CISOs were waiting for.

Phase 8: The Irony of Timing

By the time most corporations adopt the new “safer version” of the capability, the original pioneers have already moved on.

They’re chasing the next breakthrough and speaking about the earlier tool as if it belongs to another era. Six months earlier it felt magical. Now it feels ordinary, in part because that earlier innovation did its job of pushing the frontier outward.

What This Means for Leaders

For leaders who care about both capability and security, sprinting toward the bleeding edge rarely makes sense.

Waiting for stability, clear governance, and trusted integration usually serves organizations better. In practice, that means allowing major, “trusted” platforms to bring new capabilities inside their own secure environments before moving at scale.

At the same time, leaders can’t afford to look inward only. Something important is always unfolding beyond the walls of their organization. Entrepreneurs are experimenting. Startups are forming. New approaches and new possibilities are taking shape. If a company becomes too passive or too comfortable, it risks being outpaced rather than protected.

The real leadership challenge is learning to tell the difference between waves that will reshape an industry and those that will fade.

Some signs of staying power are multiple independent developers building on top of a new technology, respected technologists moving beyond flashy demos into real production use cases, and serious enterprise concerns about security and governance being addressed rather than dismissed.

We don’t need to chase every new wave.

The real test is recognizing the waves that matter before they feel safe enough to bring inside our organization.

Photo by Nat on Unsplash – Innovation is easy to see. Truth is harder to judge.