productivity – Grandpa Bob Encouraging Leadership

Pursuing Tranquility of Order

Peace is often defined as the absence of something.

The absence of conflict. The absence of noise. The absence of pressure. The absence of the next problem.

But peace is less about absence and more about order.

I recently heard peace described as tranquility of order, a phrase with roots going back to Augustine. In City of God, he wrote that “the peace of all things is the tranquility of order.”

This doesn’t suggest that peace only arrives when every problem has been solved, every relationship has been repaired, every task has been completed, and every loose end has been tied off.

That version of peace is impossible to sustain.

Life keeps moving. There’s always another hurdle to clear, another obstacle to navigate, another decision to make, another issue waiting around the corner. Just when we think things are finally settling down, something changes.

The pursuit of peace isn’t the pursuit of a trouble-free life.

It’s the pursuit of a rightly ordered life.

Priorities in the right order. Relationships in the right order. Responsibilities in the right order. Ambition in the right order. Rest in the right order. Attention in the right order.

That kind of peace doesn’t just happen to us.

We create it when we decide what deserves our attention and what doesn’t.

We create it when we stop letting every urgent thing pretend to be the most important thing.

We create it when we clean up a workspace, finish a lingering obligation, repair a strained conversation, or finally admit that something has been taking up more room in our life than it deserves.

We create it when we make the next good decision, even when everything around us is still imperfect.

I’ve always found real satisfaction in this kind of work. A confused or stalled project. A messy process. A cluttered schedule. A team that needs direction. A home project waiting for the right next step. A piece of land slowly shaped into something useful and beautiful.

There’s something deeply rewarding about creating enough order for people to breathe again.

That doesn’t mean controlling everything. In fact, the best kind of order often requires us to hold things loosely, leaving room for the unexpected, and trusting that people, plans, and possibilities are better tended than controlled.

Order, at its best, creates room for life.

It clears enough space for thought. It creates enough structure for trust to build. It gives people enough confidence to move. It helps us see what belongs, what doesn’t, and what needs attention next.

And then, occasionally, we experience it.

A quiet morning. A settled room. A finished project. A table full of people we love. A trail cleared through the woods. A plan that starts to come together. A day where the pieces seem to fit, even if only for a while.

Those moments may not last forever, but they remind us what we’re aiming for.

Pursuing tranquility of order is the steady work of arranging our lives around what is good, true, useful, loving, and worth carrying.

When life feels too overwhelming to arrange all at once, we can start small. The next right step, the next honest action. The next one thing that brings even a corner of our life back into order.

We won’t always get it right.

There will always be disruptions. There will always be pressure. There will always be something that knocks our papers off the desk just after we get them stacked.

But we can keep returning to order.

We can return to our priorities. We can return to our responsibilities. We can return to the people we love. We can return to the work that has been entrusted to us. We can return to the kind of person we’re trying to be.

Peace isn’t found by escaping the noise.

It’s built, little by little, when we keep putting the most important things back where they belong.

Photo by AO NURA on Unsplash – There’s more to this peaceful image than it appears. Growing. Cutting. Drying. Raking. Baling. Each step in its right order. Each making the next possible, leading to this image. The work isn’t finished. Those bales still need to be moved and stored.

But we can enjoy this. The proper order. A moment of tranquility.

AI Doesn’t Know Our Business. We Do.

AI can prototype our workflow. It can draft our requirements. It can generate our user stories. But it has no idea how our business actually works.

It can’t tell us where the bottlenecks in the process are. Our loan officer knows that. It can’t explain why the workaround exists. Our operations manager knows that. It doesn’t know which shortcuts blow up in an audit. Our compliance analyst knows that. It has no idea where customers rage-quit. Our customer service supervisor knows that.

Our best people, the ones who actually know how the work works, often have trouble translating what’s in their heads into something a developer can build. They know where the friction is. They know which exceptions happen every Thursday afternoon even though the procedure says they shouldn’t. They know which approval step matters, and which one is just a bureaucratic leftover from a reorg three years ago.

For the first time, the people who do the work and understand the problems they’re trying to solve can start shaping the solutions. AI gives their expertise a doorway it never had before.

These subject matter experts can sit down with an AI tool and start turning what they know into something visible. Plain language in. Workflow out. Prototype sketched. Edge cases surfaced. User stories drafted.

And when they do that, something shifts. They realize software development isn’t magic. It’s a thousand small decisions that someone has to make. That realization alone is worth the exercise.

Instead of walking into a meeting saying, “we need a dashboard” or “can we automate this?” they walk in with something tangible. Rough? Sure. Wrong in places? Probably. But it doesn’t have to be production-ready. It has to be conversation-ready.

That changes everything.

Developers, architects, and project leaders can see the idea. They ask sharper questions. They spot what already exists, what creates risk, what can ship fast. The subject matter expert starts understanding what building a solution actually involves. The dependencies. The data quality landmines. The difference between a slick mockup and something that holds up in production.

That shared understanding transforms the relationship between business and technology.

We know the old pattern. Business has a need that’s difficult to explain, the technology team tries to interpret it, weeks pass, something appears, the business says, “close but not what we meant,” the cycle repeats. Everyone gets frustrated. Nothing ships.

AI doesn’t kill that cycle. It compresses and turbo charges it. When developers start with a real prototype and a real conversation, iterations can take hours or days instead of weeks.

The AI win is getting people in the same room faster, with something real to react to.

If more people can generate ideas, workflows, and prototypes, we’ll start getting more possibilities than we can pursue. A good problem to have, but still a problem.

Bottom-up energy is powerful. It surfaces solutions from the people closest to the work. It finds problems leadership didn’t know existed.

But without focus, we’ll drown in prototypes. The bottleneck doesn’t disappear. It moves from “we don’t have enough ideas” to “we have no idea which ideas deserve investment.”

That’s on leadership.

Executives, your job isn’t to be the gatekeeper of imagination. Play that role and the old problems come back fast. Good ideas will die in departments, in notebooks, in hallway conversations that never go anywhere. You become the reason nothing changes.

Your job is to be the steward of focus. Create the channel. Invite ideas up. Encourage people to explore, prototype, get specific. Then make the call on what moves forward.

Bottom-up imagination. Technical refinement. Executive focus. That’s a model that AI tools make possible.

Subject matter experts bring better ideas because AI helps them say what they know. Technical teams sharpen those ideas because they understand what durable software is. Executives look across the whole landscape and ask the hard questions nobody else is positioned to ask.

Does this solve a real problem or just an annoying one? Does it scale? Does it duplicate something we already own? Does it create risks we can’t absorb? Is this a strategic investment or a distraction dressed up as innovation?

Not every prototype becomes a project. Not every project deserves to live in our permanent technology environment. That’s not a failure of imagination. That’s how imagination gets distilled down to create tangible business value.

The future advantage won’t go to the fastest movers or the biggest tool buyers. It won’t go to the organizations that treat AI like a cure-all and wonder why nothing changes.

It’ll go to the ones that know their business well, listen hard to the people doing the work, and never confuse creating more things with creating better things.

AI can help us build faster. That’s the easy part.

Knowing what to build and why. That’s still on us.

Photo by BEN ELLIOTT on Unsplash – This is a downwind leg, spinnakers out, boats grabbing everything the wind has to offer. A good metaphor for AI. It can give us remarkable speed. But we’re still in a race, there’s still a course to navigate, and the turns are still ours to make.

When the Goal Feels Too Big, Go Small

Some goals are big enough to carry us for a long time.

They lift our eyes. They fill ordinary days with meaning, connecting our work to something larger than the moment in front of us.

That vision matters.

It gives shape to sacrifice. It helps us endure hard things because we can see where we’re trying to go.

But big goals have a way of becoming heavy.

Sometimes the distance feels too great. The work takes too long. The gap between where we are and where we want to be can leave us discouraged before we’ve gone very far at all.

That’s when it helps to bring the goal down to just the next step. The next mile. The next call. The next page. The next hour of honest work.

We don’t accomplish great things all at once. We get there by doing the next thing that needs doing.

The small task gives us traction. It pulls us out of vague ambition and back into motion.

But this has its own challenge.

Sometimes the next step feels too small. Repetitive. Disconnected. We can lose heart in the middle of faithful effort simply because the work in front of us seems too ordinary or meaningless.

That’s when we need to lift our eyes again. Remember why we started. Who this serves. The person we’re trying to become.

Focusing only on the big vision, we risk becoming dreamers who admire the mountain and never climb it. Living only in the next task, we can become people who just keep moving and slowly forget why.

Our strength comes from learning to move between the two.

When the goal feels too big, narrow the focus. When the next step feels too small, widen the focus.

The vision gives meaning. The step gives traction. We need both.

h/t – to a recent Jocko Willink short on this exact tension…worth a couple minutes of your time.

“When making plans, think big. When making progress, think small.” — James Clear

Photo by Florian D. Bazac 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.

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.

AI as Iteration (at Scale)

We call it Artificial Intelligence, but large language models don’t think, reason, or understand in human terms.

A more accurate description might be Artificial Idea Iteration since these tools dramatically compress the cycles of research, drafting, testing, and revision.

SpaceX didn’t transform spaceflight by having perfect ideas. They collapsed the time between ideas and reality. Failing fast, learning quickly, and iterating relentlessly.

AI creates the same dynamic for knowledge work, letting us move from intuition to articulation to revision in hours instead of weeks.

Engineers rely on wind tunnels to test aircraft designs before committing real materials and lives. AI does this for thinking.

Iteration itself isn’t new. What’s new is the scale for iteration that we now have at our fingertips. We can explore multiple paths, abandon weak directions quickly, and refine promising ones without the time, coordination, and risk that once kept ideas locked in our heads.

When iteration becomes inexpensive, we can take more intellectual risks and shift from trying to always be right to trying to always get better.

It’s ironic that as iteration is becoming cheaper and faster with AI tools, human judgment becomes more valuable. Someone still needs to know what’s worth developing, what deserves refinement, and when something is complete rather than exhausted.

The intelligence was never in the machine. AI simply gives us the capacity to develop ideas, test them against reality, and learn from the results at a scale and speed we’ve never had before.

Iteration at scale changes what’s possible. Judgment determines what’s worth pursuing.

Photo by SpaceX on Unsplash – when SpaceX proposed the idea of landing and reusing their rocket boosters after each launch, the idea seemed impossible. Now it’s happening about 3 times per week…and they’re just getting started.

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Measuring the AI Dividend

In the early 1990s, the term Peace Dividend appeared in headlines and boardrooms. The Cold War had ended, and nations began asking what they might gain by redirecting the resources once committed to defense.

Today the conflict is between our old ways of working and the new reality AI brings. After denial (it’s just a fad), anger (it’s taking our jobs), withdrawal (I’ll wait this one out), and finally acceptance (maybe I should learn how to use AI tools), the picture is clear. AI is here, and it’s reshaping how we think, learn, and work.

Which leads to the natural question. What is our AI Dividend?

Leaders everywhere are trying to measure it. Some ask how many people they can eliminate. Others ask how much more their existing teams can achieve. The real opportunity sits between these two questions.

Few leaders look at this across the right horizon. Every major technological shift starts out loud, then settles into a steady climb toward real value. AI will follow that same pattern.

The early dividends won’t show up on a budget line. They’ll show up in the work. Faster learning inside teams. More accurate decisions. More experiments completed in a week instead of a quarter.

When small gains compound, momentum builds. Work speeds up. Confidence rises. People will begin treating AI as a partner in thinking, not merely a shortcut for output.

At that point the important questions show themselves. Are ideas moving to action faster? Are we correcting less and creating more? Are our teams becoming more curious, more capable, and more energized?

The most valuable AI Dividend is actually the Human Dividend. As machines handle the mechanical, people reclaim their time and attention for creative work, deeper customer relationships, and more purpose-filled contributions. This dividend can’t be measured only in savings or productivity. It will be seen in what people build when they have room to imagine again.

In the years ahead, leaders who measure wisely will look beyond immediate cost savings and focus on what their organizations can create that couldn’t have existed before.

Photo by C Bischoff on Unsplash – because some of the time we gain from using AI will free us up to work on non-AI pursuits.

Busy Isn’t the Problem…Ineffectively Busy Is

Almost everyone claims to be busy. Many will even describe their endless to-do list—what they’ve done, what they’re doing, and what’s next—justifying their busyness.

Lots of articles explore different types of busyness. One that stands out for me, Busyness 101: Why Are We SO BUSY in Modern Life?, lists the following types:

-Busyness as a badge of honor and trendy status symbol

-Busyness as job security

-Busyness as Fear of Missing Out (FOMO)

-Busyness as a byproduct of the digital age

-Busyness as a time filler

-Busyness as a necessity

-Busyness as escapism

The last one stands out to me: busyness as escapism.

When we’re constantly busy, we get to avoid the hard things in life. No time to reflect on priorities. No time to find smarter ways to work. No time to focus on meaningful goals…ours or our organization’s.

Busyness lets us sacrifice our other responsibilities. We convince ourselves that our sacrifices are necessary, without questioning what they truly cost us or those around us. And we tell ourselves that once we’re “less busy,” we’ll focus on the important things we’ve been neglecting. The problem? We rarely become “less busy” (at least, from our perspective).

But the busiest effective people operate differently. These individuals aren’t just busy for the sake of it. They work with intention, with purpose. They prioritize. They seek smarter ways to work. They focus on meaningful goals rather than just checking off task lists.

These are the people who not only get things done but get the right things done. And they do it faster than everyone else. Why? Because they’re too busy to be distracted by nonsense and trivialities. They tackle the big things first, and often, the smaller things take care of themselves.

When I managed large organizations, I valued these employees the most. They weren’t just productive, but they were leaders. They inspired everyone around them to be more effective. Whenever a new project or opportunity arose, I sought them out. I knew they’d prioritize the new project well and deliver great results.

The difference between being busy and being effectively busy comes down to mindset. The most productive people don’t just fill their days. They own them.

Next time you catch yourself saying, “I’m so busy,” pause and think. Are your tasks productive and effective, or just occupying your time?

You may find that you’re not as busy as you thought.

Photo by Anna Samoylova on Unsplash…my eye is on the girl in pink who’s walking away from the rope (I bet you didn’t notice her at first)

You Can’t Delegate Your Influence

A professional manager understands that managing is an active role. It requires proactive effort, not just sitting back and overseeing tasks. A good manager knows how to delegate responsibility and authority. It’s a key skill that helps multiply their impact and develop the next generation of leaders.

There’s no shortage of books and articles that dive deeply into the art of delegation. Many are worth reading and putting into practice. But here’s the thing: no matter how much you delegate, you can’t delegate your influence. That personal touch—the way you listen, share your perspective, and guide the conversation—is something only you can bring to the table.

Managers have a unique viewpoint. They understand the critical questions facing the organization in a way others often don’t. Their value lies in their ability to communicate directly, to really hear what’s being said (and often what isn’t), and to guide the organization toward the right path. That’s what makes their influence so crucial.

Now, picture this: a manager sends one of their team members to a meeting with internal customers. The goal? For the subordinate to represent the manager’s ability to listen, understand, and guide the discussion. Sure, it can work if that person has full decision-making authority and can make agreements that hold the manager accountable. But that’s rarely the case.

So, we come back to the reality: a manager has to prioritize where they spend their time and energy, making sure they’re showing up where their influence is most needed. It’s not just about sitting in meetings or making decisions on the fly—it’s about really understanding the dynamics in play, both spoken and unspoken.

A manager’s influence over the direction of projects, processes, and people can’t be handed off. At best, subordinates can carry a “shadow” of that influence. It might get the job done, but it’s not likely to push the organization in the bold direction it needs to go.

In the end, while delegation is a powerful tool, influence is personal. And if you’re serious about leading, you need to make sure you’re showing up where it counts.

Photo by Katja Anokhina on Unsplash