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AI Business IBM Management

Making It Up As We Went Along

There was a building along Route 270 in Gaithersburg, Maryland where people kept secrets for a living. Not the cloak and dagger kind. The corporate kind, which in its own way requires just as much discipline. The IBM Washington Systems Center occupied a two-story modern building that looked, from the outside, like any other outpost of late twentieth century American business. Inside it was something else. It was where IBM sent its hardest problems, and where the largest IBM customers in the world โ€” the ones whose names you would recognize immediately โ€” sent their most urgent ones back.

I worked there as a manager. But before I was a manager there, I was a hire. And before I was a hire, I was like every other IBM professional on the outside of a particular line โ€” a line I didnโ€™t fully understand until I crossed it.


At IBM there was a protocol so embedded in the culture it had almost ceased to be a rule and become something closer to a religious observance. New products were not discussed until they were announced. Not hinted at. Not alluded to. Not whispered about with a favored customer over lunch. The announcement came in the form of something called a Blue Letter โ€” a formal communication from senior leadership that functioned as the official moment a product entered the world. Before the Blue Letter, the product did not exist in any conversation you were permitted to have. After it, you could talk about nothing else.

Violation was not a career setback. It was a firing offense. Full stop.

That clarity had a kind of elegance to it. You didnโ€™t have to calibrate how much you could say or navigate gray areas. The line was absolute. And because it was absolute, and because everyone knew the consequence of crossing it, the culture enforced itself. You didnโ€™t need surveillance. You needed people to understand the stakes, and they did.


What I didnโ€™t understand, from the outside, was what that line was doing to my imagination.

When you canโ€™t see the roadmap โ€” when the strategy and the unannounced products and the long arc of where the company is going are all behind a wall you have no access to โ€” you donโ€™t experience that as absence. You experience it as depth. The things you donโ€™t know feel like they must be there for a reason. The gaps in the announced picture feel like the gaps in a great iceberg โ€” whatโ€™s visible is impressive, but whatโ€™s below the surface must be more impressive still.

I had faith in IBMโ€™s strategic intelligence the way you have faith in things you canโ€™t fully see. And faith, uncontradicted by evidence, tends toward beauty. The hidden roadmap wasnโ€™t just unknown โ€” it was, in my imagination, a thing of coherence and intention and vision. It had to be. The alternative was too unsettling to consider.

Then I got hired into the Washington Systems Center and crossed the line.


There was no single moment of disillusionment. No specific product that shattered the dream, no strategy document that read like a disappointment. It was more like a gradual adjustment of the eyes โ€” the way they adapt when you move from bright sunlight into a room lit quite differently than you expected. The room isnโ€™t dark. Itโ€™s just not what you anticipated. And once your eyes adjust you can see perfectly well, but you can never quite recover the image you had of the room before you entered it.

The reality on the inside was messier than the dream on the outside. More improvised. More human. We were, in ways I hadnโ€™t anticipated, almost making it up as we went along. Not carelessly โ€” the people at WSC were extraordinary, the work was serious, the commitment was real. But the beautiful coherent roadmap I had constructed in my imagination from the outside bore only a partial resemblance to the actual thing. Strategy, it turned out, looked different up close. Less like architecture. More like weather.

I absorbed this alone. Nobody sat me down and named what I was experiencing. Nobody had the conversation with me that I would later learn to have with others. I found my way through it by degrees, the way you find your way through most things that donโ€™t come with instructions.

What came out the other side wasnโ€™t cynicism. It was something more useful โ€” a clearer eye, a more grounded relationship to the institution I was part of. The faith hadnโ€™t been wrong exactly. It had just been innocent. And innocence, once lost, canโ€™t be recovered. But what replaces it, if youโ€™re lucky, is something steadier.


Years later I was the manager. And I was hiring IBMers โ€” good ones, experienced ones, people who had spent serious careers on the other side of the blue line. They knew the products cold. They knew the customers. They knew how to work. What they didnโ€™t know, couldnโ€™t know, was what waited for them on the inside of the wall they were about to cross.

I knew it. Because I had been them.

There is a particular expression that crosses a personโ€™s face when the actual roadmap becomes visible for the first time. It isnโ€™t dramatic. It doesnโ€™t announce itself. Itโ€™s more like a subtle recalibration โ€” a slight stillness, a momentary adjustment behind the eyes. The person in front of you is doing quiet interior work, reconciling what they imagined with what theyโ€™re now seeing. The gap between those two things is doing something to them, and theyโ€™re not sure yet what to do with it.

I learned to watch for that expression. And when I saw it I knew what was coming if I didnโ€™t get ahead of it.


The danger wasnโ€™t disappointment. Disappointment is temporary, and smart people move through it. The danger was what disappointment hardens into when it isnโ€™t named and worked through โ€” a corrosive cynicism that poisons not just the person carrying it but everyone around them. A talented IBMer who had invested a career in faith, discovered the faith was misplaced, and decided the whole enterprise was therefore hollow โ€” that person could do real damage to a team. I had seen it happen, or the early stages of it, which was enough.

So I developed what I came to think of as the god is dead conversation.

The name came from Nietzsche, though the application was strictly practical. What Nietzsche meant โ€” or one of the things he meant โ€” was that when the organizing faith of a civilization collapses, the collapse doesnโ€™t leave nothing. It leaves a vacancy that has to be filled with something else, something built rather than inherited. The god is dead conversation was about helping someone through that vacancy quickly, before they filled it with the wrong thing.

It wasnโ€™t a long conversation. It didnโ€™t need to be. What it needed to be was honest, and direct, and delivered before the cynicism had time to set.

I would tell them what I saw happening. I would tell them it was normal, expected, that everyone who crossed this particular line felt some version of it. I would tell them the dream theyโ€™d carried on the outside wasnโ€™t foolish โ€” it was a reasonable response to incomplete information, and the information had been incomplete by design, and the design had served real purposes. None of that made them naive. It made them human.

And then I would tell them what Iโ€™d learned on my own, without anyone to guide me through it. That the messiness on the inside wasnโ€™t a failure of IBMโ€™s intelligence or intention. It was just what strategy actually looks like when youโ€™re close enough to see the seams. Every institution looks more coherent from the outside than it does from the inside. Thatโ€™s not a scandal. Thatโ€™s organizational life.


The conversations were tricky. There was real care required. You were asking someone to grieve something โ€” the beautiful imagined roadmap, the faith in a hidden coherence โ€” without tipping them into bitterness about what replaced it. You were trying to accelerate a process that, left alone, might drag on for months and quietly corrode their effectiveness. And you were doing it while also being their manager, which meant you needed them functional and engaged on the other side of the conversation, not just unburdened.

What I had going for me was credibility. I wasnโ€™t delivering a message from outside the experience. I had made the same crossing. I knew the specific texture of what they were feeling because I had felt it myself โ€” the diffuse quality of it, the absence of a single dramatic moment, the gradual adjustment of the eyes. When I told them I understood what was happening to them, I actually did. I think they could tell.

Trial and error had taught me the shape of it. What didnโ€™t work I had found out the hard way, at some cost, early on. What I arrived at had been load tested by real people in real situations. It wasnโ€™t a framework from a leadership seminar. It was something I owned completely, which meant I could adapt it in the moment rather than execute a script.


Most of them came through it well. Better than well, actually.

What I hadnโ€™t fully anticipated โ€” though in retrospect it makes complete sense โ€” was what replaced the faith once it was gone. It wasnโ€™t the steadier, clearer-eyed pragmatism I had found my way to alone. It was something more potent than that. Something that surprised me the first time I saw it and then became one of the things I quietly counted on.

They came out the other side feeling superior.

Not arrogant. Not dismissive of colleagues still on the outside. But quietly, privately elevated โ€” because they were now keepers of the secrets they had once only believed in. The blue line that had shaped their entire professional identity, that had defined the boundary of what they could know and say and imagine, was now behind them. They were on the inside. They had access. They had been trusted with the actual roadmap, the real strategy, the unannounced products that the rest of the world was still constructing faith-based pictures of.

The believer had become the keeper. And keeping, it turned out, was a more powerful identity than believing. The believer is passive โ€” sustained by what they imagine. The keeper is active, responsible, trusted. They carry something real rather than something projected.

It solved my practical problem neatly, though that wasnโ€™t why it moved me. What moved me was watching people find their footing on the other side of a genuine loss and discover that the ground there was solid โ€” different from what theyโ€™d imagined, but solid. They hadnโ€™t just survived the crossing. Theyโ€™d been changed by it in a way that made them more valuable, more grounded, more fully present to the actual work.

Which was, I suppose, what the god is dead conversation had been for all along.


I think about that blue line often these days.

We are living through a moment when artificial intelligence is advancing faster than most people can track, and the organizations building it โ€” the labs, the research teams, the companies placing enormous bets on where this technology is going โ€” have their own version of the wall. Not identical to IBMโ€™s. The competitive and legal architecture is different. The culture is different. But the basic structure is the same: there is what has been announced, and there is everything else, and most people are working entirely from the announced side.

Which means most people are doing what I did before I crossed the line at WSC. They are filling the gaps with faith. And faith, uncontradicted by evidence, tends toward beauty.


The unrevealed AI roadmap looks, from the outside, like a thing of coherence and intention. The capabilities that havenโ€™t been announced yet must be more impressive than the ones that have. The strategy must be more considered than whatโ€™s visible. The gaps in the public picture feel like depth rather than uncertainty โ€” like the part of the iceberg below the surface, which must be vast because the part above is already remarkable.

I am not saying this faith is wrong. I held the same faith about IBM and it wasnโ€™t wrong exactly โ€” it was innocent. The people constructing faith-based pictures of where AI is going are doing a reasonable thing with incomplete information. The information is incomplete partly by design, for reasons that make competitive and strategic sense, just as IBMโ€™s secrecy made sense. None of that makes the faith naive.

But Iโ€™ve been inside enough walls to know what the inside tends to look like. And I think itโ€™s worth saying, clearly and without cynicism, that the reality is probably messier than the dream. More improvised. More uncertain. More human. The people building these systems are extraordinary โ€” the work is serious, the commitment is real โ€” but they are also, in ways that might surprise you, almost making it up as they go along. Not carelessly. But without the complete map that the outside imagines must exist somewhere, fully drawn, waiting to be revealed.

Strategy, up close, looks less like architecture and more like weather.


This isnโ€™t a counsel of despair. Itโ€™s almost the opposite.

The IBMers who crossed the line and survived the god is dead conversation didnโ€™t end up with less than they started with. They ended up with more โ€” a clearer eye, a more grounded relationship to the institution, a more useful kind of engagement with the actual work. The faith they lost was the innocent kind. What replaced it was steadier and more durable.

I suspect something similar is available to anyone willing to look at the AI moment with clear eyes. Not the disappointed cynicism of someone who expected a beautiful coherent roadmap and found a human institution instead. Not the breathless faith of someone still on the outside of the wall, filling gaps with generous assumptions. Something in between โ€” harder to sustain, more honest, ultimately more useful.

The technology is real. The progress is real. The stakes are real. None of that requires the roadmap to be a thing of beauty. It just requires it to be worked on seriously by people who understand what they donโ€™t yet know โ€” which, from everything I can observe, it is.


What I couldnโ€™t give those IBMers, and what nobody can give you, is the experience of crossing the line yourself. The god is dead conversation only works because the crossing has already happened โ€” because the person sitting across from you has already seen the actual roadmap and is already processing the gap between what they imagined and what they found. You canโ€™t have the conversation in advance. The disillusionment has to be real before it can be worked through.

Most of us will never cross the line into the AI labs. Weโ€™ll stay on the outside of the wall, working from the announced picture, filling the gaps as best we can. Thatโ€™s not a failure โ€” itโ€™s just the condition most of us are in, the same condition those IBMers were in for their entire careers before I hired them.

But knowing the wall exists, and knowing what walls do to imagination, seems like it ought to change something about how we hold our faith. Not abandon it. Just hold it a little more lightly. Stay curious about the seams. Remain open to the possibility that the most important thing about the unrevealed roadmap isnโ€™t whatโ€™s in it โ€” but what weโ€™ve projected onto it.

The blue line is still there. Most of us are still on the outside of it.

And the hidden roadmap still looks, from here, like a thing of beauty.

Categories
Curiosity

Hunting for the “Why”

Iโ€™ve spent a lot of time watching peopleโ€”myself includedโ€”hit what feels like a glass ceiling. We often chalk it up to a lack of “natural talent” or the missing spark of genius. We look at the high-flyers in our industry and assume they were born with a blueprint we never received. But lately, Iโ€™ve realized that the most successful people I know aren’t necessarily the ones with the highest IQ; theyโ€™re the ones who simply never stopped asking why.

Bill Gurley puts a name to this:

โ€œThe thing that will differentiate you more in your career than anything else is being the most hyper-curious person.โ€

For me, curiosity isn’t a personality trait; itโ€™s an appetite. Itโ€™s that itch in the back of your brain when something doesn’t quite make sense. Hyper-curiosity is the willingness to be the “annoying” person who asks for the raw data or the one who stays up an hour late following a rabbit hole that has nothing to do with tomorrow’s to-do listโ€”and everything to do with how the world actually works.

We live in an age where the “ivory tower” has been dismantled. The walls are down.

โ€œI canโ€™t make you the most talented person in your company or your field, but you have no excuse not to be the most knowledgeable person. The information is all out there.โ€

This hits hard because it removes our favorite excuse: “I just wasn’t born for this.” It shifts the weight from our DNA to our discipline. Iโ€™ve found that the moment I stop being a passive consumer and start being a hunter of information, my world gets bigger. Knowledge is the only asset that doesn’t depreciate; in fact, it compounds.

When you commit to being the most curious person in the room, you arenโ€™t just “doing well.” You are building a life in high-definition.

โ€œIf you are the most curious person constantly learning in your field, you will do extremely well.โ€

But beyond the “doing well,” thereโ€™s a deeper peace that comes with it. You realize that you don’t need to be the smartest person in the roomโ€”you just need to be the one most willing to learn from it.

Categories
AI Work

Why IBM is Hiring Beginners

There is a pervasive anxiety humming beneath the surface of the modern workplaceโ€”a quiet, collective fear that the bottom rungs of the corporate ladder are being systematically sawed off by artificial intelligence.

The common wisdom, echoed in countless op-eds and boardroom whisperings, is that entry-level jobs are the natural prey of the Large Language Model.

The tasks of summarizing, drafting, formatting, and basic coding are easily consumed by algorithms. If a machine can execute the rote labor of a junior analyst in three seconds, why hire the junior analyst at all?

It is a seductive, mathematically appealing logic, especially in an era of tightening belts and efficiency mandates.

Consequently, we are witnessing a landscape where many tech companies are quietly, or sometimes loudly, slashing their junior roles to lean on AI.

But amidst this trend, an alternative approach emerges that feels almost rebellious in its long-term optimism.

IBM, a legacy titan that has weathered every technological revolution of the past century and where I started my career, is leaning entirely the other way. Rather than cutting, they are reportedly tripling their entry-level hiring.

Reflecting on this strategy, IBMโ€™s chief HR officer noted:

“The companies three to five years from now that are going to be the most successful are those companies that doubled down on entry-level hiring in this environment.”

This perspective is profound because it challenges the very premise of what an entry-level employee actually is.

The prevailing, perhaps cynical, view treats a junior worker merely as a unit of basic output. If you view a beginner only as a spreadsheet compiler or a draft-writer, then yes, they appear redundant in the face of AI.

But what if we view the entry-level role not as a terminal function, but as an apprenticeship?

When we hire a beginner, we aren’t just buying their immediate, unpolished labor. We are investing in a trajectory.

We are bringing them into the fold so they can absorb the tacit knowledge of the organizationโ€”the unwritten rules, the cultural nuances, the complex, human art of navigating institutional friction.

An AI cannot learn the subtle interpersonal dynamics of a specific team, nor can it develop the intuition that comes from failing, recovering, and being mentored by a seasoned veteran.

If we automate away the entry-level, we effectively destroy the incubator for our future mid-level and senior leaders. Where will the experienced managers of 2030 come from if no one is allowed to be a beginner in 2026? You cannot suddenly parachute someone into a senior role and expect them to possess the deep, intuitive judgment that is only forged in the crucible of early-career trial and error.

The institutional memory breaks down.

IBMโ€™s strategy recognizes a crucial reality: AI shouldn’t replace the beginner; it should accelerate them.

Imagine a junior employee who isn’t bogged down by mindless grunt work, but instead is handed the tools to instantly bypass the mundane. They can spend their foundational years analyzing, questioning, and engaging in higher-order problem-solving alongside their mentors. They transition from data-gatherers to hyper-learners.

By doubling down on human potential in an age of artificial intelligence, companies are making a strategic bet on the one asset that cannot be replicated by a server farm: the evolving, adapting, and deeply creative human mind.

The most successful organizations of the near future won’t be the ones with the fewest employees and the most algorithms; they will be the ones that used algorithms to cultivate the most formidable, deeply experienced human talent.

The ladder hasn’t been dismantled. It has merely been redesigned.

The only question is whether we have the foresight to keep inviting people to climb it.

Categories
Creativity Curiosity Living Work

The Human Router

There is a distinct difference between information and wisdom, and often, that difference is measured in velocity. We are accustomed to thinking that faster is betterโ€”fiber optic cables, 5G, real-time Slack notifications. We want knowledge to travel at the speed of light.

But Dan Wang, in his book Breakneck, captures a sociological truth about Silicon Valley that defies this obsession with speed:

“When I worked in Silicon Valley, people liked to say that knowledge travels at the speed of beer. Engineers like to talk to each other to solve technical problems, which is how knowledge diffuses.”

It is a charming, slightly irreverent metric, but it points to something profound about how humans solve difficult problems. There is “codified knowledge”โ€”the explicit instructions found in textbooks, API documentation, and internal wikis. This travels instantly. It is frictionless. It is also, usually, insufficient for true innovation.

Then there is “tacit knowledge.” This is the intuition, the heuristic, the war story about why a specific architecture failed three years ago. This knowledge is heavy. It doesn’t travel through fiber optics; it travels through proximity. It requires the social friction of a shared table and the serendipitous collision of two engineers venting about a seemingly unrelated problem.

Crucially, this mechanism requires a specific type of operator: the Connector. These are the unsung heroes of the “speed of beer” economy. They aren’t always the 10x engineers on the leaderboard. They are the “human routers”โ€”the people who instinctively know that the problem you are facing today is the same one Sarah from the Platform team solved last year. They are the ones who drag the introverted genius out to the pub, not to distract them, but to plug them into the grid. They curate the environment where the spark can jump the gap.

In our modern drive for remote efficiency, we are optimizing for the transfer of data. But we must be careful not to optimize away the people who pour the drinks, literal or metaphorical. That slow, liquid diffusion of ideas is often where the real breakthrough hidesโ€”steered by those special few who know exactly who needs to talk to whom.

Categories
AI Work

The Rungs We Leave Behind

โ€œCompanies, too, must prepare. To thrive they need not only to make the best use of ai, but also to find and nurture the best people to work with it. Some back-office workers will lose their jobs. But others with tacit knowledge of the business may be trained for new roles. The biggest mistake would be to stop hiring young people altogether. That would not only choke off the pipeline for future talent, it would rob businesses of AI natives. Instead, companies should rethink the type of work they offer young peopleโ€”less grunt labour, more judgment and analysis; speedier rotations across the business so they gain insight that ai cannot have; piloting new roles and trying new approaches.โ€
โ€” The Economist

There is a specific kind of quiet panic in boardrooms today. It isn’t just about the bottom line; itโ€™s about the lineage of knowledge. For decades, the “entry-level” role served a hidden purpose. It wasn’t just about getting the spreadsheets done; it was about osmosis. By doing the “grunt labor,” a young professional absorbed the culture, the politics, and the subtle, unwritten rhythms of an industryโ€”what we call “tacit knowledge.”

We often view AI as a replacement for the “boring stuff,” but we forget that the boring stuff was the soil in which expertise grew. If we remove the bottom rungs of the ladder because a machine can climb them faster, how do we expect anyone to reach the top?

The shift from “labor” to “judgment” is a profound psychological leap. We are essentially asking 22-year-olds to skip the apprenticeship of execution and move straight into the apprenticeship of discernment. This requires a radical empathy from leadership. We cannot simply hand a junior employee a powerful AI tool and expect them to know what “good” looks like if theyโ€™ve never seen “bad” up close.

The “AI native” brings a fluidity with technology that my generation might never fully replicate, but they lack the scars of experience that inform intuition. To thrive, companies must become teaching hospitals rather than just production factories. We need to create “judgment-rich” roles where young people are encouraged to experiment, to fail safely, and to rotate through the business at a pace that keeps them ahead of the automation curve.

The disruption is here. It is unavoidable. But there is a soulful middle ground: using AI to strip away the drudgery while doubling down on the human mentorship that transforms a “worker” into a “leader.” The goal isn’t just to make the best use of AI; itโ€™s to ensure that when the AI provides an answer, there is still a human in the room with the soul and the context to know if that answer is right.