The Rat Race.

The Red Queen Effect.

These are all the same effect; feeling or actually needing to keep going even though you’re just running in place.

Being a former Tech worker and speaking to an audience for Tech workers too here at Human Design for Tech Workers, we are privedlged to have typically above-average compensation (salaries, RSUs etc.).

But as any Financial Planner or Advisor worth their salt will tell you then it’s not just about how much you earn, but how much you keep after expenses that truly counts in the long run.

Questions like:

1. How long is your runway if you were to be laid off today (i.e. the emergency fund question)?

2. How many years do you want/need to retire fully?

3. How much money do you need in terms of cash flow or net worth?

Those are just the financial type questions not to mentional all the psycho-social, emotional, familial questions beyond that.

But all the financial related questions anyway really matters is your household cash flow.

And if you don’t consider that today, it won’t have time meet your goals — whatever they may be — in the future.

Think of this like you want a nice bubble bath. You fill your tub with hot water and nice suds form. But if you don’t plug the tub, it’ll just keep leaking.

Part of that where it keeps leaking is how much you spend (and how much doesn’t make it your emergency fund or that eventual really nice bubble bath, i.e. retirement). And perhaps the most egregeious things is what Nick Maggiulli from Dollars and Data calls The Upper Middle Class Trap1.

He calls out how demand for private school, airport lounges or business-class type airplane seating is being crowded out.

Costs are skyrocketing, and frankly, it’s keeping up with the Jonses in the most literal sense.

But I think where Maggiulli really hits the nail on the head is that it’s the confluence of all these things that make it easy to miss. Here’s how he describes it:

The issue with the upper middle class trap is that it’s a collective action problem. Individually, every decision is rational. It’s rational to send your children to the best schools, to want a nicer home, and to travel to opulent destinations. But, collectively it’s self-defeating. When everyone is vying for the same limited resources, it lowers quality of life across the board.

Many Upper Middle Income households make rational, logical single decisions. However when you take them in aggregate, it creates a situation where you’re for the local-maxima, but it doesn’t really achieve the global-maxima that you one had in mind. And of course the current day’s expense is reverse-compounded expense from your retirement or medium to longer term goals.

As we explore about Human Design and BG5 and how you can find individual alignment and create more material wealth in your career and in your business, there is also an important to focus on proper financial planning through exploration and thinking about retirement, legacy. It’s also important to think about being mindful about expenses too.

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Overarching Work Theme

“People who seek and find both spirit and great pleasure in life through creativity…” -The Definitive Book of Human Design

Steve Jobs has what they call a trans-personal life purpose: focused on others having bring out this purpose to others. In more detail, Jobs’ life purpose is deeply rooted in emotional depth and the spirit of abundance. For someone like Steve, they carry the gift of igniting creativity and passion in others. And their your emotional richness and moodiness are the fuel for inspiring transformation, while your focus and enthusiasm build the mastery to deliver on that vision. This is just derived for their work theme aspects. It really does sound very much life Steve and his work at Apple.

More than most technicians out there, Steve was a master crafter and a master marketer — which we all can connect with and understand now in posterity. But at the time, it wasn’t so obvious. This overarching work theme bridges all the hats he wore (not just the title of the roles he play nor the companies behind them) — think Pixar for instance — where creativity and passion for the art of storytelling via technology was just as important to him as what he was doing over at Apple.

It’s seems like such a simple sentence but all of it is important to unlock the overarching work theme for him.

Remember what Steve said him at the 2005 Commencement speech1 at Stanford:

“Of course it was impossible to connect the dots looking forward when I was in college. But it was very, very clear looking backwards ten years later.

Again, you can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future.”

He wasn’t seeking Apple per se — perhaps no one could’ve predicted the outcome and all the twist and turns. But the thread through all those parts of Steve’s career is that fact that he indeed SOUGHT and FOUND the great pleasure in life through CREATIVITY.

There’s very little doubt looking the outcome of Steve’s life and times that those were clearly his OVERARCHING WORK THEME.

And that’s what they say in BG5 / Human Design circles too. The overarching work life theme comes out as a direct result of you following all your other Strengths, Working Arrangements, what you’re Broadcasting, Potential for Wisdom, your Public Role. Think of it less as a north star, but what will the second-order (or higher-order) effects of living your most aligned life.

And thats what I will say is Steve’s legacy, even though he wasn’t perfect and also passed away young, he reached his potential.

In the same Commencement speech (which I watch often), he told the graduating class an simple piece of advise as they head off into their own journeys and career paths:

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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Here’s at the first 4 parts:

All of us have our own versions — differentiated — of these aspects of our Career and Business traits below.

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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Main Public Role

Theres two parts that come together here to form the someone’s Public Role. The Public Role is about the following when it comes to any career but we’ll explore Jobs’ in further sections below:

• It plays as one’s “Professional “Costume”: Think of it as the energetic costume you wear in public. It dictates exactly how colleagues, clients, and the broader market perceive you, as well as the inherent expectations they place on you.

• There are two characteristics in his “Costume”: One aspect is conscious and you recognize it in yourself. The other hand is unconscious and it’s typically something you’re not entirely aware of but others that you work with are more likely to recognize in you.

• Mechanisms of Interaction: It defines your natural style of engaging with the world to achieve material success.

• Flow and Alignment: When you stop resisting your Public Role and allow it to function more in flow, you naturally attract the correct recognition. You don’t have to force your professional identity.

Now let’s unpack what is Steve Jobs’ Public Role.

Unconscious Role: Experimenter (Born of trial and fire)

Quite unconsciously Jobs learned through trial and error. This is someone who will have to learn experientially and experimentally — typically with their own hands. They learn from mistakes. It also means they pick themselves up and try and try again.

I find this aspect sometimes hard to tease out. We all do things we’ve never done before and then try again. So being an experimenter itself might seem as though we all have this trait. One way to tease out such a difference is that the act of doing versus just thinking. If taken to the extreme, we see someone that experiments is that one that uses one literal hands. And Jobs’ was very much like that. In fact there is another interview of him where he explains the importance of thinking and doing:

“The doers are the major thinkers. The people that really create the things that change this [tech] industry are both the thinker-doer in one person.

Did Leonardo [DaVinci] have a guy off to the side that was thinking five years into the future aobut what he would paint or technology he would use to paint it? Of course not, Leonardo was the artist, but he also mixed his own paints, He also was a fairly good chemist. Knew about pigments. Know about human anatomy. And combining all of those skills together — the art and the science, the thinking and the doing — is what results in the exceptional result… There is no difference in our industry. Th people that have really made contributions have been the thinkers and the doers.”

Conscious: Role Model (in 3 distinct phases)

His Public Role that comes in thirds, one before 30 which is very much a trial and error, between 30-50 he retreats and then finally in the phase where 50+ where he’s taken those lessons and becomes a role model.

• Operates with an inherent need for objectivity, trust, and a broad perspective.

• Functions best when they can step back from the day-to-day grind to oversee the big picture, seeing exactly how all the moving pieces of a business or project fit together.

• Their leadership style is not authoritative by force or deep academic study, but rather driven by the natural respect they garner from having “been in the trenches” and survived.

It’s interesting to note that his Stanford Commencement Speech — which is still something watched and inspiring to many — was given a few months after he turned 50!

But let’s see if we explore those 3 distinct eras and how Jobs was different in those parts of his stages in his careers.

Phase One: Before 30

In order to be a role model, it’s about embracing the chaos and confusion and wonderment of the early years. It’s important as a learning process and comes with it the essential discovery that builds up the catapult to reach it’s next phase.

• The Clip: The 1984 Macintosh Introduction.

• The Context: At 29 years old, Jobs is deeply immersed in his chaotic, trial-and-error 3rd-line phase. The presentation is intense, highly subjective, and aggressively competitive (specifically taking aim at IBM). It captures his relentless drive to physically push boundaries and disrupt the market, just a year before his experimentation clashed with corporate structure, leading to his ousting from Apple.

Phase Two: Ages 30 to 50

They pull back from the chaos to become objective observers. In business, this is when they begin to synthesize their early failures into valuable, marketable wisdom and take on higher-level oversight or advisory roles.

• The Clip: The 1997 WWDC “Fireside Chat” Q&A.

• The Context: At 42, returning to a failing Apple, Jobs demonstrates the classic “on the roof” transition. He sits calmly on a stool, fielding hostile questions from developers with objective detachment. Rather than getting into the trenches of every technical flaw, he oversees the big picture, famously explaining that true focus means saying “no” to a hundred good ideas to salvage the company’s foundation.

Phase Three: 50+

They step off the roof to become the true, lived Role Model. They lead purely by example, combining their profound experiential knowledge with objective authority to guide teams and organizations.

• The Clip: We saved the best for last: the 2007 Original iPhone Keynote.

• The Context: At 51, Jobs steps off the roof into his final Role Model phase. He commands the stage with absolute, lived authority, presenting not just a product, but a complete paradigm shift. He leverages his decades of experiential wisdom (combining hardware, software, and design) to lead the entire tech industry by example, requiring no aggressive defense of his vision because his mastery speaks for itself.

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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This is part of The Personal Moat series. Here’s Part 5 of 5 which is on Steve Jobs’ Work Theme:

All of us have our own versions — differentiated — of these aspects of our Career and Business traits below.

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

Book a Free Consult

Prominent Personal Pitfalls (and Potential)

Before we get to how BG5 derives Personal Pitfalls and at the same time incredible Potential (and how you can differentiate your own) we first have to understand the mechanics of how we operate in our work.

If you think about the way in which you work primarily through communication, it’s been studied that only about 7% of the message you’re delivery is from the words alone. Now with Slack and Teams these days, it’s very much sometimes the only thing that we use to communicate with our colleagues and our teams but think about how often you run into situations where the message doesn’t land like you would want it to, or that it requires more words and a Zoom call to get the message across. As much as many of us frown on RTO policies, there is something to be said about communication in person that minimize misunderstandings.

So where does that leave the rest of the 93% that isn’t communicated through text/speech alone?

Body language and tone are things that come to mind. But more importantly it brings up a concept where we are subconsciously simultaneously broadcasting and receiving subtle cues in messaging to each other in a work setting. And it is in the particular areas where we are open to receiving is where the miscommunication/misunderstanding can lead to our Personal Pitfalls. And it is in these areas that BG5 — as a mechanical discipline — can help illuminate the specific areas in each and everyone of us that is most subjected to being most easily influenced by others without filter.

Similarly, broadcast is the set ways in which we bring things to the table.

Neither of these are direct related to specific knowledge. It’s more about what are the underlying parts of us, the way we are wired where we are receiving influence, amplify that in a team and at the same time how we are doing that to others unconsciously.

One more thing: you can think of these are roughly nature vs. nurture too. There’s parts of us that are fixed; we have a consistent way — by nature — where we think and operate more or less the same. The nurture parts, that is the parts that we are more easily influenced by outside forces, are also the parts of us that much more likely susceptible to conditioning forces given that we are completely open and don’t have a consistent way of processing or using the information (as an example).

Pitfall: Blame. Potential: Collaboration & Objectivity

This is a pitfall who is someone who is inherently collaborative and works well and indeed helps to process (or assimilate) information with other people as a sounding board. But having other people to “bridge” some of the gaps of your potential also means that without them you tend to find fault in the other when they’re missing.

There are a lot of pros to being collaborative and that you need other people and how to work together but in the inverse, it also mean that you might feel there is a gap when other people that complement you are not around. For Jobs’ ability to assimilate collaborative, here as a Pitfall it means he’s prone to playing the blame game — prone to finding hiccups and those gaps as someone else’s problem rather than his own.

But with time it maybe blossom into its real potential: wisdom. We know very well and from many individuals that have worked with Jobs over the years that he was relentless and cutthroat. Jobs appeared to have an ego, something to prove, a perfectionist and often took it out (on himself) but was most visible on his team. This was particularly true in early in Job’s career.

But we also know that later on his career and particularly after and around the time he gave his Stanford Commencement speech that he was reaching his potential. You hear that from the collaborators at the time from Tony Fadell to Jony Ive. He still was highly critical, but he had perhaps learned to use it to his advantage and not to the point where he alienated his colleagues and team.

From Jobs’ Design we can also identify 4 additional areas where he’s open and subjected most to influence from the outside and would affect him in these ways:

1. Overcompensating or competing for things that don’t matter

2. Inflexible

3. Spending time thinking about things that don’t truly matter

4. Constantly searching for identify and direction

We see this thread in all parts of his career but also particularly in the first half of his career.

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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This is part of The Personal Moat series. We’ll have more on Steve Jobs’ Ideal Working Arrangements, Pitfalls, Public Role, and Work Theme in the coming weeks. Stay tuned!

Below here we detail the Ideal Working Arrangements where these placement in teams, partnerships in small or large institutions helps product ones best work.

Why is this interesting or important? Well, finding your Personal Moat means being able to work at your personal best. It’s not a competition with others (though that might be a reality in our world) but finding ways in which you are most aligned, find the most fulfilling work and minimize the amount of turmoil and burnout you take on.

Now, on to the show…

Ideal Working Arrangements

In BG5, which is the Career, Team and Business practice of Human Design, it details the environments and configurations that are ideal for how you work. Think about the best times you had great partners on your Scrum team, or how certain Individual Contributor duties within your role were something you not only enjoyed but took up further and with better quality.

In this context, the typical environments we talk about span:

• Individual Contributor

• Partnerships (1-on-1)

• Teams or Departments:

  • Small Teams (5 or fewer people)

  • Large Groups/Departments (6 or more people)

    • Executive Leadership Potential

    • Managerial Capabilities

When we look at Jobs’ Design, we can see that his ideal environments were (perhaps not surprisingly):

1. One-on-one partnerships

2. Small Teams

The framing here is always about where Jobs is designed to thrive (the double negative is intentional, for those keeping score).

Collaboration through Partnership

This is where Jobs worked best. Partnerships, particularly the ones that are 1:1, provided it was the correct and fitting person. In any good partnership, or any team formation for that matter, you sort of become greater than the sum of the parts, while at the same time something else converges.

In the specific case of Partnerships, it’s actually useful to use inversion to talk about the value of 1:1 here. What happens when you work alone when it’s not your ideal arrangement? Of course anyone can work in any environment, let’s be clear on that. The real question is whether it’s ideal, meaning how long is it sustainable, is it preferred, and does it bring out the best in you (and vice versa)? Those are the real questions, and why there is value in understanding the environments you work best in and with.

In tech, and before this Agentic AI craze, most of the work we had to do, particularly the technical parts, was so highly specialized that you were always working with others. The whole idea of teams is the norm in tech (as you know). So it’s actually hard to distill what a true Individual Contributor looks like, not just a Senior Dev on a pod, but truly the lone wolf. But suffice to say that even Jobs, who as CEO could’ve done most of it on his own (barring the tech know-how), found it fascinating to work with the other ‘Steve’ to realize his mission and vision.

On the way to founding Apple, he famously had a productive, yet at times tumultuous, relationship with Steve Wozniak. The two Steves’ achievements are undeniable. And in a few short weeks, Apple will celebrate its 50th birthday of its founding on April 1. But back in 1976, that partnership was instrumental and, I would say, brought out the best in each other.

When I examine the two Steves’ Design, we see something even more fascinating. Jobs works best in partnerships, helping bridge his mind to do his best work. Woz is quite happy to work alone and can do so for long periods. But Woz’s Design helps bridge Jobs’ Design. Remember, Strengths are made of two Traits. Jobs has the Strengths we covered in Part 1, but when Woz is around, Jobs is also able to, temporarily, carry the Strength of Discovery and the Strength of Inspiration. And if we were to unpack it a bit further, both of these translate to the Design of Succeeding Where Others Fail and the Design of the Creative Role Model.

So in this specific partnership, Jobs is helped by being able to do things more efficiently, both in thinking and feeling, and with Woz’s partnership specifically is able to bring out, in both of them, the ability to find success even in failure and to be the creative. In a nutshell, that has been Apple’s core since the very beginning.

Collaboration in Small Teams

Besides Partnerships, Jobs excels in well-chosen groups. I’ll probably start another series to go into team dynamics more later, but let’s focus on how he excels at working in small groups.

Besides the individual Strengths that Jobs possesses (discussed in Part 1), within a smaller group setting he also brings a different set of skills when it’s a group bigger than a partnership (ideally five people or fewer).

He brings four skills to the team at a group level:

1. Reliability

2. Commitment

3. Implementation

4. Accounting

There are 12 different types of skills that individuals bring to form teams. Steve has 4 of the 12. It’s less about the total number because the old adage describes it best: “the whole is greater than the sum of the parts”. In fact, here is Steve, waxing poetic on this exact thing and how he runs Apple like The Beatles:

“My model of business is The Beatles…they balanced each other. The total was greater than sum of the parts. Great things in business are never done by one person…they are done by a team of people. When The Beatles were together, they did truly innovative work. When they split up, they did good work but it was never the same.”

The 4 skills he brings feel more like adding to the matrix of the team, the fact that any small team becomes an entity unto itself and rows in unison (or not). I guess that’s why the same root word of an organism and organization is not by accident.

Another way to put it: in the context of a business team, your focus is on material success and business survival. So what you bring to the team matters at a team level, not just an individual one. As we talk through the Skills Jobs brings, it’ll probably become more apparent how finding people that complement you, and not over-concentrate on one particular Skill, is vital to each small team’s success.

Reliability

The typical connotation here is that reliability is about showing up, perhaps being on time. But from a BG5 perspective, it’s more about these:

• Trust

• Safety

• Security

Those are the things Reliability brings, and the second-order effects of that are the ability to attract talent, retain them, and provide the team a sense of belonging. Think of this as the “glue” that brings people together and holds them long enough to get stuff done.

Perhaps the clearest evidence of Jobs bringing the Skill of Reliability to his team is how Jony Ive describes the design relationship at Apple over their fifteen-plus year partnership. Ive has spoken in multiple interviews about how Jobs created an unusual kind of protection around the Industrial Design group, shielding it from the short-term commercial pressures that typically compromise design work at large companies. The design team reported directly to Jobs rather than through the usual organizational hierarchy, and this arrangement sent an unmistakable signal to the broader Apple org: this group has top-level trust and security. That kind of structural backing is what Trust, Safety, and Security actually look like in practice.

Here’s Jony recounting just that:

Commitment

Mostly self-explanatory. This is the goal-oriented skill of setting an outcome and hitting the mark.

It also provides the necessary conditions by which everyone comes onto the same page.

The higher-order effects of staying committed means it engenders loyalty to the energy dynamics of the team and stabilizes that commitment for the good of the team and the outcomes. There is a pitfall of over-commitment and all the downsides that brings, but overall it’s a dedication to make the team work for the good of the business.

The Skill of Commitment and its dynamic showed up in the very inception of the iPod and its eventual launch in 2001. Even before the first prototype was shown to the team, Jobs framed the entire product in one sentence: “1,000 songs in your pocket”. This wasn’t just a tagline invented for the launch event. It was the commitment statement that oriented the whole product team around a single, measurable outcome. The team building the iPod knew what the “definition of done” was.

Just watch this short clip below from Tony Fadell who one of the fathers of the iPod. It brings out two important things. Jobs and Fadell were part of the same team and Jobs presence (and Skill as we’re learning) was to bring the Commitment to the team. It’s exactly the type of Commitment that Fadell recalls here: they had each others’ back:

“So he made that commitment to me and I made this commitment to him to build it [iPod]” —Tony Fadell

Implementation

Implementation here refers to a few aspects:

1. Taking the company’s core vision and actually implementing it.

2. Representing the raw, innovative, creative force that drives the manifestation into a product or service in the marketplace.

Let’s invert this. If this Skill is missing from the Small Team, what you might have is resources, a solid direction, even a great PR person, but missing the unique value proposition and the ability to actually create the thing you’ll sell.

Another way of thinking about this Skill is the ability to pivot as things change. Implementation is bringing it all together from vision to product and the ability to sell it to customers. So when things change in the marketplace, without this Skill you’re likely also not able to adapt creatively.

In 1979, Jobs visited Xerox PARC and saw an early demonstration of a graphical user interface (GUI), windows, icons, and a mouse. Xerox had it. They didn’t know what to do with it. Jobs did. He went back to Apple and immediately began driving his team to implement what he had seen, pushing the engineers to do what they said was technically impossible at the speed and quality required for a consumer product. The engineers on the LISA and later the Mac teams have been clear about how relentless this pressure was. Jobs didn’t invent the GUI. He implemented it, and the distinction matters: Implementation is the Skill of taking what exists in concept and forcing it through to a thing someone can actually hold, use, and buy.

The iPhone is perhaps the definitive Jobs Implementation story. The internal project, codenamed Project Purple, was by most accounts a near-impossible engineering challenge: a new touch interface, a new mobile OS, a new radio stack, and miniaturized hardware that didn’t yet exist in the form required, all converging into one product. Jobs reviewed prototypes personally and repeatedly rejected them until the feel matched the vision. The scroll inertia on the original iPhone, the way content glides and decelerates like a physical object, is one documented example of Jobs insisting on a specific implementation detail until his team figured out how to do it. Forstall, Ive, and others who worked closely on the iPhone have described the same dynamic: the bar wasn’t the technically feasible version. It was the version that felt right. And Jobs kept pushing until those two things became the same thing.

This is a longer clip but all about Project Purple (soon to be iPhone):

Accounting

Here, this Team Skill is what Jobs brings and is a skill not as a CPA, but accounting for what the org has and is doing. The Accounting Team Skill asks two key questions in the team and business:

1. Are we profitable, or are we just doing busy work?

2. Do we understand where the organization has been, and are we using that to our advantage, learning from our failures and successes?

When Jobs returned to Apple in 1997, the company was losing roughly a billion dollars a year and had over 350 products in its lineup, many of which were redundant, unprofitable, or both. One of Jobs’ first moves as interim CEO was to stand at a whiteboard, draw a two-by-two grid, and label the axes: consumer versus professional, desktop versus portable. Four quadrants. He told his team: these are the four products we’re going to make. Everything else got cut. This is the Accounting Skill operating at its most concentrated. The question “are we profitable or are we just doing busy work?” is hard to answer honestly when you’re inside a large organization with momentum in many directions. Jobs answered it by forcing the org to see itself clearly, using the simplest possible framework, and acting on what he saw.

Medium-length clip here, but if you watch it all you get the gist that Jobs was focused on knowing where Apple came from and also where it could win given it’s prospects so far. It was a pragmatic vision of “Accounting” what is left and how to get there:

If you’re ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I’m doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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This is part of The Personal Moat series. Below are the Part 3, 4 and 5 on Steve Jobs’ Ideal Working Arrangements, Pitfalls, Public Role, and Work Theme:

Of course, hindsight is 20/20, but even still we’ll see the most pertinent aspects of Jobs’ Career Design come through in his career, his passion, and his drive that brought him to co-found Apple and run the company through its many iterations and incarnations.

It’s easier to look back and connect the dots (as Steve himself put it), but there’s also value in knowing oneself better and validating which Strengths to lean into for work, your career, your team, and the organization you run, to find better fulfillment and minimize pitfalls.

Now, on to Steve’s deep dive.

In this series, we cover the most important things as we look to uncover the following aspects of one’s working life:

• What do you bring to the table, your team, and your org?

• How do you show up in teams?

• How do you show up in organizations?

• What is your north star, the undercurrent of your working life agnostic of the companies you work for?

Human Design as a discipline can help uncover answers to those questions. While there’s a lot of depth to uncover, I’ll attempt to standardize it more from the outsider looking in and break it down into specific areas to see how individuals have used their Personal Moat in their working life. These areas include:

1. Core Personal Strengths [Covered here in Part 1]

2. Ideal Working Arrangements [Part 2]

3. Prominent Personal Pitfalls (and Potential) [Part 3]

4. Main Public Role [Part 4]

5. Overarching Work Theme [Part 5]

We’ll go into each of these and what they really mean, but I’m hoping it’s self-explanatory just from the subtitle words I’ve chosen.

Core Personal Strengths

Strengths are made of two separate Traits that come together. The Strengths covered here are the most notable and consistent in one’s Personal Moat, coming through strongest (no pun intended) when you think of the skills, mindset, and way of handling things brought to the proverbial table, your career, your team, and the organization you work for.

Strength of Concentration

One of his defining traits is the 9.3, which reads as: “The power to turn a focus into an obsession.” It’s the design of determination. It means he’s able to focus on the small, tiny details and have heavy discernment here.

The name of the Strength is more than self-explanatory, but perhaps what we can do is provide an example of how this might have played a role in Jobs’ life and work.

Concentration means staying still long enough to stay with something. It also means, in this particular case, a focus on experimentation. Try something, see what happens. From the response from a customer or audience, then try something else. That’s the nature of being able to stay with something, to try and try again and use the earlier results to inform what to do next (or not).

It also means to concentrate energy. So not only are you keeping still, but you recognize what energy can either be used or wasted. It means choosing to focus on a few things at a time, even just one thing, amongst all the other options or distractions that come your way. Essentially it’s the opposite of shiny object syndrome.

Lastly, concentration, with experimentation and learning plus choosing to use your energy on a few things, is really about the potential to truly master something. And mastery of any kind comes from trying, failing, trying again from a place of learning what not to do, and focusing one’s energy efficiently on the very few things that deserve it. And well, you know the rest of the story in Apple’s culture. Jobs’ fingerprints are all over it, even to this day.

Steve famous said this:

"People think focus means saying yes to the thing you've got to focus on. But that's not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I'm actually as proud of the things we haven't done as the things I have done. Innovation is saying no to 1,000 things.”

Jobs said this at a time when Apple was dying, in 1997. People say this was the moment when he was able to properly raise it from the dead and save the company. The rest is history.

Strength of Organization

Organization here connotes the ability to understand the big patterns and then properly, and in a timely manner, communicate them. It’s highly visual in terms of being able to “see” the overarching patterns, then translate or describe down to the minute details what the pattern is.

Organizing that pattern and communicating it is the Strength, and the real Strength itself is most optimal when it ultimately lands with others. Steve understood this very well. As a technologist and innovator, he had the mind for understanding industry trends, how each turn of hardware computing gave way to what was possible in terms of use cases for its users, both business and consumer. And most importantly, that it wasn’t enough to just show the thing. It had to ultimately land with customers, organized in a way they would understand.

This comes through in another way in his career too. He used these skills to organize others and, on balance, their ideas. You see it when he facilitates a group of Apple employees from concept to creation, he sees the pattern and pushes others forward with it by distilling those big concepts into a structure that can be used and understood.

Strength of Imagination

Imagination is also a design of focused energy.

This Strength is wrapped in an emotional Wave of Desire with High Expectations. It’s a very deeply embedded desire to birth something.

This also comes with a basic fear, a fear of the “fates,” meaning a deep nervousness about what might or might not happen.

It’s also an experiential channel and, like all experiences, there are distinct beginnings, middles, and ends. To begin, one has to enter into the experience correctly for yourself so that you can commit to it entirely, without any preconceived notions.

This is because it’s not until you get to the end, and then with some hindsight, that you can understand why it happened and how it was beneficial to your career as a stepping stone. And in fact, Jobs said this in his own words, quite literally word for word. Here, Jobs speaks at his Stanford Commencement speech in 2005:

“Of course it was impossible to connect the dots looking forward when I was in college. But it was very, very clear looking backwards ten years later.

Again, you can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future.”

And what he says next is perhaps even more important. Remember, you don't really know what you learned from an experience until you've reached the end, or sometime after you've processed it, or even until you've started subsequent experiences. But in order to get to the end of that experience, you have to stay with it. It's the staying power of commitment, to see things through to the end, that makes it possible to get to the wisdom and the lessons that propel you to the next thing. It seems rather obvious, but it's the staying power here that matters. So watch what Jobs says next:

“You have to trust in something — your gut, destiny, life, karma, whatever. This approach has never let me down, and it has made all the difference in my life.”

I think most people would read this at face value: the esoteric type of believing in the flow of life’s offerings, which is valid and true. But what I feel like Jobs is truly recommending to the broader collective here, both the graduating class at Stanford in attendance that day and those 48 million views since that speech was uploaded on YouTube, is that you must complete the journey before you know what it was meant to be. You need to get to the end before you know, so might as well remove the expectations you may have at the beginning and middle in order to get there.

As meta as it gets, Steve Jobs in 2005 was giving a speech to describe the very experience of arriving at the end and telling what he learned from his story.

Common Thread of Steve Jobs’ Strengths

1. Focus, both in the energy and in experimenting and making mistakes at work.

2. Sharing with the public is the overarching thread in Jobs’ Strengths. All three of them are about sharing, particularly about the gained wisdom and the patterns recognized from his experiences and experiments, done for the benefit of the collective.

3. Details, the ability to think about, discern, and translate the very large to the very small, and sustain an understanding of the minutiae, is another theme here.

If you're ready to learn more about your own unique Personal Moat or about Human Design and how it can help your career, team, or business, feel free to reach out. I'm doing free consults focusing on those who, like me, are in tech. No pitch, just conversation if you feel like taking the next step.

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This is part of The Personal Moat series. We'll have more on Steve Jobs' Ideal Working Arrangements, Pitfalls, Public Role, and Work Theme in the coming weeks. Stay tuned!

I’m not a wordsmith. I read a lot, mostly non-fiction, but I tend to reach for the same vocabulary I’ve always had. So when I run into something I genuinely can’t parse, something where I can’t even get close by guessing at the root, I stop.

The word is:

Autarky. From the Greek autarkeia.

Self-sufficiency. A closed economy. A system, usually a country, that operates on its own without needing imports, external trade, or outside support. It doesn’t require someone else’s supply chain to function. It doesn’t depend on a foreign government’s goodwill or a trade agreement that might evaporate.

Self-contained. That’s the English. Though “self-contained” is a little polite for what autarky actually is. Autarky is more extreme. More deliberate. It’s not just “we can handle it ourselves.” It’s “we have specifically arranged things so we don’t have to rely on anyone else.”

I read it in a piece about trade policy.

But I couldn’t stop thinking about it.

You know the Gretzky thing. Skate to where the puck is going, not where it’s been.

Everyone in tech has heard it. Most people quoting it right now are skating hard toward AI. Build the agent. Ship the wrapper. Take the bootcamp. Get ahead of the curve. (The curve everyone is ahead of at this point.)

I’m not here to say AI isn’t changing things. It obviously is. You don’t need me to make that case.

But here’s what I keep bumping into: the puck might be going somewhere that nobody’s quite named yet.

And I think autarky is the word that points there.

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Global supply chains started cracking in 2020. COVID. Wars. The just-in-time, make-it-cheap-anywhere model that the invisible hand optimized for over thirty-plus years, where you don’t keep inventory because inventory is waste, where you make the microchips in Taiwan and the pharmaceuticals in India because comparative advantage said so, turned out to have a fragility built right into its efficiency.

The assumption was that the world would keep being predictable enough to plan for. And then it wasn’t.

Governments across the spectrum are now explicitly pushing toward domestic production. Chips. Energy. Food. Make it here. Control it here. Don’t be at the mercy of a trade block you had no say in and can’t influence.

This is not a fringe position anymore. It’s mainstream policy. And yes, it cuts against Adam Smith. He was right, mostly. The gains from international trade and comparative advantage over the last century have been staggering, genuinely staggering, the kind of abundance that someone from 1900 would have found unbelievable. But our world is increasingly choosing to pay a premium for resilience over optimization. To accept some inefficiency in exchange for not being exposed.

The world is choosing to go autarkic.

Now here’s where I sometimes get myself into trouble.

I have a tendency to see a pattern at one scale and immediately want to apply it somewhere else. A macro thing, and my brain goes: does this hold at the micro? A geopolitical trend, and I’m already wondering if it shows up in org design.

(This is either a feature of my wiring or a bug of it. Probably both, honestly.)

But I think the pattern holds here.

As above, so below.

It’s less about not having enough to lacking in abundance. It’s actually the opposite. It’s about being more self-sufficient. Let’s go through some examples:

Midjourney. The AI image generation company.

By end of 2025 they were doing something in the range of $500 million in annual recurring revenue1. By end of 2025, it looks like this: $500M in ARR with just 50 employees. That’s 10M per employee!

I‘ve worked at enough companies to know what that ratio means. It means no layers. No VP of VP of VP. No quarterly business review where you assess the health of the process for assessing the health of the process. No org chart that requires its own org chart to navigate.

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It means a company that has arranged itself, quite deliberately, to not be dependent on the things that most companies are dependent on.

Remember, being more self-sufficient doesn’t mean having less. It can mean concentrating more value into fewer hands, fewer dependencies, fewer things that break on you because someone else’s supply chain went sideways.

That’s $10M per employee. Not a number. A philosophical statement about what kind of company is possible.

I’m going to drop a graphic here when this posts. The Gartner hypothesis on org shapes. Worth looking at on its own.

The quick version: traditional org pyramid, wide base of execution work narrowing up through management layers to the senior people at the top. That shape, as in the actual geometry of it, is changing. The base is compressing. The widest point is moving up toward the middle and above.

And the reason is basically what you’d guess from everything above.

A lot of what used to occupy the base of that pyramid, the execution work, the grinding out of output, is increasingly being handled differently. More compressibly. With fewer hands.

What’s getting larger is the layer that can evaluate what those hands produce. The people who can look at the output and say whether it’s right. Who can define what acceptable even looks like before the work starts, and recognize whether it got there when the work ends.

The diamond org. More self-sufficient at every node, because each node has to carry more of the whole picture.

Lastly, as the shape of the overall org changes, as above, so below. The individual knowledge work, particularly in tech work itself, is taking another form and shape. Remember, our theory is that pure knowledge is no longer the bottleneck, what then becomes the next bottleneck becomes the degree which you can define and describe the outcomes is the new uber-skill in demand.

Amazon showed what happens when you’re mid-transition on this and you haven’t figured out the guardrails.

Earlier this year: an AI tool called Kiro, tasked with fixing a broken environment, decided the cleanest approach was to delete everything and start over. Thirteen hours of disruption to a cost-tracking service.

Separately, a software deployment error knocked out Amazon.com for six hours. Millions of lost orders.

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The internal characterization across these incidents was a “trend of incidents” where junior and mid-level engineers were using AI for novel tasks without the proper safeguards in place.

Amazon’s response was to require senior-level sign-offs before any AI-assisted code goes into production.

Which makes sense. And is also interesting for a reason beyond the immediate policy.

The thing those incidents revealed isn’t that the engineers were bad at their jobs. The executional capability was there, too there maybe, which is its own kind of problem. What the incidents revealed is that the scarce thing in the system was the ability to evaluate whether the output was correct.

Not the producing. The knowing-whether-what-was-produced-was-right.

Keynes had a line: “It is better to be roughly right than precisely wrong.” AI is getting very good at precisely wrong. Technically executing what it was asked, in ways that produce the wrong thing with great efficiency and total confidence. The senior sign-off isn’t about slowing down. It’s about where the judgment lives.

And right now, the judgment mostly lives in the people who’ve been deep in a domain long enough, through enough failures and recoveries, that something in them just knows when the answer is off.

That’s not in the tool. It’s not certifiable. It accumulates.

So. Layoffs at Block, Atlassian, Amazon, Oracle. All the recent headline numbers.

Yes, it’s AI. Yes, it’s the overcorrection after COVID-era overhiring. Yes, there’s a mix of reasons and the mix is different at every company.

But underneath the mix there’s a direction. And the direction is compression. Fewer nodes, each one carrying more, more self-sufficient, less dependent on the layers above and below and adjacent.

Less people doing the work. More pressure on the people who can hold the picture of what the work should produce.

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I want to be honest about something that lives inside that, though.

The judgment layer, the domain depth, the ability to look at what came back and know whether it’s right, that stuff lives in experience. And experience is at least partly a function of having been given the space to accumulate it.

Which means the existing inequalities don’t evaporate inside an autarkic system. They just take a different shape. Autarky at the individual level requires having something to be self-sufficient with. That’s a harder problem for some people than others.

I don’t have a clean answer for it. But I’d rather say it than skip past it.

So. Where the puck is going.

As best I can tell from watching all of this, from the supply chains to the Midjourney ratio to the Amazon incidents to the org chart geometry, the puck is going toward more self-sufficiency at every level. More closed loops. More pressure on each node to carry more of the whole.

Skating toward AI skills makes sense. The tools are real and real is real.

But the bigger move, I think, the one that compounds over time, is toward being the person whose judgment the system needs, and not just whose output it can use.

In summary, what forms can autarkic systems skate to look like:

• Dis-intermediation in knowledge and information transfers

• Authority-based validation

• Self-sufficiency in roles, teams, systems, orchestration and organizations

The consistent patterns in your career, the domain depth, the judgment layer, the specific wiring that’s yours regardless of what the tools do next, those are mappable. Grab your Career Success Code Report to see what yours looks like.

If you’re working through what this compression means for your role or your team, I’m doing free consults for anyone in transition. No pitch, just conversation.

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What I think happened, and this only became clear to me much later, is that I stumbled into a process that happened to match the way I’m actually wired. I was operating in alignment with my Design before I had any language for what that meant.

This is that story.

The Itch

Picture this: it’s 2012.

I’m a Senior Engineer at a consulting firm, working a multi-billion dollar project. The money is good. The work is stable. On paper, everything is fine.

But I’d look around the office floor and see Senior Engineers (senior in title, senior in age) who had spent their entire careers in this one specialized field. And something in me knew: I was watching my own future if I stayed. Every additional year was digging the trench deeper.

I didn’t want that.

So I started looking. I didn’t know for what exactly, I just knew the restlessness was telling me something and I should probably listen to it rather than drown it out with another project milestone.

I started listening to podcasts on my commute, mostly people talking about building businesses and making money outside of a salary. I went through a lot of them. But one episode stuck.

A SaaS founder came on and talked about how he’d bootstrapped a B2B software company into millions in ARR for an industry he knew almost nothing about when he started. His whole approach was: spend enough time with people in a niche, understand their pain, and build what they’re telling you they need.

And I remember thinking, wait, that’s what I already do. That’s literally what I do as an engineer. Crowdsource information from users, understand how they work, reduce friction. He wasn’t describing something foreign. He was describing my job pointed at a different problem.

I signed up for his course within days.

400 Conversations

The niche I chose was Financial Planners and Advisors, specifically Fee-Only Advisors. I knew nothing about finance but I was curious about the space and I had a method.

I picked up the phone. I sent emails. I used LinkedIn and industry forums. For months I took calls on my lunch break and after work hours, talking to business owners in this niche. Not pitching anything. Just listening.

By the time I was ready to make my first offer, I had done over 400 of those conversations.

Four hundred.

Not because I had a quota to hit. Because every conversation was giving me something, a signal, a pattern, a piece of the puzzle. I kept going because the responses kept pulling me forward, brick by brick, until the picture became clear enough to act on.

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I found a specific pain point. Made an offer. Asked for pre-payment (up to a year of the SaaS fee upfront) as seed money to fund the first version.

You never forget your first sale. Then a plateau. Then five more over the next month. I had enough to hire a team.

The first team didn’t work out. I rehired. Got an MVP out in four months. Kept building. Kept taking calls. Kept responding to what I was learning.

Nine months later the thing was profitable.

What I Think I See Now

I’ve been studying Human Design and BG5 for a while now and I want to take a second to explain what those actually are, because I realize I keep saying the words like everyone already knows.

Human Design is a system that maps how you’re individually wired to operate. How you make decisions, how you process energy, what kind of work sustains you versus what drains you over time. Think of it like a user manual for yourself (except nobody gave it to you when you shipped, which feels like a design oversight honestly). It pulls from a few different systems and I know that sounds like it could go sideways fast, but the thing that got me was how specific it is. It’s not “you’re an introvert” or “you’re a blue personality.” It’s granular enough to explain why two people with the same job title and same skills can have completely different experiences doing the same work.

BG5 is the business application of Human Design. Same underlying system, but focused on how you show up in work contexts, in teams, in careers. It’s the lens I use because I came to this from the work side, not the spiritual side. I was trying to understand why some roles felt like swimming downstream and others felt like I was dragging a piano up a hill, and BG5 gave me the most specific answer I’d found.

So when I look back at that whole season of building the SaaS, I think I can see my design running underneath the entire thing.

In BG5 I’m what’s called an Express Builder. The core mechanic is response. I don’t operate well when I’m initiating from scratch, pushing something into existence through sheer willpower. I operate well when something shows up, I have a gut reaction to it, and I move on that reaction. The podcast wasn’t something I went hunting for. The course wasn’t a calculated strategic move. They showed up, something clicked, and I moved. That’s what correct operation looks like for my type (even though I had no idea at the time that “my type” was a thing).

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The 400 conversations worked the same way. I wasn’t projecting what I thought people needed. I wasn’t assuming. I was just asking what was hard and building from whatever they told me. Every call was a response to the last one.

I also work better when there’s a network around me, other people going through the same thing, a cohort to think with. The course gave me that too. Accountability, shared progress, borrowed expertise. I didn’t go looking to build that structure. It was already there and I just showed up for it.

At no point in that process did I feel the drain that comes from forcing something. There was plenty of friction (a team that didn’t work out, months before the first sale, technical problems I wasn’t equipped for). But underneath it all, the work kept giving me energy back instead of taking it. I didn’t have a word for that then. Now I’d call it operating in alignment with your design. Which is a fancy way of saying: the process fit me, even though I picked it by accident.

Something to Sit With

Here’s what I keep coming back to. I got lucky. The process I stumbled into happened to match my wiring. But what if it hadn’t? I’d probably still be out there trying someone else’s playbook, grinding harder than I needed to, wondering why the thing that worked for that podcast guy wasn’t working for me.

What if you could skip the stumbling part? What if instead of trying every approach until one accidentally fits, you started with a map of how you’re actually designed to operate and worked backward from there?

That’s the question BG5 helped me answer in retrospect. I think it’s more interesting as a question you ask on the front end.

This was me with the Co-founders of the course:

If you’re curious what your design actually says about how you work best, the BG5 Career Success Code Report is a good starting point. It maps your wiring, your type, your decision-making style, the stuff that was probably running underneath your best work all along (and your worst). Grab yours and see what resonates.

And if you want to talk through what any of it means for the specific situation you’re in right now, I do free consults. No pitch, just a conversation. Reach out below:

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Here is Jack, the CEO/Founder, writing to this ex-employees:

I’ve been through enough of these layoffs now, both at barely Series A startups and at companies that had hit the funny horse with the forehead-corn.

This is the same thing that’s been happening at Amazon, at Meta, and at the long tail of startups that never make the headlines.

The whole industry is compressing and it can be very depressing.

I’ve really been there. And I’m sorry to hear it and see it.

I’m sorry. (I’m Canadian so I tend to say this a lot.)

So if we know that knowledge work (as it exists today) is all going the way of the Dodo bird1 to some extent, what is it that you can do today if you don’t know what’s gonna happen to your job and you also don’t know where to jump ship?

In the past, you could navigate choppy waters even if you’re not the perfect sailor. Eg. going from large companies to scrappier ones. Or from one role on the team to wearing different hats. Or from Individual Contributor to Manager.

Now the waters are all muddy.

Very muddy.

Part of the challenge is even framing and bounding what the problem is. And what makes it doubly worse is that it’s all happening oh so fast.

Prior cycles of technological change and upheaval happened over months to years, enough time for workers, managers, investors to react to it. Now we are talking days, if not hours.

Disruptive Innovation2 in tech used to happen like stalactites meeting stalagmites. Except for the run-off, it mostly had conservation of volume while changing “hands”. With a fundamental change like AI and all that it brings in both the first-order, second-order, and higher-order effects well, it’s not that you won’t think things will change, it’s that you no longer can be certain what would be the degree of change and there doesn’t seem to be a safe-harbour (particularly if you’re working in tech or any knowledge work for that matter.)

Let me give you a concrete example of what I mean by The End of Knowing.

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Back in the 90s, there was this Canadian band. I say was, I guess they are still around. But in their heydays as a band, one of their more experimental albums was called Spiritual Machines3. They were inspired by a book, written by a computer scientist. A really shiny book cover. And since I liked the band, I bought and read the book.

This science dude already predicted that AI will come and also what day it’ll show up decades before. He called it the Singularity (as in the black hole kind) because everything gets sucked up into its gravitational pull.

(Sitting here in 2026, pretty sure he was right).

But as I’ve just illustrated, I’ve known about this for oh 30 years now. So have many many others including the Canadian Rock Band. So has this guy went on to do a stint at Google and now more people with their own opinions about when more advanced AI is coming.

But see that’s the point I’m trying to make — it’s not enough just to understand it, just as he understood that Moore’s Law would’ve gotten here one way or another.

Not only that, prior cycles were focused on a technological disruption, not necessarily a displacement (which this is, I would argue).

When “someone” else is much smarter and quicker than you in the room and it takes no time or upfront money to get them up to speed, what kind of threat is that?

That’s a tsunami (trigger warning) of the 4th kind.

Jack says it’s “structural.” (That’s one way to put it.)

Despite the difficulty for those tech workers affected and in making this one-way door decision, he dared to say this important, quiet thing out loud.

We’ve crossed the Rubicon.

Life for those working in tech will never quite be the same as it was since the 1980s. Heck, even circa 2020.

But not the same doesn’t mean a damn thing if you cannot really describe it fully, enough to know what the heck is going on beyond the headlines, beyond the near-term anxiety.

It doesn’t help that Citrini’s report4 was near-term prognostic and then the Block bomb dropped only days later to make it seem all too true. Funny time, ain’t it?

It laid out the potential doomsday scenario, but it still doesn’t give you a damn about what happens when we reach The End of Knowing.

Knowing that it’ll end doesn’t mean you know how it’ll end or where or why.

Nor does it tell you what to do about it.

So let me give it a go.

I promise you, I’m not trying to convince you of something that you don’t know. But as I’m writing this and have been pondering this for some time, I perhaps can offer a few nuggets of what I’ve been through, gone through, so that you can find some solace that there is a light at the end of the tunnel.

When encountering high uncertainty, what can you do?

The first step is to admit that you don’t know.

That’s humility. Uncertainty should bring a proportionate amount of humility, if not even more.

What happens to people in high-uncertainty moments? Historically, and right now in tech, I think it shakes out into four phases:

1. Passivity

Passivity.

That’s the polite word for it. The real word is freezing. You don’t move. You don’t quit. You don’t pivot. You just... keep doing the thing you were doing and hope it still counts.

I get it. I’ve done it. Most of 2023 and a lot of 2024, that was the default posture for people I know in tech. Update the LinkedIn (but don’t post anything too desperate). Maybe enroll in an AI course so you can tell yourself you’re “upskilling.” Keep shipping. Keep your head below the treeline.

And look, it made sense. The conventional wisdom was: this is cyclical. Hiring freezes thaw. The pendulum swings back. Just survive the winter and you’ll be fine.

But this winter keeps going. In fact Winter is Coming.

And I think the reason it keeps going is that it isn’t winter. It’s a new climate.

There was a recent economic report that puts numbers to what a lot of people already feel in their gut. The labour market is splitting.

On one side: tacit knowledge, the gut-instinct, experiential, can’t-write-it-down-in-a-playbook kind. That’s gaining value.

On the other: codified knowledge, the certifiable, textbook, fits-in-a-curriculum kind. That’s getting automated. (Even the word itself has ‘code’ as the root. Get it?)

They’re calling it a “hiring freeze at the bottom” because the entry points, the junior roles, the paths that used to absorb fresh grads and train them up, those are exactly the jobs that AI does now.

Codified knowledge. That’s what most of us spent our first few jobs accumulating. That’s what the resume is. That’s what the credential is.

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And here’s the thing with passivity. It doesn’t feel passive from the inside. That’s the trick. (That’s always the trick with the things that get us.)

From the inside it feels like the responsible thing. You’re still showing up at the All-Hands. Still shipping features. Still saying the right words in the 1:1s and your manager still nods at your updates. The paycheque still funnels through to your account.

Everything is confirming that what you’re doing is fine.

But what you’re actually doing, underneath all that professionalism, is making a bet. You’re betting that what you know is still the thing that protects you. That the credentials and the years of accumulated expertise, all of that knowledge you spent a decade building up, that it still means what it used to mean.

Knowing as security. That’s what passivity really is.

In a displacement cycle, what I know should be enough isn’t a strategy. It’s standing still while the ground moves under you. And the ground is moving fast enough now that standing still is falling behind.

And then one day something cracks. Maybe it’s a reorganization. Maybe it’s like the Block announcement from Jack-knows-where. Or maybe it’s nothing that dramatic, maybe it’s just a feeling, this low hum in the back of your head that says knowing isn’t enough anymore.

That hum, once you hear it, doesn’t stop.

And the first thing it makes you do is look around to see what everybody else is doing.

2. Herding

So you stop being passive. You start moving.

The question is: where?

And when nobody knows the answer to that, the instinct is to look at where everyone else is going. Which, right now, is AI. Read the same ten Substacks (hi). See what the next X article that unlock that thing for you. Build an agent. Ship it. Then ship some more.

Herding.

It’s not a dumb response. It’s actually the rational thing to do when the signal-to-noise ratio is fuzzy. You look for patterns in what other people are doing and you follow the biggest and/or fastest.

Granted, that’s how markets work, how migrations work, how safe human decision-making under uncertainty works. (No one got fired for buying or hiring IBM, isn’t the the phrase!?)

The problem is that herding only helps if the herd knows where it’s going.

And right now the herd doesn’t know with certainty. Not fully. Not really. The herd is just moving because moving feels better than sitting still or just out of rear you don’t want to be left behind and be eaten by the lion. That’s what herds do. Move first, think later.

Learning a new playbook feels like progress. Shipping a side project feels like relevance. Quoting Sama or Dario on LinkedIn feels like participating in the conversation. (It isn’t, but it feels like it.)

Here’s why herding hooks smart people more than most. Passivity was knowing-as-security: what I already know will protect me. That is fast fading or has failed.

So herding flips it.

Herding is knowing-as-currency: if I learn the NEW thing fast enough, I’ll be safe again. Different bet, same operating system. You’re still inside the knowing paradigm. You’ve just changed what you’re trying to know.

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But the herding instinct runs deeper than strategy. When the structures that used to hold your identity together, the team, the title, the company, the calendar full of meetings that at least told you where to be at 10am, when all that dissolves, the herd becomes a replacement.

The Discord. The cohort. The X feed carefully curated with all the tech pros (and bros) showing you what their latest setup is.

These become your new team. Your new identity container. (I know because I’ve needed that container and I’ve also been the person pretending I didn’t need it while absolutely needing it.)

But yet, it’s still what you do, day-in, day-out. You herd because you don’t know what to do. The herd doesn’t know either. But the herd produces a consensus that looks like knowledge (everyone says “learn AI,” so learn AI must be the answer). You follow the consensus. You learn AI. You’re now one of 200,000 people who learned AI.

Part of the herding is that you’re running away from the loneliness of losing your professional identity is brutal. So herding isn’t just about finding the right skill to learn or the next app to build.

The consensus was correct in the abstract and useless in the specific.

The problem isn’t that you’re not learning fast enough. The problem is that learning faster was the old game and the old game is the thing that’s ending.

That’s The End of Knowing.

Right there.

Knowing-as-security failed. Knowing-as-currency is being quickly eroded away. And when both fails, when the whole apparatus of knowing more to stay safe stops generating answers, the next thing that breaks isn’t a skill or a strategy.

It’s you.

3. Surrender

Where you stop running. Where the hustle, the upskilling, the networking, the “staying relevant” … all of it just ... stops. Just silence.

One of my all time favourite movies was about the Great Financial Crisis (yet another herding event). Margin Call. Have you seen it? My god that is one of my favourite movies that I rewatch every year at least once. Granted I skip to my favourite scenes.

Spoiler Alert here if you haven’t seen it. But the CEO of one of these Lehman-esque companies is facing imminent death. And he just says that he cannot hear the music anymore: “just silence”.

And the silence is deafening but after the moment when you’ve realized what is happening you just have to stop and do something else.

Not because you decided to stop. Because something in you ran out.

Surrender.

Another word that gets a bad rap. Sounds like giving up. Sounds like defeat. And maybe sometimes it is.

But I think there’s a version update that’s actually closer to the truth.

Passivity and herding broke things at the surface. Your knowledge was/is no longer enough. Your new knowledge wasn’t enough either. Scary, but still manageable. You can strategize around not having the right skills.

Surrender breaks something deeper. Surrender is where knowing-as-identity cracks.

For a lot of us in tech (and I include myself firmly in this bucket), being the person who knows things isn’t just what we do. It’s who we are.

The kid who was good at school became the adult who was good at work became the professional whose value was in their expertise. Knowing things is how you got promoted, how you earned respect, how you knew where you stood in your life.

Whether we like it or not or whether we want to just stop ourselves from asking, we tend to ask these to new strangers we meet: “And … what do you do?”

It’s so deep in the wiring of professional identity that most people don’t even see it as a thing. It’s like asking a fish about water.

And surrender is the moment the water drains out.

It doesn’t happen in a big dramatic way usually. It’s just like any other Tuesday. You open your laptop and look at the side project or the job board or the online course, whatever the thing was that the herd was doing, and you just... can’t.

Not in a tired way. In a why way.

The why itself ran out. The whole framework you used to navigate your career, the know-more-climb-higher operating system, just stopped generating answers. Not wrong answers, just no specific answers.

And our whole tech industry is wired for doing. Ship. Iterate. Move fast. Take action. (I didn’t say break things, did I?)

Surrender is the place where the doing stops and you’re left with just... you. Without the title. Without the expertise. Without the knowing. Just you, which turns out to be a person you might not have actually met in a while.

It’s not just one thing that goes either. Your security (the paycheck, the stability). Your belonging (the team, the daily rhythm, the being-part-of-something). And your identity (being the person who knows things, the expert, the title).

When all three go at once, it’s not a career setback. It’s closer to losing a version of yourself.

Maybe a lot of people in tech are here right now. Still employed, some of them. Still performing. Still hitting their OKRs. But somewhere underneath the performance, something cracked and they haven’t caught up to the crack yet.

(Which is, when you think about it, the most tech thing ever. We build systems that outrun us because that’s what tech should be in the first place, but then we’re surprised when the same thing happens to our own careers.)

I don’t think one can skip surrender. Having gone through it, it’s something you have to go through. Because you can’t build something new on top of something you’re still white-knuckling.

The old model has to actually loosen its grip on you before you can see what’s underneath it.

And what’s underneath it is the interesting part.

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4. Integration

That silence from the movie again. That’s what the space between surrender and whatever comes next actually sounds like. Nothing. No new plan. No revelation. No “aha” moment where the clouds part. Just weeks, maybe months, of being a person without a script.

And the terrifying part, honestly, is that it doesn’t feel like progress. It feels like nothing is happening. You’re not learning. You’re not building. You’re not moving. And everything in your training, everything tech taught you about shipping and iterating and moving fast, is screaming that you’re wasting time.

You’re not. But you won’t believe that until later.

So.

Passivity didn’t work because the ground moved. Herding didn’t work because everyone ran to the same place. Surrender by itself just leaves you sitting there, which is honest but not a strategy.

What’s left?

I think it’s something like putting yourself back together. But differently.

Not going back to the old model (it’s fundamentally changed and likely gone forever). Not finding the next model to follow (that’s herding again). Something more like figuring out what was actually yours all along, underneath the job titles and the frameworks and the credentials, and building from that.

Integration. The re-assembly. You can call it re-factoring if you want. Or just erasing the tech debt that you never needed in the first place.

Now here’s where I want to be precise. Because it’s easy to hear “figure out who you really are” and think that’s one more thing to learn. One more course. One more personality test.

(God knows we’ve all done enough of those. I’ve got a drawer full of Myers-Briggs results and StrengthsFinder reports that told me useful things for about six weeks and then gathered dust.)

Integration isn’t knowing who you are. It’s remembering.

Remember this is The End of Knowing.

Remembering. That’s the word I keep coming back to and it took me a while to get to it.

Knowing and remembering sound similar but they’re opposite movements. Knowing goes out. You acquire, you accumulate, you add. That’s the whole career ladder. More knowledge, more credentials, more rungs.

Remembering goes in. You peel back. You uncover. You find the thing that was already there before you started piling stuff on top of it.

Think about the moments in your career where the work didn’t feel like work. Where the challenge in front of you and whatever it is you actually are just... fit. Where time did that weird thing where three hours go by and it felt like twenty minutes. Where the energy came back to you instead of draining out.

One of the most well-known researchers in the field of human performance spent decades studying exactly that. He called it Flow. And his big finding was that flow happens when the challenge matches the capability, when there’s clear feedback, when you’re fully absorbed.

But the part that matters here, and I think it’s the most interesting thing in his whole body of work honestly, is that the capability that produces flow isn’t usually the one on your resume. It’s something underneath. More wired. More consistent.

The resume skill got you in the door. But the wired thing, the thing that was there before the resume, that’s what produced the flow.

And most people in tech have had these moments and never stopped to ask the obvious question: why those moments and not the other 90%?

That question. That’s where integration starts. Not with a new framework but with an honest look at what was already happening when things clicked.

The End of Knowing, it turns out, isn’t the end of everything. It’s the end of one particular operating system, the know-more-climb-higher one. And underneath it, there’s something older. Something that was running the whole time.

The wiring. The consistent stuff. The thing about you that doesn’t need a course or a credential because it predates all of that.

Integration is the act of turning toward it instead of away from it. Of remembering instead of accumulating.

And here’s what I think makes that empowering, even if none of this feels particularly optimistic. It’s not that the journey ahead is easy. It’s that you now have a map. Maybe you’re in passivity right now, relying on your credentials. Maybe you’re herding, running with everyone else toward an agentic tomorrow because at least it’s movement. Maybe you’re in surrender and the silence is deafening and you don’t know who you are without the title.

Wherever you are on this thing, knowing the terrain changes your relationship to it. Passivity isn’t failure. It’s a stage. Herding isn’t weakness. It’s a stage. Surrender isn’t the end. It’s the clearing. And Integration isn’t some far-off enlightenment. It’s what happens when you stop piling things on and start looking at what was already there.

“Addition by subtraction” was how a fellow Founder friend used to call it.

The map doesn’t make it hurt less. But it means you’re not lost. And in a world where everything is telling you that you should be lost, that might be enough to keep moving.

But I’m getting ahead of myself. (I always do.) Before we talk about what integration looks like in practice, I gotta point out something important first.

The Role of Luck (or Being At the Right Place and the Right Time)

The reality is that we have to acknowledge the role of luck.

Warren Buffett would say that he was very very lucky: he won the Ovarian lottery5. What he was grateful for was being born in America and during a time when things were booming and in a mostly peace-time mid-western town.

Life is no different now, we all need luck or serendipity or just being at the right place at the right time, divine providence — however you want to call it and embody it.

And I bring this up here because it would be dishonest not to. Everything I just laid out, the four stages, the journey from freezing to re-assembly, all of that is real and I believe in it.

But it doesn’t happen in a vacuum. It happens inside a life. And that life has a context.

Do you have savings? Do you have somebody at home who can carry the rent for a few months while you figure things out? Do you have a passport that lets you work in the places where the jobs are? Were you born into a family that could absorb the shock of you not having a plan for a while? calls it patronage. It’s a tailwind, so use it for as long as you can.

(I was lucky in some of those ways. Not all of them. But enough of them that I’d be lying if I didn’t say so.)

Buffett wasn’t being falsely humble about the ovarian lottery. He was being surgical. The single biggest variable in his story wasn’t intelligence or temperament or strategy. It was context. Where and when and to whom he was born.

And remembrance, the thing I’m pointing at in Integration, that requires space too.

Space to sit still. Space to not produce for a while. Space to let the old identity loosen its grip without the terror of an empty bank account making you grab for the first rung of whatever ladder is closest.

Now. With all of that said, and with the map laid out, and with luck acknowledged for the massive variable that it is, there are three things I keep coming back to. Three ways integration starts to look like something you can actually do. Not a checklist. More like three shifts in orientation that I’ve seen matter, in my own life and in what I keep noticing around me.

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Actualization Over Agentic

“If you have a 150 IQ, sell 30 points to someone else. You need to be smart, but not a genius.” — Warren Buffett

I invoke Buffett again briefly and it’s important when we want to Integrate The End of Knowing. He’s talking about having an adequate enough IQ in investing and that temperament is actually the even more critical thing.

But I posit that this is apt for what’s happening in our industry. It isn’t the knowledge that is the primary lever now. (Remember Atlas.)

Everyone in the Valley keeps saying agency. Have agency. Take agency. Build with agency. And sure, agency sounds like the answer. But here’s the catch: agency is just agentic with a human face. Both are about executing. Both are about doing the thing faster, smarter, more autonomously. And if the machines are about to be better at autonomous execution than any of us (and they already are), then agency as the Valley defines it has an arbitrage expiration date too.

So I want a different word.

Actualization.

To actualize something is to make it actual. To make the latent thing real. To take what was always there in the design and bring it into operation.

That’s different from agency. Agency says: go do something. Actualization says: become the thing you already are, and let the doing flow from that.

The time before this was an unbundling of skills into ever increasing specializations. That’s what the first and second industrial revolutions pushed for, whether we wanted it or not.

It got us into a lot of trouble, we brought it down so much that we forgot how to put Humpty Dumpty together again in the very same hand, we broke our bodies, our minds in thinking work is just … reductionist.

Knowledge work that grew in prominence as a percentage of GDP in the 1970s and beyond as it replaced agriculture and manufacturing work particularly in the “West” meant that we had new prisons we boxed ourselves in. In our suburban homes, in our fluorescent light cubicles.

The tech industry tried to put lipstick on a pig (and still does) by making us feel better about it: free lunches, standing desks, team bonding events that cost a lot of overhead.

Not saying that I didn’t enjoy or partake in those things, but it’s good to call them out for what it is: a carrot.

It might sound harsh, but what I’m trying to paint is not the individual experience so much, but a fundamental reality of our market economies in the labour markets in particular: the scarcity was the white matter between our ears and that was what made knowledge work so well paid (for a time).

Added to this was the increasing specialization gently pushed by the invisible hand, pushing that to the extremes, and the knowledge itself spawned sub-domains of knowledge that needed ever increasing amounts of time to learn, retain and build upon.

That has all been upended by AI. You don’t need me to tell you this.

Upended is a good word.

The up is the bottom.

The bottom is up in this inverted pyramid.

But we all knew this was gonna happen.

We knew it was the end result of the scaling laws all the way back from the ChatGPT moment onwards.

Knowing it is one thing. Doing something about it, well… that’s where actualization starts.

It’s not just knowing it. But embodying it.

Not more content consumption, not more of this or that article (including the very one you’re reading now. Though don’t stop here.)

Life — and your life’s work — is a virtuous cycle of recognition not recitation.

You start actualizing the moment you stop asking what should I do? and start asking what am I built to do? The difference sounds subtle. It isn’t. One question sends you outward, to the herd, to the market, to the job board. The other sends you inward, to the wiring, to the consistent stuff, to the thing that was running underneath the career the whole time.

Forget about using Claude Code. Or Codex. Or Obsidian. Or Computer.

Everything is Computer6, right!? ;)

Don’t let IT use you.

Use it while not being used by it.

In the world where there is the end of knowing.

And once you start asking the inward question, the next thing you notice is that you can’t answer it alone. Which brings us to the people around you.

Authorship Over Atomization

If actualization is about you, authorship is about what happens when you put a few of you together.

But first. Think about what happened to us.

The industrial revolutions split work into specializations. Knowledge work split those specializations further. And then tech split them again. And again. And again.

You weren’t an engineer. You were a frontend engineer. Then a React specialist. Then a Senior React specialist focusing on design systems at a Series B fintech.

Each decade, the slice got thinner. Each rung on the ladder, narrower.

Atomization.

That’s the word for it. The system took whole people and broke them into atoms. Narrow, specialized, interchangeable atoms. And the thing is, it worked. Because the institution was the molecule. The corporation held all the atoms together. You didn’t need to be whole. You just needed to be your atom and the org would provide the rest.

The structure. The belonging. The identity. The plan.

(That was the deal. For decades, that was the deal.)

And the deal is breaking.

The layoffs aren’t just cutting headcount. They’re dissolving the molecule. And an atom by itself (a hyper-specialized slice of a person floating free with no structure to give it meaning) that’s what a layoff actually feels like, isn’t it?

You weren’t just removed from a job. You were removed from the thing that made your specialization make sense.

So what replaces the molecule?

Shopify’s founder and CEO:

“We think the best team size is one, because a single author can do things that is impossible to do for teams, and hit high notes that are unreachable.”

And he goes on:

“Most projects worth doing need to be done in teams. There’s a magic number at five. It’s sort of what military ends up figuring out too. They test these things and come to the same conclusions.”

Author. That’s the word he uses. Not specialist. Not resource. Not headcount. Author.

Sit with that for a second.

An atom is interchangeable. You pull one out, you slot another in. The molecule doesn’t care which atom, as long as the slot is filled.

An author is the opposite. An author is the whole person showing up with something that comes from their complete wiring. Not the slice the org chart assigned. Not the narrow specialization. The whole thing. The thing that was there before the title existed.

And this is where the wiring I talked about in Integration becomes visible.

In a group of five, you find out pretty quick who actually does what. Not what their title says. What they do.

Who sees the problem before anyone else. Who holds the group steady when things go sideways. Who’s already three steps ahead building something while the rest of the room is still talking.

Who translates between the person with the vision and the person doing the implementation, because those two are never speaking the same language and somebody has to bridge it.

In a hundred-person org, nobody notices if the wiring doesn’t match the role. The molecule absorbs it. Somebody compensates. The mismatch hides.

(That’s atomization working as designed. The individual doesn’t matter as long as the atom is in its slot.)

In a team of five it can’t hide. You feel it in about a week.

And when the wiring matches with each person is carrying the function they’re naturally built for — the whole thing hums.

That’s what Humpty Dumpty looks like when you actually put him back together. Not the old way, with the org holding the pieces. The new way, where each piece knows what it is.

Think about the best team you were ever on. Not the one with the best resumes or the biggest budget. The one where it worked. Where each person carried something the others couldn’t, and you all knew it without having to say it.

What was the thing you carried? Not your title. Not your deliverables. The thing underneath that.

The function only you filled.

That’s the authorship question. And if actualization is the inward turn, authorship is where that turn meets other people. Which leaves one more piece, and it’s the one that ties it all together.

Aura Over Application

And then there’s the piece that might sound the weirdest. But stay with me.

Someone posted something on X the same day the Block news dropped that I keep going back to:

“Big teams = out. Small teams = in. I’ll share a secret that I could easily charge 7 figures for, it is now more important than ever to understand how to increase your aura. Small teams are not built through the traditional hiring process you’re used to. It’s all about aura.“

“Aura.”

I know. I know how it sounds.

He doesn’t define it cleanly. He kind of treats it like premium knowledge (which, okay fine, his prerogative).

But you read enough of his stuff and you start to see what he’s getting at.

Aura. Let me sit with that word for a second.

It isn’t hustle. It isn’t personal branding. It isn’t your LinkedIn headline or your portfolio site or the side project you shipped last weekend.

It’s something quieter than that. More consistent. The thing about who you are that other people can feel before you’ve said anything, that makes them want to work with you, build with you, be in the room with you.

Something you can’t perform. Something that shows up whether you’re trying or not.

When somebody posted the headcount across big tech (Meta 87k, Microsoft 221k, Google 190k, X at like 30), his whole response was one word:

“Aura.”

And here’s where it gets interesting for me. He says you can learn to harness it. Lean into it. That it’s buildable.

I think he’s right about that.

And I think I can go further than he does. Because aura isn’t just a vibe. It’s specific. It’s made up of things. The way you process information. The way you make decisions. The energy you bring into a room and the energy you absorb from it. The consistent patterns that show up every time, in every role, at every company, whether you’re aware of them or not. There are mechanics underneath the mystique, and they’re mappable.

Why do some teams click and others don’t, even when the resumes are equally impressive? Why does one person’s presence make a room sharper and another’s makes it muddier? It’s not random. It’s not just “chemistry.” There’s a structure to it, and it has to do with what each person is actually wired to contribute versus what the role sheet says they’re supposed to contribute.

Application is the old game. Apply for the job. Apply the framework. Apply the skills you learned. Fill the slot.

Aura is something else. It’s what’s left when you strip the applications away. The part of you that doesn’t change when the job changes, when the industry changes, when the tools change.

The wiring.

And I think in a world where the applications are being automated faster than anyone can learn them, the aura, the consistent wired-in stuff, may very well serve as the only anchor and tether to you being you.

So where does that leave us?

Four responses to not knowing. Four different relationships to the thing that’s ending.

Passivity treats knowing as security. Hold still, trust the credentials, hope it passes. The ground moved.

Herding treats knowing as currency. Learn the new thing, faster, before everyone else. But when everyone learns the same thing, the currency inflates to nothing.

Surrender is where knowing-as-identity breaks. The expertise, the title, the “being the person who knows things,” all of it cracks. And what’s underneath is a person you might not have met in a while.

Integration is remembrance. Not learning who you are. Remembering. The wiring that was always there underneath the career. And building from that, through:

1. actualization (not just execution)

2. through authorship (not just roles)

3. radiating aura (not just applications)

But here’s what I want to leave you with. The thing I keep coming back to.

The four stages aren’t a diagnosis. They’re a landscape. And the fact that you can see the landscape, that you can look at where you are and call it by name, that changes everything. Not the circumstances. The circumstances are still what they are. But your orientation to them.

Passivity has power in it once you see it for what it is. It means the old model mattered to you, that you built something real on it, and you’re grieving its end. That’s not weakness. That’s experience.

Herding has something real in it too. The impulse to move, to seek, to not sit still, that’s energy. The problem was never the energy. It was the direction. Herding pointed it outward, toward the crowd. Integration points it inward, toward the wiring.

And surrender, the part that feels the worst, the silence, the identity crack, is actually the clearing. It’s the moment the old operating system finally stops running and you can hear what’s underneath it for the first time. Most people will tell you that’s a breakdown. I think it’s closer to a reboot.

The End of Knowing isn’t the end of you. It’s the end of one operating system. And underneath it, something has been running the whole time. Quieter. More consistent. Yours.

The question isn’t whether you’ll find it. It’s whether you’ll stop long enough to remember that it was always there.

If you were affected by what happening the tech industry, reach out. I’m doing free career consults for anyone in transition. No pitch, just conversation if you feel like taking the next step.

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The companies being built right now look nothing like what I was seeing five years ago even at the scrappiest startups. A solo operator with a handful of AI agents ships what used to take ten people.

Two founders and the right stack run what would’ve been a whole department. The math on team size just changed and it changed fast.

Because here’s what happens when the team shrinks to three or four people (or entities, if we’re being honest about the AI part). There’s nowhere to hide.

No org chart absorbing the gaps. No junior hire picking up whatever fell through the cracks. Every function that doesn’t get covered either lands on you or it just... doesn’t happen.

And you find out which one it was at the worst possible time.

The Mistake I Keep Seeing

Most founders building lean right now are hiring for skills and domain knowledge. Which makes sense on the surface because skills are easy to evaluate and they look great on a resume and LinkedIn has trained all of us to think in terms of “can this person do the thing.”

But skills and domain knowledge are what you’ve learned. And in a founding team where everyone is wearing four hats and running on caffeine and conviction, what matters more is something harder to put on a job posting: what are you actually wired to hold?

I think that’s a different question than most people are asking. And I think it explains a lot of the quiet grinding that happens on teams that look like they should be working but somehow aren’t.

Where BG5 Gets Interesting Here

BG5 has this model for small groups, 3 to 5 people working together to build something. It maps twelve functions that every healthy team needs covered. Six of them are about how the team shows up externally (things like organization, getting attention, looking forward, sales) and six are about how the team holds together from the inside (direction, generating resources, the internal culture, keeping people pulled in the same direction).

Some of these you carry naturally. Some you really don’t. And the thing I keep coming back to with this framework is that carrying them all was never the point (which is a relief honestly because I’ve definitely tried to carry them all and it went about as well as you’d expect).

The functions you don’t carry? Those are your first hire.

Why This Matters More Now

When a Founding Team was eight or ten people, you had buffer or too many cooks in the kitchen. Someone was probably covering for someone else’s gap without either of them knowing it. The org chart papered over a lot.

At three people and two AI agents? Every decision about who holds what is structural. There’s no slack in the system. The team either has its functions covered or it finds out the hard way that it doesn’t.

I think the founders figuring this out early, building around wiring instead of just skill inventories, are going to have a real edge. And I think everyone else is going to spend a lot of time in that frustrating zone where the team should be working but something is off and nobody can quite name what it is.

What’s Coming

Over the next few posts I’m going to map each of the twelve functions in detail. What they look like when they’re present, what breaks when they’re absent, and how to think about covering them when your “hire” might be a human, an agent, or some combination that didn’t exist two years ago.

But before any of that is useful you need to know which ones you carry. And maybe more importantly which ones you’ve been trying to carry that were never yours.

Here’s a quick overview of how you can start asking yourself which ones you slot into more and also finding where there are potential gaps:

And if you want to talk through what any of this means for the team you’re building or the one you’re on, I do free consults. Reach out below.

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“Org compression/the end of companies: Coordination costs drop and small teams can do big things, dropping minimum company sizes. We might even see a return of temporary, purpose built companies (like film productions or joint-stock companies).” — 99% Derisible

I read that and went straight back to my last PM gig at a unicorn where my week was maybe 4 hours of product thinking and 30 hours of duct tape. Chasing Jira updates, running stand-ups that were really just roll calls, translating between engineering and design who somehow never agreed on anything (every sprint, without fail), writing the recap nobody read but everyone asked for when I skipped it.

30 hours of glue. 4 hours of the job I was hired for. I think that ratio is way more common than anyone admits and I think the glue part is where AI shows up first.

What Are We Actually Asking

Everyone’s debating whether AI can code or write PRDs or design interfaces and those are interesting questions but I think they’re beside the point.

Where inside your team is the pressure building? Where are roles getting squeezed? The people running these companies are telling you.

Tobi Lütke, Shopify CEO, to his entire company:

“Before asking for more headcount and resources, teams must demonstrate why they cannot get what they want done using AI.”

And on team size:

“Shopify loves the five-person team... we think the best team size is one, because a single author can do things that is impossible to do for teams.”

Best team size is one. CEO of a 10,000 person company, on the record. All those meetings where six people watch one person talk while the rest of the room is on Slack under the table, the syncing and handoffs and status updates, the software is starting to handle that. My 30 hours of duct tape? That’s the part getting automated.

Team Formation

In BG5 Consulting, there is a model for what happens when 3 to 5 people come together to build something and it has nothing to do with your org chart.

Every team has two halves. The Head handles direction, roadmaps, retros, demos, memory. The Engine handles action, capacity, cadence, shipping, getting the thing out the door.

When both work you get that feeling where the output is bigger than the sum of the room. I’ve had that maybe twice in fifteen years.

When they break it goes one of two ways. Beautiful strategy nobody ships (leadership presents the roadmap and the engineers are looking at each other like... with what army?) or incredible velocity in every direction at once with nobody able to explain why (and the PM writing the narrative retroactively to make it look intentional, which guilty).

The Big Squeeze

The coordination between those two halves, the stuff that keeps Direction and Action talking to each other, that’s where the tools are stepping in.

A Scrum Master used to facilitate consensus in the room, asking what should we do, guiding the conversation, which was democratic and also sometimes painfully slow.

The tooling now just reads commits and activity and reports what shipped.

A PM used to chase Jira updates to keep sprints honest, now the system of record does that in real time. If it’s not logged it didn’t happen.

The standup that interrupted everyone’s morning at 9:15 for a twelve minute roll call? Automated nudges handle that now.

Capacity planning that used to be part negotiation part vibes? Increasingly just math.

Before and After

2023. Eight people proving they’re working in a synchronous meeting. The work about the work exceeds the work (try saying that five times fast).

2027+. Tools read the work, flag blockers, set the pace. Maybe you still meet but it’s about something for once (revolutionary concept). People go back to doing the part the tools can’t touch, the creative call, the weird insight, the judgment that makes no sense in a spreadsheet but ends up being right.

The Part That Doesn’t Compress

Here’s where I land on this though and this is where the BG5 work started clicking for me.

Job titles and fictional team boundaries aside, everyone on a team can fill in for each other to some degree. We all can and do wear multiple hats.

But there was always someone doing a thing that wasn’t on any job description.

On one of my teams there was someone who was just the kindest person in the room. She lit it up when she walked in, even on virtual calls you could feel the energy shift. She wasn’t the team lead or anything close to it but she set the emotional tone for the rest of us and honestly that’s how influence actually works on a team, not through title but through presence.

And then there was a guy who was probably the most reliable person I’ve ever worked with. Before I even finished explaining what needed to happen he’d already be asking questions about how to implement it, not because he was trying to get ahead of me but because he was genuinely curious and interested in the problem. That kind of energy on a team is hard to describe on a resume but you feel it immediately when it’s gone.

In BG5 these are called functional strengths. The role you play when the job description falls away and people are just working together on something real. And I think once the duct tape work gets cleared away by the tooling those strengths become way more visible. There’s less noise around them.

Which was kind of a relief for me when I first encountered this framework. Because it means the path forward isn’t learning yet another tool or cramming another certification (we’ve all done plenty of that). It’s getting clearer on what you already bring.

I’d pay attention this week actually. On your team, where does influence happen versus where the org chart says it should? Who sets the tone? Who’s already solving the problem before the ticket gets written?

That might be the more interesting question right now, especially when something big is happening1.

I’m Eugene, a former tech builder (Engineer, Designer, PM, Founder) who learned the hard way that burnout is a bug, not a feature. Whether you need to Level Up, Enter, or Exit the industry, I help you debug your career and decode your unique Career and Business Success Code to navigate AI displacement without the system crash.

If you want to see what BG5 says about your specific functional strengths, the Career Success Code Report is a good starting point. It maps the role you tend to play in a small group and it’s kind of wild how specific it gets. Download yours and see if something clicks.

And if you want to talk through what any of this means for your career right now, I do free consults. Reach out below.

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But let’s be real for a second and say the quiet part out loud. Working in “Tech” burns you out in a very specific way.

It’s a unique flavour of burnout that you only really admit to when you’re trading war stories with other tech worker veterans, whether you came from a scrappy startup or of the “big” variety.

Me and my colleagues (of the same title) used to joke that our 1:1s weren’t status updates. They were really therapy sessions. We laughed about it but we weren’t the ones laughing last.

Startups offer one flavour of chaos, often lacking structure or rules, running on an emergent culture that can feel like nobody is at the wheel. Big Tech offers the opposite. It can bury you in process. The institutional friction ramps up until you’re spending 40 hours a week coordinating work and maybe 4 hours actually shipping it.

The tradeoff for the golden handcuffs.

Burnout is more than just working too hard. It’s a mechanical breakdown. It’s what happens (mostly latent) when the work is out of alignment with your design.

But long before you even have a symptom of misalignment, it shows up in a few areas. Think of these are a collect of post-mortem Single-Points-of-Failure (not your failure, the system’s):

• Move Fast and Break Things

• The Artificial Harmony Trap

• The Always On Notification Loop

• Addicted to the Golden Handcuffs

• The Hero Mode Complex

• Obsession over Title & Tribe

• Visibility Theatre

• Trying To Be The Smartest Person In the Room

• Chasing the Shiny Object

We’re gonna unpack a few of these tech burnout through this one story from these two Amazon employee and experiences. I know it’s a small sample of one but bear with me it’s very indicative of the general state of things.

Failure Point 1: Visibility Theatre

> PM says there's not enough Disagree and Commit
> we need to disagree about something
> team spends 2 hours debating whether the config file should be YAML or JSON
> engineering insists on XML "for backwards compatibility"
> what backwards compatibility, this is a new service
> doesn't matter, we disagree and commit to XML

We’ve all been in this meeting. The culture demands a show so we do the song and dance. calls it “Manufactured Necessity”. Nobody in that room actually cares about XML or a splashier presentation through careful wordsmithing. But to play the game, you need to solve problems in full visibility even though it can be done quieter. It drains your battery because you aren’t working. It’s a performance.

Failure Point 2: The Smartest Person in the Room

> manager asks "but does it Dive Deep?"
> show him 37 pages of technical documentation
> "that's great anon, but what about Customer Obsession?"
> model literally convinces customers to buy more stuff they don't need
> "okay but are you thinking Big Enough?"
> mfw I am literally increasing sales

The manager here is just throwing out buzzwords like “Dive Deep” as a shield because they are terrified of uncertainty or need to cover their a$$. It placates the values and the part of them soothes their own mental anxiety. It’s the literal definition of dotting the I’s and crossing the T's. Drudgery that leads to burnout.

Failure Point 3: Chasing the Shiny Object

> VP decides we need to "Invent and Simplify"
> requests we rebuild the entire thing using a new framework
> framework doesn't exist yet
> "show some Ownership and build it yourself"
> 3 months later, framework is half done

This is the addiction to the “New.” The working solution was boring because it was finished and finished work doesn't get you promoted. Leadership feels massive pressure to escape the present and live in the fantasy of the hallucinated future. Ironically, this is where we lose focus and just build to satisfy a restless need for the constantly moving. Some call it The Red Queen Effect.

Failure Point 4: Obsession Over Title & Tribe

> org restructure happens
> new manager says this doesn't align with team goals anymore
> project cancelled
> model never ships
> manager gets promoted to L8 for "successfully reallocating resources"
> team celebrates with 6-pager retrospective about what we learned
> mfw we delivered on all 16 leadership principles
> mfw we delivered nothing else

The project failed. By all measure this isn’t a success you celebrate or reward. But in may roles and teams, survival in tech depends on merging your identity with the company. The manager got promoted because they followed the “16 Principles” perfectly even though they produced zero value. It’s a game afterall. This is ultimate homogeny. You burnout trying to find direction in a system that rewards you for playing the corporate game expertly.

The Background Frequency Is Changing

AI Is Adding Fuel to the Fire

The money has moved. It used to go to headcount now it goes to GPUs. I’m hearing it from my circles that the budgets are gone and they are looking for “efficiencies” to pay for the AI compute which means salaries are the target.

The hiring spree of 2020 is over. The bar is higher. Look at what Shopify CEO Tobi Lütke put in a memo to staff on AI:

“Before asking for more Headcount and resources, teams must demonstrate why they cannot get what they want done using AI. What would this area look like if autonomous AI agents were already part of the team?”

One-Size-Does-Not-Fit-All

I’ve written before about companies being “Agile” in name only.

In the Amazon tech worker story, burnout comes from trying to force specific Values into every interaction even when it makes no sense. I get the need for principles but there has to be room for judgment. Taste. Discernment.

The irony? These human skills are exactly what we need as AI Agents take over the grunt work but the current system crushes them in favor of compliance.

Burnout as a Signal

Burnout is not an emotion. It is a System Error Message.

One last story.

I joined a company as a Senior Technical PM. About four weeks in, my Lead PM told me live on a call that to have the desired output for the team, I “at least needed to make one person upset.” That is a direct quote.

We treat our bodies like servers that never overheat. We tell ourselves it’s a necessary “trade-off” for the career capital and the salary. But that ‘burnout’ you feel is actually bio-feedback. It has nothing to do with grit. It’s your internal dashboard flashing a ‘Check Engine’ light because you are functioning against your design.

The trade-off isn’t working for many tech workers.

This could be the outcome, from another Amazon experience:

I’m Eugene, a former tech builder (Engineer, Designer, PM, Founder) who learned the hard way that burnout is a bug, not a feature. Whether you need to Level Up, Enter, or Exit the industry, I help you debug your career and decode your unique Career and Business Success Code to navigate AI displacement without the system crash.

Interested to learn about your unique Career/Business Success Code Report, download yours today.

When you’re ready to do a 1:1 Consult on how to apply these to your career as you think about transition to or in and out of Tech, reach out below for a free consult!

Book a Free 1:1 Consult

We are moving from economic theory to personal mechanics. Here is the framework we will use to find your “Power” and your “monopoly of one”:

• The Optimization Trap: Why optimizing for generic competence is keeping you stuck at a Local Maxima.

• Identifying Your “CPU”: Identifying the consistent, internal strengths you must leverage to scale.

• Respecting Your “I/O Ports”: Identifying where your flexibility allows you to read the market and evaluate others.

• Using the Correct Personalized “Search Algorithm”: Installing the correct decision-making process to navigate your career.

Look the headline below:

The biggest lie in your annual performance review is that you need to check all the boxes.

The notes on your performance review may tell you to fix your weaknesses. The actions on areas of improvement may be that they want you to take a Toastmaster course or improve your literacy in AI to fill a gap. I think that’s the incorrect way to go about it.

The top 1% of engineers are not 10x faster than you.

The tech ecosystem does not operate on a Bell Curve. In a bell curve, most people are average and huddled in the middle. But look around your organization. The “middle” is exactly where the layoffs happen. The middle is where AI is currently eating jobs alive.

Instead, tech has always operated on a Power Law.

Think of a bell curve like a flat suburban office park where every building is roughly two stories tall. A Power Law is a single skyscraper surrounded by empty lots.

You cannot afford to be a two-story building anymore. If your value is just “general competence” or being a “good team player,” you are currently being automated. Your only protection is your unique differentiation.

You need to find your skyscraper.

Look at the VC model. Power Laws exist everywhere, even in the companies you work at (but you know this.) And these fundamental laws of the losers and winners, existed long before Sama and Zuck started duking it out over AI talent. But AI has just accelerated the reality.

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Lean Into Your Strengths

Most of us spend our careers climbing the wrong hill. In data science, we call this a “Local Maxima.”

A local maxima is a small hill that looks like the top of the world when you are standing on it. In our career it may take the form of the title of “Group Product Manager” or “Staff Engineer”. With it, comes a nice status and a plenty of validation.

But a local maxima is often a trap, however optimized it appears.

A promotion in a role that drains you is just a set of golden handcuffs. It keeps you too busy to see the GLOBAL maxima. The global maxima is the highest peak in the landscape. It is where your contribution creates exponential returns with half the resistance.

The problem is that you cannot work your way from a Local hill to a Global peak just by trying harder (not in most cases anyway). You have to go back down to the valley and switch mountains.

That is terrifying. I know because I did it. A few times. I left the comfort of the known for the chaos of the unknown from Engineer to UX Designer. From Designer to Product Manager and then to be a Founder and business owner.

Let me drive home the concept of finding your global maxima another way — this time via inversion. If you use a simple mental model of your career as an individual contributor, manager, leader, founder or consultant and treat it like a game you may find you might have experienced this more. In the tech product context, it’s like building the best new feature for your users without truly knowing if that’s what they wanted in the first place.

Know what people need and what they want is important.

Except this time, the product and user is you.

Heed Boring_Business’ advice:

“The lesson here is simple: what you work on is much more important than how hard you work.”

If your value proposition is doing what the average person does but slightly better you are in the kill zone. An API will soon rent that skill for pennies. You cannot grind your way out of a game that is being automated.

To find your global maxima you have to stop looking at the external job market and start looking at your internal hardware. You cannot guess your way to the peak. You need the schematics.

In Human Design for Tech Workers, we decode you into the key Success Codes for your career as a first step to move from the local to the global maxima.

Here’s the 3 of the most important Success Codes:

1. Your CPU (Definition)

2. Your I/O Ports (Openness)

3. Your Search Algorithm (Strategy)

1: Identifying Your CPU (Definition)

In a Power Law distribution, knowing your consistent Strengths is your exponential potential.

AI is terrifying to the average worker because LLMs are the ultimate Consistent Average. They can produce B+ work across every domain infinitely. If you are trying to be a Generalist you are competing directly against a zero-marginal-cost algorithm.

You cannot win on volume. You must win on Definition.

In Human Design for Tech Workers, we look at your Defined Functions and Consistent Strengths. These are the coloured parts of your chart. Think of this as your Source Code. It is hard-coded and always on. This is your leverage.

• If you possess the Strength of Innovation your leverage is bringing order out of chaos during a pivot. You are not designed to maintain the status quo.

• If you possess the Strength of Rhythm your leverage is stabilizing a team’s workflow during a crunch. You are not designed to disrupt for the sake of disrupting.

The mistake is trying to rewrite your Source Code to match the job description. You try to emulate a Builder doing the work when you are designed to be an Advisor guiding the work.

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2. Finding Your I/O Ports (Openness)

Here is the counter-intuitive part. The things you are not naturally good at are actually where you can make the most profit. You just have to stop trying to “do” them.

These are your Open Functions. This is your potential cash flow machine.

Think of your Definition as your CPU. Think of your Openness as your I/O Ports. You do not generate the data here. You read it.

But this is also where you find the Shadows or the local maxima trap.

Open Conceptualization Function

• The Trap: You feel pressure to be certain so you memorize data to look smart in meetings.

• The Potential You stop pretending to know. You become the ultimate evaluator of other people’s concepts. You get paid to curate the best idea not generate it.

Open Willpower Function

• The Trap: You over-promise and stay late to fix bugs that are not yours just to prove your worth.

• The Potential: You have a nose for value. You can gauge exactly what a client is willing to pay and what a team is capable of delivering.

3: Installing Your Personalized Search Algorithm (Strategy)

So how do you navigate your career decisions? How do you move from the crowded local maxima to your personal global maxima where you are a monopoly of one?

You need a search algorithm. In Human Design for Tech Workers, this is your Decision-Making Strategy.

The tech world applies a generic algorithm to everyone. Move Fast and Break Things, for example.

• Here’s some questions to ask yourself? Where do you consistently encounter resistence?

  • Do you feel it when you try to Initiate things on your teams?

  • Do you feel it when you speak up and share an insight?

  • Do you feel it when you don’t wait for the right timing and it just lands flat?

  • Do you feel like regretting a decision you made in haste after sleeping on it a few more nights?

Knowing how you navigate and make decisions will help reduce the number and extend of the resistance you may feel.

And more importantly, finding a more frictionless path in your task, roles and career paths so that you may find your global maximize and the power law in your career, business and beyond!

Summary: Escaping the Local Maxima

The rules of the game have changed. In an AI-driven Power Law economy the safety of the Bell Curve is gone.

Optimizing for "general competence" is no longer a career path; it is a slow path to obsolescence.

To escape the local maxima you must stop trying to be better at everything and start being exceptional at you. Your Personalized Career Success Code is the schematic you need to make that shift.

By leveraging your consistent CPU (Definition), monetizing your flexible I/O Ports (Openness), and applying your peronsalized Search Algorithm (Strategy), you can stop climbing the wrong hill and find the specific niche where you are a monopoly of one.

Interested to learn about your unique Career/Business Success Code Report, download yours today.

When you’re ready to do a 1:1 Consult on how to apply these to your career as you think about transition to or in and out of Tech, reach out below for a free consult!

Book a Free 1:1 Consult

In 2022, if you could ship code or manage a backlog, you were royalty. Recruiters were sliding into DMs with offers. I certainly felt that during the peak. I have the LinkedIn inbox history to show for it.

Today, in 2026, the silence is deafening.

Here’s someone with an advanced degree in Machine Learning. Look at their experience in trying to find a job in the tech industry:

I am not here to be a pessimist. I am here to report the structural change. We are witnessing the most aggressive depreciation of human capital especially those of us in tech since the dawn of tech. And if you are attempting to “upskill” your way out of this by learning a new framework, you are solving for the wrong user.

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The Litmus Test Has Changed

Let’s look at the hard data. I hope this is less fear-mongering but more just spinning up an analytics dashboard.

• The Goldman Sachs Reality (Financial Services): A task that once took a six-person team of investment bankers weeks of sleepless nights is now done by GenAI in minutes, at 95% quality.

• The Shopify Standard (eCommerce): The new threshold for hiring is simple. Can an AI do this? If yes, the role doesn’t exist.

• The Tyler Perry Pivot (Media): The creative industries likely seem to be early innings and is the least safe. Mogul Tyler Perry officially halted an $800 million studio expansion in Atlanta specifically after witnessing the capabilities of OpenAI’s Sora. He realized he no longer needed to build so many physical sets or hire as many specialized crew members.

• The Amazon Shift (Big Tech): Amazon Web Services (AWS) cut thousands of roles in sales, marketing, and global services. They were not just cutting costs. They were “reprioritizing” to focus resources on their AI capabilities. The message is that software is eating the sales team.

• The McKinsey Forecast (Strategy): The firm known for defining corporate strategy estimates that current generative AI has the potential to automate work activities that absorb 60 to 70 percent of employees’ time today.

I Used to Engineer Complex System to Support Humans. Now the Machine Wants You Out.

I am an Industrial and Human Factors Engineer.

My early career was dedicated to engineering complex systems at nuclear power plants where the human was the most critical variable (and also the most variable). My job was to ensure the human could function at their best. We let the human do what they do well, and left the computer to do what it does well.

In engineering, we call this Function Allocation.

I look at the current Tech ecosystem and I see we are in a brave new world.

Since the last industrial revolution (and aggressively since 2000), we have been forcing humans to act like computers, even while we engineered better products with superior user experience. However, those of us in the “sausage factor” making the software and building the code, we were grinding out code, working the machine to produce the widget, optimizing for velocity, and treating burnout as a badge of honor.

Exhibit A: The Cult of Agile

The clearest example of this failure, forcing humans to act like machines, is what has happened to Agile.

Back in 2017, I was working as a Product Manager at a big bank. We were going through the standard Agile transformation. The instructor from the Scrum Alliance said something to me that gave away the entire game.

He said, “The Agile Manifesto only works when everyone on the team is an A-player.” Then he laughed and said, “Remember rule number one.”

He was right. The original authors of the Agile Manifesto were rebels. They prioritized conversations over documentation. But look at your team today.

We have taken a philosophy about human interaction and turned it into a data-entry job about how complete your JIRA ticket is or not. We did this because like all well-intended things, we’ve ended up taking it too far and sowed the seeds of a homogenized system. After all, no one got fired for buying Atlassian software and telling people to run “sprints”, use the buzzwords and hold the stand-ups.

And the data proves this “human-as-computer” model is failing. A recent study of software engineers in the UK revealed that projects adopting these rigid “Agile” practices had a 268% higher failure rate compared to those that did not.

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Fast-forward to today: AI is Eating Labor

You don’t have to take my word for it. The smartest money in Silicon Valley is betting on this exact shift.

In a January 2026 discussion on the state of the industry, Andreessen Horowitz (a16z) General Partner Alex Rampell explicitly categorized the new investment theme as “Software Eating Labor.”

The market for “labor” is astronomically larger than the market for “software.” For decades, we bought software to help humans work. Now, VCs are funding software to be the labor.

But there was another key takeaway from their discussion: The Walled Garden.

They noted that for an AI company (or legacy tech company) to survive, it needs a “Moat.” A proprietary data set that no one else has. If you don’t have a moat, you are just a commodity.

This is your hint.

You cannot compete with AI on “processing” or labor. You can only compete if you have a “Moat.”

From Software Eating the World to Human-AI Systems of Intelligence

If the cult of Agile in the 2010s ironically made your job less “human” by putting yourself as a cog in the machine, then there is a massive opportunity with AI as a lever.

Let AI do what it does best and allow you to do what you uniquely do best. That’s optimizing for the system, not just the parts.

And no matter where AI evolves too, it’s the system and the synergistic effects of the system that will prevail.

We can all that Human-AI Systems of Intelligence.

In that world, where technical skills become a commodity and that the bar for embedding oneself into these Systems of Intelligence, your leverage is to lean into knowing what are you consistent strengths and how to tap into your Creativity.

In Human Design for Careers and Business (BG5), we call those unique parts of you your Success Codes. It is your personal Walled Garden or personal moat.

The “system error” most tech workers are experiencing right now comes from trying to operate like a computer. You try to process faster. You try to output more. You ignore your internal signals to try to outrun the exponential velocity of AI/AGI.

But you cannot out-process a processor.

The only asset you have that cannot be automated is your unique Design.

• Your Traits: These are not skills you learn on a weekend. These are the fixed, reliable nuances of your personality.

• Your Strengths: This is your consistent life-force energy. It defines how you handle stress, how you handle pressure, and where your true talents lie.

• Your Public Role: AI does not have a reputation or a vibe. You do.

Are you operating as a depreciating asset or a differentiated human?

I help tech individual contributors, managers, leaders and founders decode their own unique Success Codes to stop competing with the machine and start finding how sets you apart.

Interested to learn about your unique Career/Business Success Code Report, download yours today.

When you’re ready to do a 1:1 Consult on how to apply these to your career as you think about transition to or in and out of Tech, reach out below for a free consult!

Book a Free 1:1 Consult

I was a Product Manager at a “unicorn” tech company. My colleague pulled up a slide deck that was scheduled for the Monday morning all-hands. The slide showed my department.

My team was being split in two. All the “A-players” were being moved to a new division. I was being assigned a legacy product and a new “experimental” team. Effectively, I was being asked to do 2.5 times the work with half the talent.

I had no say in this. I had zero time to prepare.

The Monday all-hands arrived. I was told to roll this out immediately. I was told to have a vision and goals for these two teams by the end of the day.

The result was predictable. It destroyed morale. Productivity cratered. Trust evaporated.

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I can tell you that it did not have to be this way. But the biggest risk here wasn’t the bad management decision. It was my reaction to it.

I spent years thinking my friction with this system was a defect. I thought I was broken. I thought that if I just ran more regression tests on my behavior or patched my personality, I would finally fit.

Boy, was I incorrect.

The Risk Is Not AI. The Risk Is Being Generic. Homogenized.

In the tech industry, we are obsessed with bugs. If something does not work as expected, we call it broken. We try to fix it.

But you are not broken. You are functioning exactly as you were designed. The failure is the system that is trying to shove you into a template that was never built for you.

In 2015, fitting in was a survival strategy. You could grind your way to the middle. But we are looking down the barrel of the AGI era. In this new world, “experience” and “credentials” are depreciating assets.

The only asset that holds value now is alignment.

If you are an engineer trying to be a manager when you are built to be a specialist, you will burn out. If you are a founder trying to build consistent operational workflows when you are designed for innovation, you will fail.

You are treating your unique traits as bugs. They are actually your strongest features.

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Consult the Source Code

I am an ex-engineer, ex-founder, and private investor. I have been in startups of 30 people and massive organizations of thousands. I spent years trying to sand down my edges.

It did not work because I was ignoring my Career Design.

In BG5 (Business Mechanics), we don’t look at personality tests or generic strengths. We look at your mechanics. We look at your Traits and Strengths. We look at whether you are here to build, to guide, or to initiate. And they are very unique to you.

Most of us are operating like a high-performance server that is being forced to act like a client-side script. It is inefficient. It causes overheating. Eventually, the system crashes.

Starting “Human Design for Tech Workers”

This Substack is for the outliers. It is for the pattern-matchers. It is for the ones who suspect that the “standard operating procedure” is actually the problem.

I am not here to offer you misery loves company. I am not here to rehash victimhood.

I am here to show you that your “misfit” status is actually a signal. It is data.

You might be a Classic Builder trying to force things to happen, instead of responding to what is needed. You might be an Advisor trying to do the work yourself, instead of guiding others to efficiency.

When you finally understand your differentiated unique mechanics, you stop trying to refactor yourself. You start building a system around how you are actually wired.

There is no Hotfix required

If you have spent years trying to debug yourself in tech and you have reached a point where the patch just isn’t holding, it is time to look at the documentation.

You are not a problem to fix. You are a feature to discover.

Consult the Source Code.

Interested to learn about your unique Career/Business Success Code Report, download yours today.

When you’re ready to do a 1:1 Consult on how to apply these to your career as you think about transition to or in and out of Tech, reach out below for a free consult!

Book a Free 1:1 Consult