However, leaders all suffer from human biases and tendencies, including:

• The tendency for linear thinking and templates in planning (SWOT, vision, mission, values)

• Tendency to reward people similar to themselves in business culture

• A disconnect between how high level business decisions affect people with boots on the ground

To establish a broad understanding on how engineers can lead, I’ve selected five books that cover a large breadth of challenges in the organizational space.

High Output Management

Written by the legendary former CEO of Intel, this is considered the “Bible” of Silicon Valley operations. Andy Grove treats management as a production process, using the “Breakfast Factory” as a metaphor for high-stakes manufacturing.

He establishes a few key responsibilities of managers in high-tech organizations:

• The Concept of Leverage: A manager’s output is the output of their organization plus the neighboring organizations they influence. A managers job is to focus on “High Leverage” activities—those where a small amount of their time produces a large amount of results.

• Task-Relevant Maturity (TRM): There is no one-size-fits-all management style. Depending on the TRM, new people might require hand on training, whereas more experienced people don’t need to be handheld as much. It is the managers job to ensure that people are adequately trained for the job they are in.

Grove observed that all large organizations with a common business purpose eventually become hybrid/matrix organizations with dual reporting to both functional and project managers. This structure allows a huge amount of flexibility to match talent to business needs, but this requires a strong corporate culture to manage dual reporting.

Good Strategy Bad Strategy

Rumelt argues that most “strategy” is actually just “bad strategy”—a collection of buzzwords, goals, and ambition, and the use of templates with vision, mission, and value statements. It is what leaders tend to revert to when they don’t want to deal with tricky fundamentals and risk tradeoffs.

Bad strategy can manifest at higher level positions because of things we tend to perceive and reward in business culture - sales ability, visibility, or pure business knowledge without much technical depth.

“Good strategy” is more intellectual in nature, and involves a “kernel” that consists of three components:

1. A Diagnosis: Defining the nature of the challenge.

2. A Guiding Policy: An overall approach to deal with the obstacles identified.

3. Coherent Actions: Steps coordinated with one another to support the guiding policy.

Good strategy involves viewing the organization as a “chain link” of interconnected functions that are hard to replace. An organization is only as strong as its weakest subunit. In semis, if your EDA tools are world-class but your packaging tech is mediocre, the entire product fails.

To increase performance, you must integrate components more tightly, not just improve them in isolation, so good strategy can involve strategic acquisitions that enhance this chain link.

Good strategy is hard because organizations are resource limited and it can involve choosing between a number of lucrative opportunities. To concentrate on one pivotal objective requires the courage to ignore a dozen other “important” things.

Innovators Solution

Speaking of bad strategy, there are no buzzwords more frequently abused than the words “disruptive” and “innovation” because everyone wants the benefit of these, but few people want to bear the risk involved.

If The Innovator’s Dilemma explained why large companies fail, The Innovator’s Solution explains how companies structure themselves to overcome this dilemma. This books highlights the key difference between conventional business processes which are deliberate, vs innovation processes which are emergent.

It advocated spitting business into into execution and R&D teams:

• Execution teams focus on core revenue generating business with low risk

• R&D teams incubating new ideas and technologies with high risk

On the product side, one core theme as it applies to complex engineering products is the concept of Modular vs. Interdependent Architectures: Early in a product’s life, when performance isn’t “good enough,” interdependent (proprietary) architectures win because they allow for performance optimization and control of all the components. Once performance exceeds market needs, the industry shifts to modular architectures that involves “outsourcing” components with industry-standard interfaces. This can lead to commoditization.

One major topic Christiansen advocates is avoiding the bias to favor “Right stuff Criteria” when evaluating managers for new growth businesses. These are mental heuristics used to evaluate people in corporate contexts among a large body of candidates, such as prestige of the company, the school they went to, whether they are a good communicator, results-oriented, decisive, and have good people skills. However, the downside of “right stuff criteria” is that managers can succeed for reasons not of their own making and the tendency to favor success in low-risk contexts. Instead, potential managers should be asked what problems they have wrestled with in the past.

Christiansen also talks about “good” and “bad” money involved between core revenue generating businesses and innovative businesses. This refers to the risk vs return expectations tied to the money that the shareholder or investor gives. Most corporate finance literature advocate for minimizing risk in the core business since shareholder value is largely tied to it. However, innovation requires risk distributed among a number of “bets”. When a core business sags, “good money” can turn into “bad money” when corporations demand that new ventures become “big, fast”. This “impatient capital” forces startups to bypass the learning phase, often leading to failure.

Thinking in Systems

Humans tend to feel a comfort in linear thinking - of thinking in terms of cause and effect. Frederick Taylor, one of the pioneers of scientific management, strongly advocated for breaking down complex tasks into smaller, specialized roles with rigorously defined processes for each.

However, this type of thinking can narrow ones view to complex interdependencies involved. Semiconductors are perhaps the world’s most complex system of feedback loops not only in the circuit themselves, but within the organization and supply chain.

Donella Meadows provides the tools to understand non-linear cause-and-effect with a few key concepts:

• Stocks, Flows, and Feedback: A system consists of elements (stocks), interconnections (flows), and a purpose. In our industry, the “stock” might be engineering talent or wafer inventory, and the “flow” is the rate of hiring or production.

• Feedback Delays: Because of long lead times in fabs, by the time a problem becomes apparent, it is often too late to solve easily. Leaders must “get the beat” of the system and look for “leverage points” where small shifts in structure cause big changes in behavior.

• The Trap of Sub optimization: When a subsystem (like a specific design team) optimizes for its own goals at the expense of the total system (the final chip’s power/performance), the whole organization suffers.

Reframing Organizations

“Reframing Organizations” by Bolman and Deal is one of the most influential leadership books that is commonly read in top MBA programs.

This book establishes four possible “frames” for leaders to view an organization through. These frames provide a framework for leaders to balance the coordination of the tasks involved with the psychological tendencies and needs of the humans that operate in organizations, including the desire for power and meaning. These four frames include:

1. The Structural Frame (The Factory): Focuses on goals, roles, and technology. It assumes the organization is a machine designed to achieve a specific task.

2. The Human Resource Frame (The Family): Focuses on the relationship between the organization and the people. It assumes that if people feel competent and supported, they are more willing to give more to the company.

3. The Political Frame (The Jungle): Sees the organization as an arena for competition. It recognizes that resources are scarce and power is the primary currency. Leaders here must be negotiators and coalition-builders.

4. The Symbolic Frame (The Theater): Focuses on meaning, ritual, and culture. It recognizes that in a world of ambiguity, people need a “vision” and symbols to give their work purpose.

Having knowledge of these frames allows leaders to be flexible in creating a culture that enables production. It also allow leaders to “reframing” to turn around failing organizations - that is, when organizations are facing issues in, say, structure and politics, leaders can emphasize the human resource and symbolic side to generate enough buy in amongst workers.

Conclusion: The Holistic Leader

Engineering leadership requires having a broad organizational knowledge of how peoples efforts are organized to achieve a goal. They must make decisions and set standards that balance the market needs and the psychology of the people within the organization.

All of the books I mentioned provide a foundational overview into the type of thinking leaders must face. Leaders might be concerned with how projects are being managed from within, the overall business strategy, how innovation is being handled, and whether all the parts of the organizations are being optimized properly.

Top leaders might start their morning in the structural frame (analyzing fab yields), move to the political frame (negotiating with a geopolitical partner), then the human resource frame (understand what motivates your workers to achieve), and end the day in the symbolic frame (rallying the team around a breakthrough).

To lead in this space, semiconductor marketers must possess a rare combination of skills: an understand of what key performance metrics customers are willing to pay a premium for, the ability to translate complex capabilities into business value, a time-to-market instinct, and a holistic grasp of the supply chain involved.

To understand why the industry is shaped the way it is, I have mapped out five foundational books and three key themes from each. Together, they form a cohesive foundation for understanding the move from disruptive innovation to the brutal realities of global economies-of-scale.

This post is designed for readers who want to gain a feel for to “why” the semi value chain is the way it is due to the complex interdependencies. I’ll keep a high level discussion here; refer to the books for more detail.

Innovators Dilemma

Innovation is a trap. Christensen’s core thesis is that “great” companies fail not because they are poorly managed, but because they are too responsive to their most profitable customers. He hits upon three key themes:

• Sustaining vs. Disruptive Innovation: Large incumbents excel at sustaining innovation—incremental improvements for high-margin tiers. However, they often ignore disruptive innovation—low-end, lower-performing tech that eventually scales to intersect and destroy the incumbent’s market.

• The Resource Allocation Trap: In semiconductors, where gross margins of 50%+ are the gold standard, executives are incentivized to “eat their way up” the value chain. This leaves the “bottom” of the market open for new entrants who can scale faster than the incumbents can pivot.

• The “Right Stuff” Bias: Organizations often use “heuristic shortcuts” for hiring and promotion, favoring managers who maximize short-term ROI. However, these are often the wrong people to lead a disruptive unit that needs to focus on learning rather than just execution.

Crossing the Chasm

If Christensen explains why firms fail to innovate, Geoffrey Moore explains why innovations fail to sell. The “Chasm” is the massive psychological gap between Early Adopters (who see the performance benefits) and the Early Majority (who want to follow the market leader). For products to cross this chasm, Moore proposes three key marketing strategies:

• The Beachhead Strategy: In a mainstream market, the early majority delays buying until they see a clear leader. To win, market share, companies must secure a “beachhead”—a specific, referenceable pragmatist customer base that allows them to “own” a niche before expanding.

• The Whole Product Concept: Marketing in semis often fails when engineers tout specs (FLOPs/TOPs) instead of solutions. Pragmatist customers buy the “whole product”—the silicon, the software stack, the documentation, and the support.

• Positioning as a Heuristic: Positioning isn’t about what the product is; it’s about creating a mental shortcut for the buyer that differentiates your product relative to the competition.

  • Example: NVIDIA’s early success wasn’t just about GPU architecture; it was about positioning themselves as the “only way” to play Doom or run professional CAD, creating a marketplace where they were the only reasonable choice.

Fabless: The Transformation of the Semiconductor Industry

This book tracks the “raw” history of how the industry moved from Integrated Device Manufacturers (IDMs) to the specialized, horizontal ecosystem we see today.

• The EDA & IP Revolution: The rise of Electronic Design Automation (Cadence, Synopsys) and reusable IP (ARM) decoupled design from manufacturing. This allowed “Fabless” companies to focus on architecture while outsourcing the capital-intensive fabrication.

• The Rise of “Coopetition”: As technology advances, no single company can do it all. We see increasing interdependencies: Samsung is Apple’s fiercest rival in handsets but its most critical partner in the foundry/supply chain.

• The System-in-a-Package (SiP) Era: We are moving past the “single chip” era. Modern high-end silicon (like FinFET-class chips with 3D memory stacks) requires a massive ecosystem of specialist companies to collaborate just to get a single product to market.

Chip War: The Fight for the world most critical technology

Strategy does not happen in a vacuum. Miller maps the industry through the lens of “Geopolitical Chokepoints”—specific nodes in the supply chain where a single entity holds disproportionate power.

• Mapping the Nodes: The supply chain is concentrated in specific geographies: EUV lithography in the Netherlands (ASML), manufacturing in Taiwan (TSMC), and EDA tools in the U.S.

• The Silicon Shield: Taiwan’s dominance in high-end manufacturing creates a “shield” where the global economy is too dependent on their output to allow for instability.

• Sovereign Silicon: We are seeing a shift where “marketing” a semiconductor company now involves navigating national security interests, as countries race to reverse-engineer, replicate, or replace foreign technology.

Apple in China: The Capture of the Worlds Greatest Company

Apple is the ultimate case study of all the previous concepts clashing in real-time. It is a masterclass in managing the “value network” across geopolitical lines while fighting the “innovator’s dilemma.”

• Zero-Defect Mentality: Apple’s success is built on a “zero-defect” mindset and a brutal Custom Silicon Management (CSM) process. They train suppliers to scale quality, then “pit” rivals against each other to drive down margins.

• The China Challenge: Apple highlights the tension of being a Western company deeply integrated into the Chinese ecosystem. While they benefit from the scale of partners like Foxconn, they face “reverse-engineering” threats from local giants like Huawei.

• Serialization as Control: To maintain their brand and deter bad actors, Apple serializes almost every component. This is a marketing and supply chain tactic to “own” the customer experience—even if it creates friction with right-to-repair advocates.

Conclusion

Understanding the semiconductor market isn’t just about knowing the “what” (the specs); it’s about knowing the “why” and how all the elements (marketing, geopolitics and technology) are interconnected. We see a map of an industry that is simultaneously the most globalized and yet the most protective on earth.

Leave a comment

(Edit: I revised this article on 5/20/26 with sections and much richer insights, including the generational career gap, the compartmentalization in the Manhattan project and why we mistake curiosity for consumption)

I attended ISSCC in 2026, which is the “Olympics” of chip design and one of the most highly specialized conferences in the world. During a plenary talk, Hope Giles, VP HW PM at Apple, emphasized that system thinking and cross domain awareness will become critical skills as semiconductors and technology become more complex.

And I absolutely agree.

However, the advanced nature of technology work nowadays makes it difficult to develop this type of thinking in practice.

I’m writing this post because I notice a huge gap amongst the way job roles and defined nowadays, and the type of cross-domain thinking that is actually a premium as systems become more tightly integrated.

The Generational Career Gap

I’d argue that there is a perspective gap amongst leaders/more senior engineers and junior/mid level engineers nowadays. As companies have gotten bigger and more integrated, the former group have scaled their experience along with the development of the technology. This allowed them to get a much broader perspective of entire systems earlier in their career when they were less complex, and build their career capital through incremental ownership of complex systems.

Now, as systems have become more complex, most job descriptions are specifically tailored toward specific subsystem ownership of more complex systems, not broad ownership of less complex systems. This is causing gaps understanding amongst engineers where they have trouble describing the impacts their role had on the bigger picture.

Why Cross Domain Thinking is Easy to Say but Difficult in Practice

Due to structural and psychological factors, cross-functional awareness is hard to develop in complex technology organizations because it tends to reward specialized subsystem ownership with handoffs at interfaces.

To coordinate peoples efforts in designing a complex product, organizations are set up to flow down requirements to subsystem executors, and later integrated at the end. This is an unfortunate consequence of how we must coordinate work to be able to create complex products that meet performance demands of the market.

Some organizations are especially notorious for keeping information under tightly guarded wraps on a need-to-know basis. For some organizations, this is to prevent IP leaks, while for others, its for national security reasons.

The consequence of this is that big picture assumptions often do not make it to subsystem executors, and can lead to inefficient work being done as information is thrown over the wall. There have been a few times where I’ve asked “can I better understand why you need this?” or “can I sit in a meeting to better understand customer needs” and either told no or gotten spoon-fed information.

• For instance, the Manhattan Project was one of the most heavily compartmentalized efforts in American history. Approximately 130k people worked on the project not knowing they were building a bomb. Only about 10 people knew of the projects purpose. This causes quite a stir amongst physicists like Richard Feynman, who thought it would make people “stupid and incompetent”. Compartmentalization even caused serious risks when workers handed Uranium without knowing what is was intended for. When these workers were read on and understood the purpose, they were able to better handle the uranium.

Cross domain thinking is also difficult psychologically because it requires you to admit to yourself what you don’t know. When you are an expert in a specific area, it often feels like a blow to the ego to not understand material in adjacent domains and to ask someone in that field to explain something simple to them. This requires a huge amount of psychological safety amongst members of an organization, which may not always be present. Not all organizations and teams really emphasize psychological safety or rather treat it as “fluff”.

Of course, businesses need to make money, execution on set priorities is important and information does need to be controlled to some extent.

How to develop Cross Domain Awareness

It can be very difficult and frustrating to develop cross-functional awareness in such environments that rely on sole handoffs at interfaces and deadline pressure. Trust me, I’ve had my experiences.

However, the two most powerful ways to develop cross-functional awareness within such organizations is by cultivating your own curiosity and by teaching others in small ways. Let me explain.

In my experience, which I teach something, whether as a TA in undergrad, mentoring others, or writing dense technical Substack articles, it forces me to consider what the learner doesn’t know. There’s also a risk of me being wrong when I put information out there. This forces me to do a ton of research and filter out complex information to convey what is important for them. In the process, it helps me sharpen my own mental models.

Teaching is more about the process of synthesizing information on your own so that both you and the learner mutually benefit from the information exchange. This is the reasoning behind the old adage, “You remember 90% of the things you teach others”.

Why do we mistake curiosity for consumption?

However, when it comes to tech, the real risk is mistaking curiosity with consumption of information. What do I mean by this?

• Consumption is passive and mindless. When we consume information, such as YouTube videos or Substack articles, we tend to do so because the algorithm effectively lowers the resistance to seek out such information. You might read a nice article describing a complex system and thinking you gained something of value, and you might have indeed if you really focused. But unless you successfully explain to someone like they are 5, you haven’t really learned it.

• Real curiosity, however, is deliberate and requires focus. It forces you to admit to yourself what you don’t know, and force you to seek information to satisfy that curiosity.

When out jobs make us stressed, we tend to resort to consumption and escape at the end of the work day. This is understandable.

However, to develop a broad base of knowledge, we need to actively carve out small chunks of time as “deep work” times to let new material soak in.

How to Cultivate Curiosity

There are several little ways to cultivate your own curiosity. These include:

• Taking advantage of organizational resources.

• Going to the local/university library and look for technical and business resources. Read small units of chapters at a time.

• Attending internal seminars and asking the speaker questions afterwards

• Attending external conferences and reporting back on what you learned

• Asking questions of more senior people like “How did you get to your position”. (In my experience, people enjoy imparting their wisdom, but only if you ask them for it.)

• Reach out to people in other domains in the company and ask them what they do.

One thing that actually helped me cultivate real curiosity outside of work is Brazilian Jiu Jitsu. BJJ is a sport that humbles even the strongest people because in most cases, success is more about leverage and technique than pure strength. As a white belt you might be learning something new every class but not able to use it right away against more skilled opponents. Rolls feel frustrating. However, by continually showing up, you slowly accumulate knowledge little by little and a few months later, you know more than the new guy who just came in.

I personally BJJ is a perfect analogy of how real insight is developed: not through chasing quick trends, but slowly accumulating hard-won insight that compounds over time. When new people show up, you have a platform to share those insights.

Another useful thing that helps is integrating a mindfulness practice in your daily routine to help regulate your nervous system. Even if it helps a bit, it can open up small windows that all you to develop the curiosity needed to let new material soak in.

How to Teach Others

Once you’ve gathered enough insight, there are small ways you can teach others in corporate environments:

• Find ways to offer interesting insight to people during hallway conversations and handoffs at interfaces

• Propose a seminar in your organization about a past problem or conference you’ve been in

• Create internal “lessons learned” and forum posts on things you think would benefit others in the organization

• Find impressionable people, such as early career engineers, and offer to mentor them

You don’t have to go out of your way; just find little moments here and there to add value to others. Run little micro-experiments with people, see what works and doesn’t.

Eventually, these little efforts now can lead to much bigger efforts down the road such as organizing seminars and writing that you and other greatly benefit from. These also lead to visibility that helps during promotion decisions.

In some cases, teaching others may not improve your visibility within the organization. Even in these cases, you still benefit from the preparation that went into knowledge accumulation that can’t be taken away, unlike titles and status. It also helps future proofs your skillset in case the industry can and will take a turn. Trust me, you will want to ensure your skillset is sharp because you never know what will happen.

Conclusion

In my opinion, cultivating curiosity and teaching others around you is more beneficial for both your career and others around you in the longer run. Organizational execution and gaining visibility for promotions is also important, but should not be the sole focus for career success, even when it seems like everyone else is doing it.

Share

For a long time I confused confidence with certainty. I thought confidence was associated with quick answers, strong opinions, and no visible doubt.

There are times where certainty is appropriate when one has done enough research or has the life experience to support that belief.

But some of the most capable people I’ve met sound less certain—not because they’re unsure of themselves, but because they’re listening, asking good questions, and being attentive to the flow of the conversation.

That mismatch sent me down many rabbit holes: why do we keep rewarding who sounds right over who is right?

And that led me to the book “Quiet” by Susan Cain, a gold mine that explains how the extrovert ideal took hold—and what it rewards, and why we confuse confidence with certainty.

What are Introverts and Extroverts”?

Introverts and Extroverts are not about “outgoingness” but about how people gain or expend energy:

• Introverts: tend to prefer deeper, lower stimulation and often think-before-speaking

• Extroverts: tend to prefer external, higher stimulation and often think-by-speaking.

Most people aren’t purely one of the other; it’s a spectrum and context matters.

Unfortunately, we have this misconception that introversion = shyness. It’s not. Shyness is a feeling of discomfort due to fear of negative judgment.

The Extrovert ideal in America: The Cult of Personality

Cain argues that as the U.S. industrialized and urbanized in the 1900s, Americans moved from tight-knit communities of people into a network of strangers.

That shift quietly changes what gets rewarded from “Character” to “Personality”. “Personality” becomes a form of social currency: confidence, charm, verbal ease, a strong point of view delivered cleanly. If you can’t know someone deeply, it helps to quickly signal “I’m competent, trustworthy, and worth listening to.”

This shift from community to network-based activity is where the classic American self-help lineage comes in to help people navigate. Dale Carnegie’s How to Win Friends and Influence People (1936) is basically a manual for social navigation and influence in a world of strangers. This book emphasizes that people develop “extroverted” type behaviors: verbal fluency, likability, and gregariousness, in order to signal competence in an anonymous society.

The Failure Mode: Confidence theater

The problem is that certainty is different from confidence:

1. Certainty = how strongly you believe a claim is true

2. Confidence = the ability to act and adapt under uncertainty—without pretending you know more than you do.

There’s also a difference between earned certainty vs performed certainty:

• Earned certainty = confidence in a claim because evidence/track record supports it

• Performed certainty = certainty as a signal to win status when evidence is thin

Put these definitions together and you get confidence theater:

Confidence theater is performed certainty replacing earned certainty.

In environments with incomplete information—and business is full of it—teams still have to make decisions and move. In meetings and client-facing interactions, there’s real pressure to sound decisive even when the evidence is incomplete.

Earned certainty is healthy when the evidence backs the claim.
But when outcomes can’t be verified quickly, groups start rewarding the signal of certainty—tone, fluency, speed—because it’s easier than verifying who’s actually right. That’s where confidence theater creeps in and starts distorting what we perceive as competence.

Two Ways Confidence Theater Distorts Competence

If a room can’t quickly verify who’s right, it starts rewarding who sounds right.

When people perform confidence theater, we get two predictable distortions:

1. We confuse sales with leadership

   People start treating sales signals—charisma, energy, certainty, smoothness—as the primary proxy for leadership. In that environment, the best “seller of ideas” can get elevated over the best builder of outcomes. But there’s a crucial difference between the two:

   1. Leadership is the art of coordination: coming up with a vision, aligning people around a shared mission, and making high-level decisions that affect people.

   2. Sales is the art of persuasion: understanding a customer’s needs, framing value, and creating conviction.

2. We drown out introverts

   Introverts can be very confident in their ability to synthesize—but they can sound less certain at first because they’re listening, asking clarifying questions, and updating before they commit.

   When a room is performing certainty, it removes the pauses needed for that synthesis. Quiet gets misread as weakness—even when it’s actually judgment.

Where do Introverts and Extroverts Shine

Extroverts and introverts have their strengths and complement each other perfectly.

Introverts often excel at:

• Listening deeply (and asking clarifying questions)

• Synthesizing messy information into a coherent model

• Thinking before speaking

Extroverts often excel at:

• Building verbal rapport and social connection

• Persuasion and motivating action

• Coordinating people toward a decision

Conclusion

There are times where earned certainty is appropriate when evidence and experience support the claim.

The extrovert ideal can cause people to misread introverts as quiet and shy. Even though introverts may not have the quick wit and verbal fluency, that doesn’t mean they aren’t competent; they’re doing the mental work of integrating threads, resolving contradictions, and separating assumptions from facts. All it takes is to listen and ask good questions.

There are takeaways for both extroverted and introverted people:

For extroverted people,

• Allow pauses in group discussion to allow others to speak up

• Listen and ask clarifying questions

• If you notice someone quiet in the room, ask them for their opinion.

For introverted people,

• Ask questions, like “What led to this assumption”

• Find more 1-1 conversations to share insights

• Express your thoughts through writing than speaking

• Find ways to tactfully interject with something

References

Cain, S. (2012). Quiet: The Power of Introverts in a World That Can’t Stop Talking. Crown Publishers.

Everyone talks about innovation, but few organizations actually create the conditions necessary to get it.
Why? Because the same systems that make companies efficient also quietly suffocate the very creativity they claim to value.

In “Loonshots”, Safi Bahcall describes two archetypes inside organizations:

• Artists – the explorers: researchers, architects, tinkerers, and inventors chasing uncertain ideas.

• Soldiers – the executors: teams who scale known ideas into reliable, revenue-generating products.

The problem isn’t that companies have Soldiers.
It’s that as companies grow, they often optimize everything around the Soldier mindset—and accidentally make the Artist mindset unsafe.

The real tension: how failure is treated

The core difference isn’t “creative vs not creative.” It’s the organizational meaning of failure.

• In R&D, failure is expected—and often informative.

• In execution, failure is costly—so it gets minimized.

When those norms spill into each other, something predictable happens:

People stop proposing risky ideas—not because they lack creativity, but because the career cost of being wrong becomes too high.

That’s how you end up with the familiar outcome:

Companies praise innovation in words, but punish it in incentives.

How do you keep ideas fresh inside environments built for predictability?

Bahcall argues that organizations need dedicated spaces for innovation—protected from day-to-day execution pressure—with strong bridges back to execution teams so the best ideas can scale.

In short:

• Innovation teams should be measured on learning.

• Execution teams should be measured on reliability.

When you confuse those scoreboards, you get the worst of both worlds: R&D becomes timid, and execution becomes chaotic.

Practical habits that keep the spark alive (even in execution teams)

Even without a formal formal “innovation lab,” there are “small levers” that change culture if leadership actually prioritizes them:

• Engineer-led seminars – weekly rotating talks that share new concepts keep knowledge flowing.

• Knowledge libraries – a strong collection of technical books and training material to pass down know-how

• Conference paper reviews – ISSCC, APEC, etc. to bring in outside perspective.

• 20% time projects – side projects or friendly competitions can spark new ideas.

One of my favorite examples in an Analog Mixed Signal Design job: I once saw young engineers challenge each other to design a better bandgap reference.

The takeaway

Most companies don’t fail at innovation because they lack smart people.

They fail because they accidentally build systems where:

• predictability is rewarded,

• uncertainty is punished,

• and “learning” is treated as a luxury.

If you want innovation, don’t just ask for ideas.
Build conditions where smart people can explore without betting their careers.

References:

Bahcall, S. (2019). Loonshots: How to nurture the crazy ideas that win wars, cure diseases, and transform industries. St. Martin’s Press.

Most engineering orgs say they value ownership and innovation—but their systems often reward the opposite: compliance, hesitation, and dependency.

I was deeply inspired by L. David Marquet’s Turn the Ship Around! A True Story of Turning Followers Into Leaders. Marquet took command of the USS Santa Fe—then considered one of the Navy’s worst-performing submarines by many measures—and proved that the usual “top-down, give orders” model wasn’t the only way to lead. Instead, he pushed decision-making downward and built a system where the people closest to the work had real control and accountability. The result was a dramatic turnaround in performance, retention, and overall operational excellence.

L. David Marquet’s core insight is simple (and uncomfortable): when leaders make all the decisions, they may get control—but they also train everyone else to stop thinking, and causes talent to atrophy and harder to “build bench strength from within”.

What top-down leadership is (and why it’s so seductive)

In a top-down model, major decisions are made by a leader/manager, then handed down for execution. It can look efficient—especially under time pressure—because:

• one person holds the “map”

• clarity feels high

• accountability appears concentrated

• leaders get rewarded for being decisive

The trap is that over time, followers outsource judgment to authority. And the org quietly becomes less adaptive.

When top-down goes too far: the “induced numbness” problem

When people learn that “the safest move is to wait,” you start seeing predictable behaviors:

• Process becomes the objective. Doing the steps matters more than achieving the outcome.

• “Perfect on first presentation.” People optimize for not getting criticized instead of iterating openly.

• Waiting for permission. Teams delay decisions that could be made locally.

• Ownership collapses at the interfaces. Critical blocks become “someone else’s problem.”

• Silo friction + blame games. Cross-functional groups protect themselves instead of solving together.

This is how you end up with organizations that look busy but move slowly—and require “heroes” to ship.

The core idea from Marquet: push authority down without losing control

Marquet didn’t remove leadership. He changed what leadership does.

1) Replace “permission” with intent Instead of “Can I…?” people say: “I intend to…”

That forces real thinking: the plan, assumptions, tradeoffs, and risks—while still giving the leader a chance to course-correct.

2) Build psychological safety through early, frequent thinking out loud

Frequent 1:1s, short feedback loops, and candid early discussions reduce rework and prevent silent divergence of assumptions.

3) Cut process that doesn’t serve the objective

Too much process numbs initiative and thinking. Too little creates tribal knowledge and chaos. The goal isn’t “less process.” It’s right-sized process that amplifies judgment.

What happens when you do this well

Marquet’s results were dramatic: retention, promotions, performance, and a ship that could operate at a high level even when the captain wasn’t the single point of decision-making.

In corporate terms: you’re building a leadership pipeline and reducing dependence on individual heroes and can build talent from with.

Why organizations struggle to change

These barriers map cleanly onto tech orgs:

• Mindset inertia. Leaders and followers are trained into the old model. Under stress, everyone reverts.

• The seductive pull of control. Many leaders who’ve “played the game” don’t want to easily give up power to followers

• Short-term incentives. Shipping this quarter is rewarded more than building systems that outlast you.

• Skill atrophy. People who’ve been “numbed out” need time + coaching to rebuild judgment muscles.

• It’s not painful enough yet. Change often arrives only after churn, misses, or quality crises.

I think every engineering team can take something from this book—even if your context isn’t a submarine.

What have you seen in your org: top-down control that helped… or top-down control that quietly reduced ownership? Curious where people agree / disagree.

References

Marquet, L. D. (2013). Turn the ship around!: A true story of turning followers into leaders. Portfolio.