books

Book Review: Titanium Noir by Nick Harkaway

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Titanium Noir is a noir novel first, set in an interesting world second. World-building and story take a backseat to tone and genre conventions, which is either a feature or a flaw depending on what you came for.

The main character, Cal Sounder, struck me as somewhat ridiculous: no meaningful background, no real character development, just an embodiment of the noir detective archetype. This is likely intentional, a genre conceit where the detective exists primarily as a lens through which we observe the world.

A Chandler Cast in a Strange City

At its heart, this is a murder mystery. A quiet, private man gets killed, and because the victim is a Titan, Cal Sounder gets the call. He is a private investigator who works closely with police on cases involving Titans, the ultra-wealthy elite made superhuman through repeated doses of the life-extending T7 drug. Most of the book follows Sounder as he navigates a cast of characters lifted straight from Raymond Chandler: a nightclub singer, a corrupt cop, a beautiful but neurotic woman, and so on. The core plot feels secondary to atmosphere and world. There are twists, turns, and some surprisingly violent sections, but the mystery exists in service to the setting rather than the reverse. I enjoyed some of the characters, though the plot itself fades from memory faster than the world Harkaway built around it.

The World of Stasis

What I found most compelling was thinking through the implications of a world ruled by a small cadre of superhuman Titans. They are apart from everyone else in how they look, how they act, and crucially, the time horizons that shape their thinking.

The world they rule is static, and that stasis makes perfect sense. If you intend to be immortal, you want predictability and control. You actively suppress black swan events, like widespread access to T7, because such disruptions threaten your position. This stasis manifests throughout the book: repeated references to 20th century films, archaic computing infrastructure, the absence of mobile phones. Some technologies have clearly advanced, medical facilities most notably, but these directly benefit the Titans.

If I were to construct the backstory, I would imagine T7 invented toward the end of the 20th century, with the Titans consolidating control in the early 21st. This explains the new city where they reside, built fresh for their purposes, while the rest of the world still references Brazil, Greece, Beijing, Mumbai. This is not a colony planet. It is Earth, transformed by Titan influence.

Verdict

A solid 6.5. The world stayed with me; the plot did not. I am not certain I would read a sequel if one arrives, though Harkaway clearly has ideas worth following.

2025: My Year in Books

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Reading kept me sane in 2025. Between two young children, a hectic travel schedule, and an industry in the throes of transformation, books were the constant. These aren’t all the books I read this year, and not all these books were published in 2025. These are just the ones that stuck with me.

Non-Fiction

  • Apple in China: The Capture of the World’s Greatest Company by Patrick McGee
  • Breakneck: China’s Quest to Engineer the Future by Dan Wang
  • The Nvidia Way: Jensen Huang and the Making of a Tech Giant by Tae Kim
  • The Golden Road: How Ancient India Transformed the World by William Dalrymple
  • Destiny Disrupted: A History of the World Through Islamic Eyes by Tamim Ansary

Fiction

  • There Is No Antimemetics Division by qntm
  • Between Two Fires by Christopher Buehlman
  • The Loneliness of Sonia and Sunny by Kiran Desai

Non Fiction

Building the Modern World

One strand of my non-fiction reading this year was understanding how the modern technology ecosystem actually functions. Not the startup mythology or the investor narratives, but the physical reality of how complex devices get designed, manufactured, and shipped.

Reading Apple in China made me realize just how complex the supply chains and manufacturing capabilities required to build devices like iPhones are. Images of Apple engineers spending days and weeks on assembly lines, fine-tuning machines and processes to build the slab of metal and glass in my pocket, stayed with me after I finished the book. McGee’s observations of colorful characters like Foxconn founder Terry Gou gave me an appreciation of the Chinese entrepreneurs who invested alongside Apple, giving us the modern electronics industry.

Breakneck by Dan Wang was an excellent companion piece. Wang contrasts the “engineering-focused” approach of China against the “litigation-focused” approach of the United States. Wang walks factory floors and rides high-speed trains while making a sustained argument about how countries build technological capacity. His comparison of how the two countries approach intellectual property and innovation is particularly sharp.

Tae Kim takes a different approach entirely in The Nvidia Way. Where McGee focuses on systems and supply chains, Kim writes biography. The book is as much about Jensen Huang as it is about Nvidia’s history and culture. Kim traces how Nvidia came to dominate the PC gaming industry before pivoting to AI and the datacenter. The Nvidia story is optimistic: a company that nearly died multiple times, led by an intense and sometimes abrasive founder, that happened to build exactly the right technology at exactly the right moment. If you want to understand why AI development has accelerated so dramatically, understanding Nvidia’s journey helps.

Many Journeys

Another strand of my reading was history. I’ve had a long-standing interest in Indian history, and William Dalrymple’s The Golden Road offered an unexpected view into pre-Mughal, pre-Islamic India. Dalrymple traces how Indian ideas, religions, and material culture spread across Asia and shaped civilizations from Indonesia to Japan.

Perhaps the most interesting part of The Golden Road was Dalrymple’s telling of the Chinese monk Xuanzang’s journey to India to collect authentic Buddhist scriptures. His journey is the basis of Journey to the West, a story that I also enjoyed reading this year. I think Xuanzang’s journey is as interesting and full of intrigue as that of Tang Sanzang in Journey. The India Xuanzang visited was chaotic, with the old Buddhist empires falling apart and the emergence of Hindu and soon Islamic empires. This theme of journeys undertaken in times of chaos is something I came across repeatedly in my reading this year.

Tamim Ansary’s Destiny Disrupted allowed me to fill in the blanks of my own education. In small-town India, the history of Islam is either the glory of Akbar or the tyranny of villains like Timurlane. Destiny Disrupted provided a much wider view of what was happening in the Middle East: the slow fading of the Byzantine empire, the emergence of local powers in Arabia and Central Asia, and the many wonderful characters who play central roles in the spread of Islam.

Next year, I plan to focus on early-medieval Europe and South America.

Fiction

Existential Dread, Cosmic Horror, and a Tender Love Story

I read less fiction than I normally do this year. The three books that stayed with me span genres: science fiction, horror, and literary fiction.

I love science fiction, and qntm’s There Is No Antimemetics Division hit all the right notes. An engaging plot, elements of both hard science fiction and cosmic dread, and a non-linear narrative that rewards attention. The premise involves a secret division of a shadowy organization that fights entities which cannot be remembered. The horror isn’t in the monsters; it’s in the systematic erasure of the knowledge that monsters exist.

Christopher Buehlman’s Between Two Fires is set in a France ravaged by both the Hundred Years’ War and the Black Death. It also has a demonic infestation. Thomas, a disgraced knight, and Delphine, a young girl who may be a saint, journey to a demon-haunted Avignon. Buehlman’s prose is excellent, and his depiction of fourteenth-century France feels genuinely medieval rather than cosplay.

Kiran Desai’s The Loneliness of Sonia and Sunny is a sprawling and beautifully written love story that is also an incisive study of the immigrant experience and an evisceration of upper-class Indian values. The book layers trauma upon trauma: the partition generation still processing displacement decades later, the loneliness and alienation of immigrants far from home, abusive relationships that distort both parties. And yet it remains, at its core, a love story. It’s a hard book to summarize because Desai’s sentences do so much work.

Navigating Chaos

The theme connecting these three fiction books only became clear to me after I finished them. Thomas and Delphine journey through a France that is literally going to hell. Quinn, the protagonist of Antimemetics, repeatedly confronts horrors that erase themselves from memory, forcing her to rediscover threats she has already defeated. Sonia and Sunny navigate changing countries and cultures while growing from passive, somewhat spoilt twenty-somethings into adults with agency, forced to reckon with inherited and inflicted trauma alike.

Each book finds its protagonists in a chaotic world that seems to be coming apart. They cope, they fight, they sometimes fail. The rules keep changing.

I don’t think my fiction choices were accidental.

My Year in Reading

Reading The Nvidia Way and my fiction picks in the same year created an interesting tension. Kim’s book is a story of technological optimism. Jensen Huang bet on parallel computing when the market didn’t exist, nearly bankrupted his company multiple times, and emerged as the most important hardware supplier for the AI revolution. It’s inspiring. It suggests that talent, persistence, and technical insight can build something transformative.

My fiction picks suggest a different mood. The world is confusing. Threats are hard to identify and harder to remember. The rules keep changing. You navigate as best you can.

Both feel true to me. I work in technology. I’ve spent this year helping teams adopt AI tools and watching the capabilities expand month by month. The optimism is warranted. And yet the speed of change creates its own kind of vertigo. The skills I’ve built over two decades may or may not transfer to whatever comes next. The existential dread in my fiction choices probably reflects something real about how I experience this moment.

Note

My love of reading manifested as QuietReads this year, an AI-powered reading tracker I’ve been building. Using it to track and discuss books like The Loneliness of Sonia and Sunny with its AI assistant deepened my appreciation for what Desai was doing. Building something that helps me think about what I read has been its own kind of pleasure. I look forward to working on it in the new year.

The Same Window For Everything

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I’ve been thinking about how I use AI tools lately. They’re clearly useful. What interests me is how the experience feels.

A few nights ago I was reading Kiran Desai’s The Loneliness of Sonia and Sunny and noticed something interesting. There’s a passage where Sonia, reading Anna Karenina, is overcome by a “tingling” sensation:

“Now Sonia could barely read Anna Karenina because when she read, a tingling overcame her, she so wished to be writing it herself. What a tingle, an almost unbearable, sublime tingle, from head to toe. How many millions of observations and moments it had taken to compose this book! Sonia began to make notes, she wrote descriptions of landscapes, snatches of conversations.”

It struck me that Desai might be revealing her own process through this character. Is Sonia a kind of surrogate? Is Desai, through Sonia’s response to Tolstoy, offering a key to how she sees her own craft?

I wanted to think this through. I opened Claude, pasted the passage, and started a conversation. It was genuinely illuminating. Claude pointed out that the passage reads like “a confession barely disguised as characterization.” The specificity of the physical sensation is a giveaway: writers who haven’t felt that particular ache when confronting great work don’t describe it with such precision. And the passage enacts what it describes. Sonia wants to write like Tolstoy; Desai is showing us she can write like someone who wants to write like Tolstoy. It’s recursive. A kind of metacommentary on the work of being a novelist.

The next morning, I used Claude to help with a deployment problem on a project. Same window. Same prompt box. Same conversational cadence.

There’s something strange about this. Claude (especially Opus 4.5) is amazing: a tool that can move fluidly from literary analysis to infrastructure troubleshooting.

But I notice that I bring the same me to both conversations. The same patterns, the same phrasing, the same mental posture. Whether I’m contemplating themes of self-awareness in a novel or investigating why a Lambda function is timing out, I’m using the same application, the same text box.

The platforms know this is a limitation. Claude has Projects. ChatGPT has custom GPTs. Gemini has Gems.

These features exist because context matters. A conversation about books should draw on what I’ve read before, and a conversation about code should know my stack and preferences.

But notice what’s happening: we’re building elaborate scaffolding around general-purpose tools to make them behave like specialized ones. We’re adapting ourselves to the tool. The center of gravity remains the AI interface itself. Everything orbits around it.

Jim Barksdale, the former CEO of Netscape, once said there are only two ways to make money in business: bundling and unbundling. The line came off the cuff at the end of a grueling IPO roadshow in 1995, when a British investment banker asked how Netscape would respond if Microsoft simply bundled a browser into Windows. Barksdale’s throwaway answer became a kind of axiom.

Technology moves in these cycles. The early web was dispersed into countless specialized sites, then concentrated into platforms like Facebook and Google. Craigslist bundled everything (jobs, housing, dating, selling) until startups like Airbnb and Tinder unbundled each category into dedicated experiences.

In that same HBR conversation, Marc Andreessen observed that when underlying technology shifts, the question becomes: if you sat down today with a clean sheet of paper, knowing the technology was changing, what would be the proper form of the product?

AI feels like it’s deep in a concentration phase.

A handful of general-purpose models, a handful of chat interfaces, a shared assumption that the right approach is to build one very capable thing and let users figure out how to apply it.

I’m curious what a dispersion phase looks like for AI.

I want the same powerful models. What I wonder about is AI experiences that are genuinely embedded in specific contexts.

Software where the intelligence isn’t a chat window bolted onto the side, but integral to what you’re trying to do.

When I’m reading Kiran Desai and want to explore whether Sonia is an authorial surrogate, I don’t want to leave the reading experience to talk to an AI. I don’t want to context-switch into a general-purpose tool, paste in a passage, explain what book I’m reading, and then switch back. I want the exploration to feel like part of reading itself. A deepening.

When I’m debugging infrastructure, I probably want something different. A different interface, a different interaction pattern, a different relationship with the underlying model.

The current generation of AI tools has trained us to be good prompt engineers. We’ve learned to provide context, to frame questions well, to work within the constraints of conversational interfaces. We’ve learned to use Projects and memory features to maintain continuity. This is a skill, and it’s valuable.

But are we building habits around what’s available rather than what’s ideal? We’ve gotten so good at adapting to general-purpose tools that we’ve stopped asking whether purpose-built experiences might be better.

Side note: I know there is a vibrant reading community online. There are meetup groups and book clubs IRL which, I am sure, have stimulating conversations. But, I have a full time job. I have young children. I read when everyone is in bed and the house is quiet. So Claude is my reading buddy. For now.

When reading, the conversations that matter most are the contemplative ones. When I wondered about Desai and Sonia, I wasn’t looking for an answer. I was trying to think, to better understand what Desai was trying to do with this passage. This is materially different from asking for a summary or a recommendation.

But those moments of genuine literary exploration get lost in the same interface where I’m debugging code, drafting emails, or planning trips. The conversation about The Loneliness of Sonia and Sunny sits in my chat history between a thread about Python type hints and a thread about project planning.

General-purpose AI is astonishingly good at being general-purpose.

That’s the point. But have we overcorrected? Have we become so enamored with tools that can do anything that we’ve stopped building tools designed to do specific things well?

I don’t have answers yet. I’m building toward something, experimenting with what a more focused AI experience might feel like. But I know that my conversation about Sonia and Tolstoy deserved a different container than my conversation about Docker issues or how to remote-start my minivan.





Playground by Richard Powers

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I read most of “Playground” in a rattly old plane as it shook and juddered over the Atlantic and then the vast emptiness of Russia before landing in New Delhi. I finished the book in a crowded airport, in tears and in awe of what Richard Powers has achieved.

Playground has a beautiful cover

The novel weaves together an exploration of friendship and the games people play with one another, a hypnotic love letter to the ocean, and a deep meditation on technology and meaning. Like memory itself, the story refuses to follow straight lines. Instead, it spirals and circles, guided by a narrator whose version of events becomes increasingly complex and layered as the story unfolds.

At its heart are four people – Todd, Rafi, Ina, and Evie. Todd and Rafi both call Chicago home, but they might as well be from different planets. Todd is wealthy, white, and obsessed with computers; Rafi is poor, African American, and a precocious reader. What bridges their worlds is a shared love of games – chess, Go, and eventually the intricate game of their own peculiar friendship. When they meet Ina in college, their duo becomes a trio, and their lives become permanently entangled in ways that echo across decades.

In contrast stands Evie – a scientist and pioneering diver whose sections contain the book’s most luminous writing. Through her eyes, we discover coral reefs, sunken ships, and manta rays in passages that evoke pure wonder about the ocean’s depths. While others build virtual worlds, Evie explores an actual one, until all four lives ultimately converge on the Pacific island of Makatea – a place strip-mined for phosphate in the 20th century and slowly being reclaimed by jungle. The island stands as a testament to both human intervention and nature’s resilience.

Threading through these human stories runs the history of modern technology and machine learning, embodied in Todd’s journey. He transforms his obsession with computers and gaming into a wildly successful social platform that crosses Reddit with Facebook. But as his success peaks, tragedy strikes – a debilitating neurological disease that leads him to narrate his story to an AI assistant before memory fails. This creates layers of uncertainty about perception and reality that build toward a wonderful (and slightly puzzling) final act that questions what it means to be alive and how technology might reshape our understanding of consciousness and truth.

As a technologist, I found “Playground” to be a powerful lens for examining both my relationship with technology and my feelings about the natural world as we venture deeper into the Anthropocene. The book doesn’t choose sides. Instead, it shows us how the awe inspired by a coral reef and the possibilities of artificial intelligence can coexist, each raising questions about consciousness and reality that the other helps us explore.

If only I could write like Mr Powers

There’s still so much to process in this book. Like the games its characters play, each move reveals new possibilities, new uncertainties to consider. And I’m nowhere near done processing.

Book Review – A Philosophy of Software Design by John Ousterhout

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“A Philosophy of Software Design” by John Ousterhout is a short and thought-provoking book about practical software development.

Key Concept

The book starts with a bold claim – the most critical job of a software engineer is to reduce and manage complexity.

Mr. Ousterhout defines complexity as “anything related to the structure of a software system that makes it hard to understand and modify the system.”

This definition serves as a motivating principle for the book. The author explores where complexity comes from and how to reduce it in a series of short chapters, which often include real-world code examples.

My well-thumbed copy of the book

Summary

The book starts with identifying the symptoms of complexity:

  1. The difficulty in making seemingly simple changes to a system.
  2. Increasing cognitive load – i.e., a developer’s ability to understand a system’s behavior.
  3. The presence of “Unknown unknowns” – undocumented and non-obvious behavior.

Mr. Ousterhout states that there are two leading causes of complexity in a software system:

  1. Dependencies – A given piece of code cannot be understood or modified in isolation
  2. Obscurity – When vital information is not apparent. Obscurity arises due to a need for more consistency in how the code is written and missing documentation.

To reduce complexity, a developer must focus not only on writing correct code (“Tactical Programming”) but also invest time to produce clean designs, and effective comments and fix problems as they arise (“Strategic Programming”).

The book provides several actionable approaches to reducing complexity.

Some highlights:

  • Modular design can help encapsulate complexity, freeing developers to focus on one problem at a time. It is more important for a module to have a simple interface than a simple implementation.
  • Prevent information leakage between modules and write specialized code that implements specific features (once!).
  • Functions (or modules) should be deep – and developers should prioritize sound design over writing short and easy-to-read functions.
  • Consider multiple options when faced with a design decision. Exploring non-obvious solutions before implementing them could result in more performant and less complex code.
  • Writing comments should be part of the design process, and developers should use comments to describe things that are not obvious from the code.

The book concludes with a discussion of trends in software development, including agile development, test-driven development, and object-oriented programming.

Conclusion

“A Philosophy of Software Design” is an opinionated and focused book. It provides a clear view of the challenges of writing good code, which I found valuable.

Mr. Ousterhout provides actionable advice for novice and experienced developers by focusing on code, comments, and modules.

However, the book is also relatively low-level. The book contains little discussion around system design, distributed systems, or effective communication (outside of good code and effective comments).

While books such as “The Pragmatic Programmer” provide a more rounded approach to software engineering, I admire that Mr. Ousterhout sticks to the core concepts in his book.

Book Review: “Artificial Intelligence – A Guide for Thinking Humans” by Melanie Mitchell

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Artificial Intelligence – A Guide For Thinking Humans

Introduction

Melanie Mitchell’s book “Artificial Intelligence – A Guide for Thinking Humans” is a primer on AI, its history, its applications, and where the author sees it going. 

Ms. Mitchell is a scientist and AI researcher who takes a refreshingly skeptical view of the capabilities of today’s machine learning systems. “Artificial Intelligence” has a few technical sections but is written for a general audience. I recommend it for those looking to put the recent advances in AI in the context of the field’s history.

Key Points

“Artificial Intelligence” takes us on a tour of AI – from the mid-20th century, when AI research started in earnest, to the present day. She explains, in straightforward prose, how the different approaches to AI work, including Deep Learning and Machine Learning, based approaches to Natural Language Processing. 

Much of the book covers how modern ML-based approaches to image recognition and natural language processing work “under the hood.” The chapters on AlphaZero and the approaches to game-playing AI are also well-written. I enjoyed these more technical sections, but they could be skimmed for those desiring a broad overview of these systems. 

This book puts advances in neural networks and Deep Learning in the context of historical approaches to AI. The author argues that while machine learning systems are progressing rapidly, their success is still limited to narrow domains. Moreover, AI systems lack common sense and can be easily fooled by adversarial examples. 

Ms. Mitchell’s thesis is that despite advances in machine learning algorithms, the availability of huge amounts of data, and ever-increasing computing power, we remain quite far away from “general purpose Artificial Intelligence.” 

She explains the role that metaphor, analogy, and abstraction play in helping us make sense of the world and how what seems trivial can be impossible for AI models to figure out. She also describes the importance of us learning by observing and being present in the environment. While AI can be trained via games and simulation, their lack of embodiment may be a significant hurdle towards building a general-purpose intelligence.

The book explores the ethical and societal implications of AI and its impact on the workforce and economy.

What Is Missing?

“Artificial Intelligence” was published in 2019 – a couple of years before the explosion in interest in Deep Learning triggered due to ChatGPT and other Large Language Models (LLMs). So, this book does not cover the Transformer models and Attention mechanisms that make LLMs so effective. However, these models also suffer from the same brittleness and sensitivity to adversarial training data that Ms. Mitchell describes in her book. 

Ms. Mitchell has written a recent paper covering large language models and can be viewed as an extension of “Artificial Intelligence.”

Conclusion

AI will significantly impact my career and those of my peers. Software Engineering, Product Management, and People Management are all “Knowledge Work.” And this field will see significant disruption as ML and AI-based approaches start showing up. 

It is easy to get carried away with the hype and excitement. Ms. Mitchell, in her book, proves to be a friendly and rational guide to this massive field. While this book may not cover the most recent advances in the field, it still is a great introduction and primer to Artificial Intelligence. Some parts of the book will make you work, but I still strongly recommend it to those looking for a broader understanding of the field.

The Psychology of Money – Morgan Housel

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The Psychology of Money

I read Morgan Housel’s “The Psychology of Money” towards the end of last year. I found it an insightful book that took a more personal and nuanced look at money and building wealth. It is not a “how to get rich quick book.” 
Its core advice is to take advantage of compounding and take a reasonable approach to risk — hardly rocket science. However, it explores some of the more common pitfalls and anti-patterns when people think of money. 
While I would strongly recommend everyone to read the book — it is fantastic, here is a quick summary of my notes from reading (and enjoying) the book. I hope you find it helpful!

A more personal view of money

People think of money as an abstract. We think about and are taught about money like we are taught physics. We assume that money is governed by rules and laws. Yet, psychology, with its study of emotions and nuance, may offer a better way to think about money.

Most people make financial decisions by taking the information that they have access to and plugging it into their mental model of how the world works. But these mental models are driven profoundly by personal experience.

Mr. Housel’s book takes a personal and intimate approach to understand how money works and illuminates some of the difficulties we face when making money decisions.

How to get rich and stay rich

Compound growth is the key to growing wealth. There is plenty of material available that describes viable strategies for becoming wealthy. However, Mr. Housel states that there is only one way to stay wealthy — “some combination of frugality and paranoia.”

If one can stick around for a long time without wiping out or being forced to give up, the power of compounding comes into play and helps generate wealth.

The key to a successful investment strategy is to not risk what you have and need for what you don’t have and don’t need.

The importance of sensible optimism

Successful investors take an optimistic view that, in the long run, the odds are in their favor, and over time things will balance out to a good outcome even if what happens in between is filled with misery.

But the optimism must be balanced with a healthy dose of paranoia. This means accepting nuance and understanding that the key to exploiting long-term optimism is survival.

It is critical not to get swept up in short-term momentum or get giddy about short-term gains or losses. The most effective long-term strategy is to not get overly influenced by short-term events.

Understanding wealth

When most people think about becoming a millionaire, they think of the ability to spend a million dollars. However, the true meaning of wealth is the ability to deploy money towards living a life that lets you do what you want, when you want, with who you want, where you want, for as long as you want. So, true wealth is financial assets that haven’t yet been converted into consumption.

The ability to save is also critical to building wealth. Savings are a hedge against life’s inevitable ability to surprise the hell out of you at the worst possible moment. The most potent way of increasing savings is not to raise your income but to raise your humility.

Making reasonable financial decisions

Financial decisions making is thought of as making coldly rational decisions in the light of available information and knowledge of the past. However, history is primarily the study of unanticipated events.

Therefore, relying on history as an unassailable guide to the future is risky. It is important to consider the past but to look at it in terms of generalities.

So, one must not be overly influenced by history and take a reasonable and pragmatic approach when making financial decisions. Having savings gives a buffer to absorb short-term volatility. Having a realistic and flexible approach to financial decisions makes it likely to stick with your investment strategy in the long run.

The role of skill and of luck

Money constantly changes returns. If an asset has momentum, a group of short-term traders will assume it will keep moving up. We have seen this play out in recent times with the GameStop saga.

It is not an unreasonable strategy for the short term. Executing such short term strategy doesn’t really require much skill but does need some luck in timing the strategy just right. Plenty of traders both lost and made huge amounts of money trying to time their GameStop trade. It was all about momentum.

The mistake we are susceptible to is focusing solely on what we want to do and have the ability to do. We ignore the plans and skills of others whose decisions might affect our outcomes. We also focus too much on the causal role of skill and neglect the role of luck. This makes us overly confident in our beliefs.

Cultivating Range: Lessons for Startups in a Wicked World

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Introduction

I recently read David Epstein’s book Range: Why Generalists Triumph in a Specialized World. The book focuses on how to cultivate broad thinking strategies to learn effectively. Epstein’s focus is on individuals. As I made my way through the book, I saw that the points made in this book apply equally well to teams.

Range by David Epstein

I work with and advise early stage technology startups. I learnt a lot while reading “Range”. In this post, I explore how the lessons from “Range” can benefit technology startups or teams looking to launch a new product.

Thriving in Wicked Environments

Epstein introduces the concept of Kind and Wicked environments. A chessboard is a kind environment: the rules are clear, and actions are deterministic. Strategies that work in one situation should work well in similar cases. However, in the real world there are feedback loops and second-order consequences that are difficult to predict. It is a rapidly changing Wicked environment. Strategies that worked well in the past can stop working due to changes to the external environment or the market’s reaction to your previous actions.

We see this pattern repeatedly in the world of startups. Ideas that seem destined for success fail because they attempt to solve a problem that is no longer important or serve a market that no longer exists.

To thrive in a Wicked environment, a team may need to take conceptual knowledge from one problem domain and apply it to an entirely new one. The ability to think broadly and to be able to deploy flexible solutions to complex problems could be the difference between a successful product launch and complete failure.

Creating Innovative Products Through Analogical Thinking

Epstein describes Analogical Thinking as —

“The practice of recognizing conceptual similarities in multiple domains or scenarios that may seem to have little in common on the surface.”

Barriers to entry in the information economy are low. While anyone can launch a software product or service, successful companies frequently bring together ideas from different fields to build a compelling product.

Uber brought together logistics, mapping, mobile experiences, and access to an entirely new labor market to create a transformational service. Snowflake’s recent success is another example of a business built on the convergence of industry and technology trends. They successfully executed a simple, in hindsight, idea — cloud-only data warehouses.

Building a Successful Team

In Superforecasting, Philip Tetlock quotes the Greek poet Archilochus: “the fox knows many things, but the hedgehog knows one big thing.” Hedgehogs are specialists — they love to focus on one problem and usually work within their specialty’s confines. Foxes tend to work across various disciplines and work under ambiguity and contradictory conditions.

Epstein cites Tetlock’s research in forecasting and shows that in the face of uncertainty, individual breadth is critical. Similarly, teams that were open-minded and embraced a wide range of experience outperformed teams of narrow specialists.

A Team of Foxes may be more effective in a startup

Early-stage teams need to be open-minded and willing to change their assumptions and pivot when circumstances demand it. As a company matures, it may become useful to include specialists to refine a product and idea. However, having too many specialists at an early stage could lead to tunnel vision.

Choosing a Technology Stack

Gunpei Yokoi was a legendary video game designer at Nintendo. He designed the Game Boy. In Range, Epstein talks about Yokoi’s concept of “Lateral Thinking with Withered Technology.”

The heart of his philosophy was putting cheap, simple technology to use in ways no one else considered. If he could not think more deeply about new technologies, he decided, he would think more broadly about old ones.

You can still see this philosophy in play at Nintendo today.

The Nintendo Gameboy — A Lateral Application of Withered Technology

This lesson is of particular importance for startups with technical founders. It is tempting to be on the cutting edge of technology. But few customers will pay to use a product because it uses a fashionable technology stack. The ability of the company to solve the customer’s problem is way more important.

It may be more productive and faster to build a product using battle-tested, well-understood technology that is quickly and cheaply available. Just like Nintendo, a startup must cultivate a relentless focus on delighting the customer. Technology choices should come second.

Deploying Data Carefully

Startups are encouraged to be data-driven. They optimize for metrics such as customer behavior metrics, sales funnels, infrastructure costs, etc. The danger for the startup here is relying too much on data to make decisions without considering the market or whether the data is relevant to the vision of the company. As Epstein says — the critical question to ask is:

‘Is this the data that we want to make the decision we need to make?’

A dogmatic data-driven approach may lead to doing the same thing in response to the same challenges over and over until the behavior becomes so automatic that it is no longer recognized as a situation-specific tool.

An over-reliance on data can lead to actions that may improve the metrics the team relies on, but may not help the company in the long run to achieve their strategic objectives.

Making the most of External Advisors

Formal or informal advisors can play a critical role to the founding team in a startup. The most effective advisors are outsiders who may be removed from the company’s problem but may help reframe the problem that unlocks the solution.

Epstein notes —

‘A key to creative problem solving is tapping outsiders who use different approaches so that the “home field” for the problem does not end up constraining the solution.’

An outside advisor may offer solutions to a problem the founding team may not even consider because they are too close to the problem.

Knowing when to Give Up

Thirty percent of startups will go under within two years. Fifty percent will fail within five. Running out of money is the most common reason for failure. If a startup keeps trying to execute the same plan despite not gaining traction, it will fail.

Startup culture venerates hard work and not giving up. But here, Epstein provides an essential quote from Seth Godin:

‘We fail when we stick with tasks we don’t have the guts to quit.’

The best, most thought-through plan may fail when it comes up against external conditions — like a global pandemic. Persevering through difficulty can be a competitive advantage, but knowing when to quit can also be a significant strategic advantage. As a startup, it is vital to define and understand the conditions in which it is clear that Plan A has failed, and it is time to try something else.

Conclusion

Building and running a startup is exciting, scary, and can be extremely challenging. It rewards being able to adapt to complex, changing environments. It is vital to pick the right problem to solve, identify the correct tools to solve the problem, and build a team that learns how to make the most of diverse skill sets. Leveraging data and being metric driven can help guide, but must not constrain decision making. Leaning on external advisors and investors is essential to help keep the team grounded and provide different perspectives to solve tricky problems.

Finally, success is not just about persevering through difficult times; it also involves knowing when to quit and when to pivot. A battle may be won simply by disengaging at the right time.

Range is a fantastic book and one that I strongly recommend. The lessons in the book are important not just for individuals but also for teams.