The title says it all: I am an idiot.

It used to be hard to say this. It used to be hard to even think it.

It’s like there’s a trip-wire in my mind. The moment a thought breaches I'm an idiot territory, or even brushes against it with Ugh I'm so bad at this or The only explanation is my stupidity, another thought snaps to attention like a drill sergeant: That's loser-talk, soldier! Drop and give me twenty reframes!

Sometimes a third thought trundles in like an indulgent grandmother: Don’t be ridiculous. You’re wonderful just the way you are. Did you know everyone fails sometimes? Other times, it arrives with the eye-roll of an older sibling: I’m not going to entertain that kind of nonsense. Go for a run. Or eat some Flamin’ Hot Cheetos. Get over yourself.

As all these thoughts engage in a ferocious power struggle, I inhale a bag of Flamin' Hot Cheetos.

Eventually the I am an idiot thought slinks back into the murky depths of my mind, sulking, where it lies in wait, never fully banished.

ii.

I am an idiot about many, many things:

I cannot explain to you the fundamentals of physics, or chemistry, or biology.

My memory for names, dates, and details is so bad I’d be the worst witness at a trial.

Following mathematical proofs exhausts me.

My wit is plodding; I can’t think on my feet.

I use 100 lines when one would do, because the right words elude me.

My mind jumps around like a cricket, unable to enjoy the perfectly good leaf it’s on.

I rarely have conviction. When I do, it's only a matter of time before I'm proven wrong.

Multi-tasking feels like an arcane skill.

I have every intent to follow up on all my texts and messages but rarely do.

With kids, I lecture too much and listen too little.

With adults, I listen too much and contribute too little.

My prediction algorithm is eroding.

My taste is out of date.

My judgment is continually upended.

And yet the world keeps spinning, glittering in its marvels.

iii.

We swim in a world where knowledge is power and competence is currency, especially among achievement-oriented, terminally online, hustler types.

The layman’s dream is to be so good at something that you will make boatloads of money and get oceans of affection. People will admire and want to be you, or curse you because they aren’t. The pulsing heart of this dream is winning. And it’s the smart, hardworking, hungry folks who seem to win. Not the idiots.

I’ve interviewed hundreds of people and not once has anyone said, “You know what, I’m really an idiot.” We’ve learned to launder weakness into strength. I’m slow because I’m thoughtful. I’m abrasive because I’m truth-seeking. Idiocy doesn’t get the same treatment.

But let us look at it, let us really sit with this question:

What’s wrong with being an idiot?

When I examined it, two fears jumped out: that nobody wants to be around an idiot, and that nothing good happens to one.

Strip those away (imagine a world where people sought out idiots and good fortune followed them) and the trait itself would be neutral.

So idiocy is not some inherently negative trait, it’s only so because of its association to rejection and misfortune.

Which brings us to the next question: are those fears true?

iv.

Exhibit A: famous people who have said they were ding-dongs:

Albert Einstein: “I know quite certainly that I myself have no special talent.”

Warren Buffet: “I’ve been an idiot for not buying Amazon.”

Shakespeare: “The fool doth think he is wise, but the wise man knows himself to be a fool.”

Elon Musk: “Starting a car company is idiotic and an electric car company is idiocy squared.”

Confucius: "Real knowledge is to know the extent of one's ignorance.”

Ray Bradbury: “A conglomerate heap of trash, that’s what I am.”

Mark Twain: "I must have a prodigious quantity of mind; it takes me as much as a week sometimes to make it up."

Niels Bohr: "An expert is a person who has made all the mistakes that can be made in a very narrow field."

Charles Darwin: “My power to follow a long and purely abstract train of thought is very limited; and therefore I could never have succeeded with metaphysics or mathematics.”

Socrates: “I know that I know nothing.”

v.

Surely there is a difference between an accomplished person saying they are an idiot, and actually being an idiot. After all, if you are accomplished, you must not be an idiot.

But what is idiocy, really?

Merriam-Webster gives us a foolish or stupid person. Foolish and stupid relative to what, though? To other humans? To the smartest humans? To some imagined ideal?

If Einstein, Shakespeare, and Socrates claim to be idiots, is your judgment so sharp that you are certain these people did not mean what they said? Do you charge them either with false modesty or error in judgment? (If it is an error in judgment, then maybe they really are idiots!)

Recently, Anthropic announced that its latest model, named Mythos, outperforms previous models across the board, but the headline finding is that it managed to find security vulnerabilities in widely-used open-source code that 27 years of human review had not caught.

The machines are getting smarter with every model.

At first, they overpowered us with their calculation speed.

Then, their fluency with the world’s accumulated knowledge passed ours.

Soon, their prediction will sharpen. Their taste will catch up. Their judgment will improve.

I am an idiot, yes. But as time goes on, we all may well be.

vi.

The fear of a thing is often worse than the thing. Most of the suffering lives in the wait.

When I was a kid, an inexperienced ER nurse tried to draw my blood and missed a good dozen times. After that, the sight of a needle would send me into a mess of tears.

At eight, people understood. I got sympathetic looks and lollipops. At eighteen, waiting for travel vaccines before a trip abroad, the sobs that erupted when the nurse walked in with the syringe were more alarming than charming.

The agony was in all the moments before the needle. The whimpering countdown, the anxiety that imagined the incoming poke as a pain of extreme proportions, my body stiffening into a board as the nurse swabbed my arm.

It all bubbled into a hot, bright point of panic before she emptied the syringe and stuck a Band-Aid over it. And then I’d slump over in relief. The worst part, the imagined part, was over.

This was my relationship to needles until the day I learned from my doctor that I was pregnant. Matter-of-factly, she put me on a regular blood-draw routine, unaware of my extreme fears.

I thought to myself, Pregnancy is going to be a bitch if I panic-attack every time a needle comes near. At that moment, something switched in me. I decided to stop being afraid.

At the next appointment, I made myself watch. The needle went in. It was a small pinch, the same one it had always been. It was so anticlimactic.

The thing I’d been afraid of had only ever been a story.

vii.

It’s time I stopped with the fear of being an idiot.

Let me sink into the notion, cozy into it like I would a plush set of slippers.

I’ve been an idiot too many times to count. I’ve blurted out the wrong things, chased the wrong trains, and assumed I actually knew exactly what I was doing.

I suspect I’ll grow even more idiotic, as we ricochet faster and faster into a future none of us can predict.

So call me an idiot. I’ll agree.

Interview me, and I’ll tell you what I really am.

Maybe we’ll find some common ground. Maybe it won’t be so terrible.

There are marvels yet to be discovered in the world. Creative acts that still need pursuing. Pieces of truth still to be assembled. After all, our souls need proof of work.

Whoever said that idiots couldn't be happy? That they couldn't grow content?

It’s only ever a story in our minds.

The Craft Beneath the Craft

Soleio Cuervo has one of the sharpest eyes in design.

He’s hired and mentored some of the best designers in the industry, led foundational work at Facebook and Dropbox, and gone on to invest in a long list of design-led companies. Ask anyone in the design industry if they know Soleio and chances are good that you’ll hear a personal story about how Soleio did them a favor or dropped them a note or helped them learn an invaluable lesson.

One of the things I admire most about Soleio is his ability to spot top-notch design talent. So I set out to ask him: what do you see that others don’t?

What came back to me was a collection of structural distinctions that come out as small differences in posture, ownership, and intent. Like a snowball rolling down a hill, these differences compound into enormous differences in impact.

Below are the contrasts Soleio kept returning to, the ones that explain why some designers plateau while others become indispensable.

1. Okay designers show work. Excellent designers communicate intent.

Most portfolios fail for a simple reason: they assume time and patience that don’t exist.

The reason is simple: hiring managers are not lovingly studying one portfolio at a time, as much as you’d like them to. As Soleio put it, they are often “rummaging through a lot of portfolios in a single block of time,” sometimes scanning “40 or 50 or maybe 100 URLs” in an hour.

Remember this image, because it changes the bar.

In that environment, okay portfolios are tidy grids of projects with generic text. They may be competent. They may even contain strong work. But they require effort before they reward attention. The web is littered with such portfolios, which feel safe and expected.

Excellent portfolios understand the first job is not completeness but rather intrigue.

Soleio compared the experience to rummaging through videos at Blockbuster, quickly scanning for something that feels worth pulling off the shelf. The portfolios that stand out are the ones with “something visceral in their quality” and “a really strong core message or concept.”

That might mean a sharp point of view. It might mean a clear framing of what kind of designer this person is. It might just mean that within one scroll, you can tell what they care about and why you’d want to work with them.

This is also where range matters, but not in the shallow “I’ve done mobile and web” sense. What really stands out is evidence of appetite. Designers like Gabe Valdivia, Nicolas Jitkoff, or Diana Lu, whom Soleio admires, make it easy to grasp both the scope of their work and the type of designer they are within a single scroll.

Portfolios with side projects can signal something even more valuable than competence, but genuine creative hunger. Side projects are “not an example of having free time. It’s more of like an example of having a passion for the work that you do.”

Your portfolio does not need to be a complete documentation of your work, like some kind of museum; it should feel like a trailer that gives an exciting peek into who you are and what you can do.

2. Okay designers tell tidy stories. Excellent designers remember the texture of the pain.

Once you move from the portfolio to the interview, the gap gets easier to spot.

Okay designers recount projects that seem like polished little case studies: the project was important! The team got aligned! Lo and behold, the solution emerged! Then we launched, and good things happened. The end.

Excellent designers remember the mess. The remember what hurt.

“There’s always a degree of hardship, right, to anything excellent,” says Soleio. He compared it to the old Hollywood trope that if you show him a happy set, he’ll show you a bad movie. Great work leaves “residual pain”, and the pain is the more interesting story.

Excellent designers tell you what they tried that didn’t work. What they were initially convinced of and later had to abandon. What got cut. What they versus other people owned and where they disagreed. Which tradeoffs shaped the final outcome.

Soleio put it bluntly: “If it feels like a dance, then they may not have a lot to say about the project and their involvement in it.”

When someone has really lived inside a problem, they can “telescope into the details,” in his words. They can speak to the contours of the work with specificity. They know where their side of the bedroom starts and where someone else’s ends.

This is also where communication quality matters. Soleio finds “an aesthetic in economy”: the ability to take something complex and distill it without flattening it. Excellent designers know how to operate at the right level of abstraction. They can summarize three weeks of work in a crisp way for executives, then go deeper when the room actually needs it. They use demos, visuals, and narrative to shape their intent and know how to maintain “ball control” so the conversation doesn’t rat-hole on the wrong thing.

A polished story may sound impressive. But a story with texture, contexualized to the given environment, is one you can really trust.

3. Okay designers optimize the artifact. Excellent designers optimize the user.

One of the sharpest distinctions Soleio drew was between making a design artifact better and making sure the company is building the right thing in the first place.

He told a painful story from his Facebook days about the Share Bar. Here’s how it worked: when someone clicked an external link from Facebook, the company would wrap the content in an iframe and add a bar at the top to make it easy to comment and share.

The team spent real time refining the mechanics: making sure the underlying URL didn’t break, making the share controls flawless, putting in thoughtful design detail touches.

And then it launched and people hated it.

Why? Because it felt like Facebook was hijacking their web experience. Someone had intentionally shared a link, and now Facebook was intercepting and altering what the recipient saw. In retrospect, the team had optimized a self-serving idea. The issue was not the design of the thing itself, it was the entire premise of the feature.

This is one of the most important lesson of design. It’s so common to get good at refining an idea while losing sight of whether the idea is actually respectful, useful or trustworthy to the user.

Excellent designers have built up a vast bulwark to protect against that drift. They do not just ask, “How do we make this cleaner?” They ask, “Should this exist at all?”

They hold the delicate tension between company strategy, end-user experience, and long-term trust.

4. Okay teams polish early. Excellent teams confront users early.

Soleio shared another painful example from Dropbox’s Carousel, a standalone photo app.

The team invested heavily in the features and polish of the epxerience. But one of the most damning realizations came too late: many users were reluctant to give Dropbox access to their full camera roll because they were worried about eating into their storage quota.

This was not a small onboarding detail, it was a fundamental user concern that could have been surfaced much earlier. Instead, the team discovered it after months of work had already gone into the product. Soleio’s brutal lesson: “If you hide from your users for too long, you’re really going to pay the price.”

This is a key difference between excellent designers and average designers.

It’s so natural to fall in love with the idea as it exists in your head. We want to preserve the fantasy that is in our minds through putting it on paper and perfecting its every edge.

But ideas need frequent collision with reality. Excellent teams force themselves into that kind of contact with user truth while the idea is still cheap to change.

The tragedy of projects like Carousel is not that the team lacked craft; it is that they deployed their craft too late against an incorrect version of reality.

5. Okay designers follow the plan. Excellent designers refuse to delegate impact.

This was the hardest line Soleio drew.

When I asked him how he thinks about the boundary between design and product strategy, he was unequivocal: When designers “delegate impact and strategy to PMs or other people on the team, they cannot ask for the title of excellent.”

That is a very high bar and I believe he’s absolutely right.

Okay designers treat strategy as something outside of their job description. It’s someone else’s job to decide what matters. Their job, as designers, is to make the experience prettier, clearer, more usable.

Excellent designers participate in shaping the why.

Excellent designers ask the questions the PM should ask. They probe into what the customer actually wants. They pressure-test whether the idea is directionally right. They use design not just to execute decisions, but to help make them. Soleio described design as one of the few disciplines that can give “extraordinary definition to the what if.”

This is also why so many founders misdiagnose design problems. Sometimes the issue is not the designers at all.

When a CEO asks him whether their design team is excellent, Soleio often starts with a different question: “If I joined your team for a month, what would I work on?” It is a diagnostic for whether leadership itself can articulate a clear strategy and intended outcome. If the CEO cannot do that crisply, it is unrealistic to expect the design team downstream to somehow compensate for the vagueness.

At the same time, he sees a very common anti-pattern: designers treated as production resources, brought in at the tail end of decisions, staffed across too many projects, given little say in prioritization, and then blamed for being slow or for “not being strategic.” In that environment, even very strong designers can look weak.

Excellence in design is not just about craft quality. It is about whether a designer is both willing and allowed to create impact.

6. Okay designers seek consensus. Excellent designers ask for the ball.

When a project has too many stakeholders and too many opinions, design can get mushy fast.

Okay designers try to satisfy everyone. They collect all the feedback, soften every edge, and slowly back into compromise.

Excellent designers do something harder.

They synthesize the input, choose a direction, explain why, and accept accountability for the result. As Soleio frames it: sometimes you just have to “ask for the ball.”

You have to say what direction you’re going to move toward, call your own shot, ask for trust, and own that outcome.

His favorite personal example was the redesign of Facebook Groups in 2010. The team had roughly 90 days to ship, too many cooks in the kitchen, and no shortage of opinions about what the product should become. A more consensus-driven approach could easily have stretched the project into six months or a year.

Instead, Soleio felt he had to step forward and say, in effect: trust me, this is the direction, and the most important thing right now is to get it out the door. They could layer in improvements later, but first they had to “crash the beaches” and get into production.

I love the accountability embedded in those words: trust me. It isn’t earned by virtue of having ‘designer’ in the title. It’s asked for. And in order to make the ask, you have to own the outcome.

Trust me, and hold me accountable if I’m wrong.

That willingness to absorb responsibility is one of the clearest signs of mastery.

7. Okay designers think in screens. Excellent designers think in systems, story, and worlds.

When I asked Soleio what feels different about design excellence today, in the era of AI, he gave me such a thoughtful answer that I’ve thought about it multiple times since then.

The biggest shift, in his mind, is that we now live in a world where our tools allow very small teams to create work with much more range and coherence than ever before. AI-modern teams can now share “a spirit to every release.”

Now, a tiny team can launch across web, mobile, and new surfaces, and still make it feel like one idea expressed in unison across many forms. For Soleio, excellence is no longer about just polishing the X-wing, but building the entire Star Wars universe around it.

While AI will get better at the craft of design, the larger opportunity for Soleio is the empowerment of humans in moving up a level: toward full world-building. He suggests that tomorrow’s great designers may not come from traditional design training at all; they may be folks with strong instincts for narrative and experience-building, who can use these new tools to create things that feel both useful and alive.

The future of design excellence is getting rewritten; it’s less about who can push pixels best and more about who can create the most compelling and coherent universe for those pixels to live inside.

What separates okay design from excellent design?

Across these seven contrasts, one thing stood out to me:

Excellent designers do not stay in the lane they were assigned when the work demands more of them.

They don’t just make the artifact cleaner.

They don’t just present polished stories.

They don’t just execute someone else’s strategy.

They don’t just accommodate the room.

They care about intent. They care about users more than the work. They care about learning early. They care about ownership. And when the moment calls for it, they ask for the ball.

Okay design improves what is put in front of it.

Excellent design changes what is possible.

“Seeing” excellence

Your hand can never draw better than your eye can discern.

They say that mallard ducks can see 100 million more color combinations than humans can. I think this is true also of a master versus an novice.

A 10x-builder looks at the world differently than a 1x-builder. A pro can zoom into the nuanced details of a piece of code, a design, a headline, and see many more possibilities than a n00b. But what is it that they see?

Thus begins a new experiment, where I interview some of the people who I admire the most to help me improve my eye in their respective crafts. The goal is to elevate my own bar for excellence so I can start to see what they see.

I hope these interviews help you as much as they help me.

The Art of Growth

Brian Hale’s career is the stuff of legend. Starting out in the nascent field of search engine optimization after working as a line chef, he fast became known as a wunderkund in the early days of Facebook, the person you’d call to magically make numbers go up. We now know call this practice “Growth” in the tech industry, and many a company has adopted the concept of a dedicated group of cross-functional people focused on the business of growing a business.

Today, Brian is the Chief Growth Officer at DoorDash, and he remains one of the sharpest thinkers I know on the topic of sustainable hyperscaling.

Through our conversation, what stood out to me wasn’t a list of tactics but a set of sharp contrasts.

Over and over, Brian drew a line between what okay growth teams do and what excellent growth teams do. The differences are small but structural. Once you see them, you can’t unsee them.

Below are the top seven contrasts that, together, explain why some companies unlock orders‑of‑magnitude growth while others plateau at 5–10% of their potential.

1. Okay growth teams optimize funnels. Excellent growth teams own the entire journey.

Okay growth teams talk about growth as if it ends at signup.

They focus on acquisition. They measure top-of-funnel conversion. Once a user creates an account, the work is considered done, or handed off to another product.

Excellent growth teams see this as a category error.

Brian described excellence as “Obsessing about every single step — not just ‘did we get a customer in,’ but did they complete the order, and every single thing that might possibly go wrong in between.”

This obsession changes the unit of work. It’s no longer a funnel step or a dashboard metric. It’s the lived experience of a real person trying to get value.

Growth, in this frame, isn’t about getting people in. It’s about getting people through.

2. Okay teams ship changes. Excellent teams remove blockages.

Okay growth teams ship a lot of things.

Buttons change colors. Headlines rotate. UI elements move by a few pixels. Sometimes these experiments works. Sometimes they don’t.

Excellent growth teams care far less about what they changed than why it mattered.

Brian told a DoorDash story that captures this perfectly. The company had a strong zero-delivery-fee offer for new users, and yet many customers still hesitated because they were worried about fees.

As he put it: “We were like, ‘but there’s zero — what do you mean you’re worried?’ And that’s when it became obvious we were doing a terrible job explaining it.”

The growth win wasn’t inventing a new offer, it was making the existing offer impossible to miss.

When small changes produce massive results, it’s generally always because it resolved real customer confusion or fear that had been blocking their progress.

3. Okay teams maximize experiment count. Excellent teams maximize learning rate.

There’s a popular myth that the best growth teams ship the most experiments.

Brian is blunt about this being wrong.

He’s seen teams shipping dozens of experiments a week — changing button colors, moving pixels, rotating headlines — with almost nothing to show for it.

“What’s missing,” he said, “is why the hell that thing mattered in the first place.”

A button color only matters if users are getting stuck on that step. If no one is confused, the experiment is noise. Dozens of experiments per week usually means, in his words, “You’re not doing a ton of understanding work… you’re just shipping random stuff.”

Excellent teams earn the right to test by first understanding where friction actually lives and for whom it manifests, by diving into the data to understand conversion rates and user segments. They move at a steadier, almost boring pace where there are fewer experiments but much stronger hypotheses. As a result, the experiments tend to yield much higher signal.

Excellent teams also get excited about failures, not because failure is great in and of itself but because even failures yield important teachings. “This didn’t work,” Brian explained, “which means therefore this other thing must be true.”

Real growth velocity shows up as insight density rather than experiment motion.

4. Okay teams “growth hack.” Excellent teams practice product growth.

The phrase “growth hacking” sounds exciting. It also does real damage because it implies clever tricks, randomness, and the idea that anything might work if you try enough things at the wall.

Brian rejects this framing entirely. What excellent teams do, in his words, is product growth.

Product growth means removing friction, clarifying value, and fixing anything that makes the product harder, scarier, slower, or more expensive than it needs to be.

Great growth leaders aren’t asking, “What can we test?”

They’re asking, “Where is the user stuck and why?”

The answers are rarely flashy, but that’s where the big gains come from.

5. Okay teams optimize activity. Excellent teams optimize relationships.

As companies mature, their metrics start to betray them.

Orders. Sessions. Usage. All of them go up because they’re driven by a small group of power users.

Brian calls this a trap.

No power user starts out as a power user. “They all started out as first-time users,” he reminded me, an obvious statement that many teams somehow forget.

Teams start to optimize for activity for two main reasons:

The first is that power users tend to be the most vocal about their needs. Roadmaps become cluttered with features that help the person who is already coming back three times a week eke out 10% more efficiency in their workflow.

The second is that as companies mature, everyone inside the company becomes a power user. This results in collective blindness, as new users, occasional users, and less-enthusiastic users become invisible.

The new user flows get very little love. The price-conscious users are not represented within the company. The tech-unsavvy users, who grow in number as a company scales, get overlooked.

Growth teams exist, in large part, to restore that lost perspective and represent the people who aren’t already fluent.

Excellent growth teams anchor on MAU, or other people-count metric, because it forces the question: Are we continuously earning new relationships?

Focusing on activity may feel flattering in the short term, but relationship counts spell the breadth of opportunity for sustained long-term growth.

6. Okay teams celebrate wins. Excellent teams obsessively compound them.

When an experiment works, okay teams celebrate and move on.

Excellent teams slow down. They ask why the impact was so large. Why it worked ten times better than expected. What was the invisible bottleneck they just removed.

Brian described how the best insights often emerge this way: a fix that works far better than anticipated reveals a deeper truth about what actually matters.

From there, excellence looks like obsession to apply that lesson everywhere. This is how a pretty big win becomes a massively compounding one.

Breakout growth rarely comes from many ideas; rather they come from over-indexing on a small set of deeply right ideas.

7. Okay growth hires want the job. Excellent growth hires interrogate you.

If you’re hiring your first senior growth leader, this is the clearest tell.

Brian looks for people who are trying to understand whether the company is actually ready for growth, because they know that excellence in growth is conditional. Thus, their questions serve a diagnostic purpose. They may ask things like:

• “What does retention look like over years, not weeks or months?”
  This is a test of whether growth compounds or decays. Brian is clear that most companies fool themselves by quoting short-term retention. Long-horizon retention tells you whether there’s actually a pot of gold at the end of the funnel or whether growth will just pour water into a leaky bucket.

• “Where do new users get stuck or hesitate today, and what evidence do you have?”
  This question probes whether the company has done the understand work. Brian repeatedly emphasizes that excellent growth comes from deeply understanding confusion, fear, and friction, not from brainstorming ideas in the abstract. If the answer is vague, it signals the team isn’t yet seeing what matters.

• “Will this role have engineers and designers fully dedicated, or is this expected to live inside marketing?”
  This tests structural readiness. Brian is clear that growth is a cross-functional, product-level discipline that oversees the entire journey of the user. Without engineering and design partnership, the role collapses into acquisition tactics, and excellence becomes impossible.

Great growth leaders know that growth excellence requires the right conditions. And they’re not willing to join a team that isn’t ripe for the lever or structurally set up to succeed.

What separates Okay growth from Excellent growth?

Across all seven contrasts, one thing stands out to me: Excellent growth teams relentlessly do the most important thing, even when it’s unglamorous, non‑obvious, or uncomfortable.

They don’t chase tactics.

They don’t confuse motion for progress.

They don’t build for themselves.

They obsess over the customer and hunt for where the value is leaking.

If growth feels elusive, it’s rarely because teams lack ideas; it’s because they don’t have the patience or discipline to find and commit to the real leverage.

I love the start of the year, the collective closing of one chapter and the opening of the next. Some people go through the holiday season with visions of sugar plums dancing in their heads; for me, it’s all the possible intentions I might try on, like outfits, and the many Sliding Door-eque possibilities for the new year.

December ends with a flurry of writing. In the past, these were long lists of “goals,” tangible achievements I could check off like Santa’s list. But gradually I’ve drifted away from crisp binary outcomes to something softer and more abstract, gifts prepared for the tastes of my subconscious rather than the thinking mind.

Ultimately, where I landed for 2026 is this: Play authentic games.

Why games?

Because the idea of a game reminds me that the rules are arbitrary.

When a ball goes out of bounds, why does the opponent get a point in tennis, but not in soccer? Is one rule more universally “correct” than the other?

I doubt it. If you see a group of children playing some new game they invented, you’ll notice that rules are slapped on for all sorts of reasons, the most common of which seems to be a kid litigating that what she did counts and should grant her the advantage. Usually a big lively debate ensues. Eventually, a decision gets made that “this is now how we’re going to play the game,” everyone mutters their agreement, and merriment ensues. (Or not: sometimes the players can’t agree and the game falls apart.)

The important thing is, remembering that rules are arbitrary gives games a certain lightness. When something is universal law, say gravity in the physical world, there’s no ifs, ands, or buts about it. Gravity is serious business.

But most of life is not that. I should do well at my job. I need to find a partner. I want my kids to be happy. I need to eat healthier — none of these are universal laws.

These rules are as fluid as my imagination.

Why authentic games?

Because there are an infinite number of games that could be played, so it’s important to choose the right games for me, the ones I genuinely opt into playing rather than the ones I might have been shoved into.

It can be disorienting when everyone else is playing a game they’re obsessed with, and their entire worldview shapeshifts around this game. It becomes their reality, as if they’re in a The Matrix-like simulation. Every one of their words and actions implies that we all exist in the frame of playing this game, whether it’s status, or wealth, or approval, or what have you.

But this is not true! I get to choose my games!

Sometimes, two games can look similar from the outside but actually have a different set of rules. For example, a casual observer might not really notice the difference between tag and freeze tag, or baseball and cricket, or Build a great team vs. Build a great product.

But the rules make the game. It’s important for me to distinguish the actual game I am playing from the ones that others might be playing, even if we’re all doing our thing in the same space.

Why play authentic games?

Because the idea of play reminds me that at their best, games are meant to be rewarding. It’s a privilege to be alive, in an expansive world, with a beating heart. There’s a kid-in-a-candy-store type of delight to realize the agency of discovering and choosing games that will fulfill me, whether it’s for a few minutes or for a lifetime.

Of course, this isn’t to say that every second of gameplay is fun. Ask any experienced player who loves their game whether there are mountains of frustration (yes). Whether there are oceans of doubt (yes). Rivers of sorrow, fields of boredom, plateaus of stagnation (yes, yes, yes).

But the best games are not simply the ones that help us amusingly pass the time. They challenge us. They allow us to dive into a state of flow where we forget about our lonesome little egos. The best games leave us tired and satisfied and alive. The best games help us discover who we are and who we can really be.

One of my favorite origin stories starts, like many such stories do, with a Great and All-Knowing Deity.

One day, this Deity decided to play a game. They split Themself into hundreds of thousands of pieces, little soul-shards brimming with the spark of All-Knowing Greatness.

The Deity then scattered these pieces of Themself all over the world in a vast and cosmic game of hide-and-seek.

If one of those pieces of Themself encountered another piece of Themself, would they be able to recognize that they came from the same All-Knowing Greatness? Would they laugh and scream with delight upon this finding, as children do?

Each of us is a soul-shard of that Deity. Our daily encounters are an expression of this hide-and-seek game. What fun, to think of each flicker of eye contact, each smile, each conversation, as a chance to uncover our secret connection! What a beautiful way to look at the world.

I love this story because it reminds me that some of the best games are those we play with ourselves. Games of curiosity and personal growth. Games of alchemy, to transmute my boredom into amusement, my fear into fuel. Games whose leaderboards show me only different incarnations of myself.

I hope 2026 brings you some wonderful games, and I hope you have tremendous fun playing them.

Some authentic games I am choosing to play this year (bonus content for paying subscribers):

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You may not believe this, but if you pull me apart and unpeel me layer by layer, you will discover that I am an ice queen.

Yes, you read that right.

My eyes glitter keenly; my tongue is sharp and cutting; my heart is smooth and cold as a mirror’s surface.

Vast dominions of my mind glitter in the sunlight, pure and beautiful and white, like songs in a Christmas jingle.

Here, where I reign, everything is cool and collected. My streets are straight and orderly. My castle is a crystal marvel.

It’s not perfect, not by any stretch.

But oh, how I try.

ii.

A few weeks after I moved to the United States, my parents’ friends invited us to their small apartment for a welcome dinner. I was five years old, disoriented and bored, the only kid at the gathering. Desperately I wished to go home.

I trundled about the tiny apartment, sniffing for amusement like a pig for truffles. In the kitchen, plastered onto the refrigerator, I found it: a plush egg-face magnet. Between two paisley-yellow cracked egg halves, a hot pink face with googly eyes peered out at me.

It looked adorable. It beckoned like a friend.

I pulled the magnet off the fridge and plunked down on the linoleum. We played for hours in that tiny kitchen corner. My mother found me there when it was time to leave.

“What’s this?” she asked me in Mandarin as she plucked the magnet out of my hands.

“I want it,” I said, yanking it back.

“We’re going. Put it back where you found it,” she ordered.

“I want it,” I insisted. A whine bubbled in the back of my throat.

At this point our hostess fluttered into the kitchen, overhearing the argument.

“Oh, she can have it,” she said brightly, taking the magnet and pressing it into my grateful palm. She flashed my mother a smile, sent us on our way, and that was that.

Or so I thought.

Delighted, I played with my new eggy friend the entire car ride home. But as soon as we reached our own tiny apartment, my mother whirled on me.

“You. Cannot. Take. Other. People’s. Things!” She grabbed the magnet, as dark as a freak thunderstorm.

The force of my mother’s anger barreled into me like a battering ram. I must have fought it, must have tried holding onto my naive innocence. There was no guilt in my heart then; I had no conception that I had done anything wrong.

Before long, my mother pulled my crumpled form into the bathroom. “Think about what you did,” she demanded as she flicked off the lights and shut the door behind her.

On that cold tile floor in the blackness, I slumped my face on the toilet seat and cried and cried.

iii.

Let us examine the tear, that droplet which carries the chemistry of our emotions.

For centuries, people dismissed tears as weakness. Science today tells a different story.

Emotional tears, different from the ones you shed chopping onions, are chemically denser, laced with stress hormones like cortisol and ACTH, and natural painkillers called endorphins. In the 1980s, biochemist William Frey found that emotional tears are like a river that carries away stress-related substances.

The act of crying is orchestrated by the brain’s emotional command center, the limbic system. The amygdala sounds the alarm, the hypothalamus routes the signal, and the tear ducts respond. What follows is a cascade that flips the body into its parasympathetic state—the “rest and digest” mode that slows your heart, deepens your breathing, and tells your muscles to unclench. Psychologists like Ad Vingerhoets and Jonathan Rottenberg have shown that although crying sometimes dips your mood at first, within about 20 minutes most people report feeling calmer, lighter, and more in balance. In biological terms, shedding tears is a form of repair.

The benefits don’t stop at physiology. Tears are a kind of social glue. Unlike screaming, which pushes others away, crying is more likely to draw people closer. Researchers found that people who cry in front of others are more likely to receive comfort and support. For those mourning a loss, studies show that expressing genuine grief, including crying, predicted better long-term adjustment than burying emotions tightly inside. In therapy rooms, tears often mark breakthrough moments when buried trauma surfaces and has a chance to heal.

Not everyone finds it easy to cry. Hormones matter: testosterone dampens tearfulness, while prolactin (higher in women) encourages it. Medications like antidepressants can make crying harder, flattening the peaks and valleys of feeling. And of course, there is the matter of culture.

Yet when tears do come, they are a gift to the nervous system, lightening the body’s chemical load and opening our hearts to others.

iv.

I cannot tell you when my crying stopped. At age 8 or 9 or 10 perhaps. It was a gradual taper, one that seemed as normal as rain. In a million different ways, the world conspires to tell us that we don’t need to cry. Or, in its harsher moments: we shouldn’t cry.

Let’s take a cliche we all grew up hearing: Don’t cry over spilled milk. On the surface, it delivers a nugget of wisdom: what’s the use regretting something you cannot change? Used nobly, its intent is to nudge the listener towards peaceful acceptance and perhaps more fruitful action (You still have the power to clean it up!)

But how might this be meant by a parent distressed by their toddler’s howling at a bustling restaurant? Your crying is loud and embarrassing, so please stop!

And how might it be interpreted by the toddler? Crying makes Mommy upset!

Growing up, I saw kids get teased at the playground for crying. Don’t be such a baby!

I saw adults apologizing when they did cry. Oh gosh I’m sorry, I’m making such a scene.

I never ever—not even once—saw someone being praised for crying.

So I swallowed the message: Tears are weakness, tears are useless. Tears are an omen of trouble. Tears are a thorn in the side of polite society.

v.

In my line of work, I meet many denizens of the ice.

Like me, they are attracted to the elegance of cold, hard logic.

What is a problem but an opportunity for creative solutions?

What is the future but a chance to achieve our grandest designs?

Obstacles are meant to be deconstructed and understood; chaos is meant to be transfigured into elegant systems.

And emotions—emotions are meant to be contained. They are like flies; nuisances to good work. How often have I heard a colleague vent to me in frustration, “If only <X> could see this logically, then they would agree with me!”

Rulers of ice kingdoms know intellectually that they can’t solve every problem. They know life cannot be fully controlled. But shouldn’t it be? The pursuit itself feels urgent and noble and deeply, deeply important.

Because ice people do not value emotions, they have a blind spot for them. It’s easy for them to tally other people’s emotional illogic; it’s much harder for them to recognize their own.

If you asked me how I was feeling on any given day, the answer I’d give you would be an algorithmic assessment of my current circumstances—family healthy? Job enjoyable? Milestones marked? Fun weekend impending?

“Doing well,” would be the usual answer. If I wanted to sound more human, I’d throw out a problem du jour — “But <family member> is struggling with <y>, which is taking up a lot of energy.”

My answer would certainly not be the bodily feeling of the moment: Lonely. Disappointed. Frustrated. Angry. Loving. Joyful.

Why not? For the longest time, I don’t know that I felt those things consciously. My overmind performed its security duties admirably in keeping those pesky emotions locked behind thick walls.

On the rare occasion when I was consciously aware of a feeling, it was branded illogical, fleeting, not worth bringing up. When you asked me how I was feeling, you probably wanted a birds-eye view, not the asylum escapee of the moment. No need to scare you with my sudden roil of existential dread; that thing will be taken care of very shortly.

You see the logic of the ice queen?

Being an excellent fixer means not tolerating those fuzzy feelings that get in the way of fixing.

I held fast to this belief, like some kind of zealot. It took years for the scientist in me to crack open the possibility that this may be the wrong way to look at it.

What if the logic goes the other way?

What if it’s the inability to tolerate fuzzy feelings that leads someone to becoming an excellent fixer?

What if problem solving develops as a protective mechanism against feeling pain?

What if the predominant, subconscious emotion of ice rulers is fear?

Intellectually, we know we cannot solve every problem. Life cannot be fully controlled.

But our feelings dominate.

And therein lies the dilemma.

vi.

The airplane was when I first noticed the cracks.

During a long, trans-Atlantic flight, I idly selected The Notebook, at the time a cultural phenomenon I was curious to understand. I like certain romances but the entire plot of this one had me rolling my eyes. And then, suddenly, during a particularly overwrought scene, my eye-rolling turned into eye-watering. I was shocked. Me? Really? This sappy, fluffy thing? Perhaps this was why the movie was a phenomenon! Getting me to cry was some feat!

The next time it happened was a trans-Pacific flight, nearly a decade later. The movie was Lion. I bawled my eyes out and remembered the flight attendant looking at me sympathetically as she poured me a drink.

Some years later on yet another flight, the movie was La La Land. As the long musical ending montage flowed before me, some inner hand turned on the spigot.

Three is a pattern, a mystery! Why would movies on airplanes make me cry, while movies not on airplanes induce no such effect? I dug around and found a satisfying scientific explanation: altitude induces mild hypoxia which increases stress! Of course! Silly ol’ biology!

This explanation did little to patch up the leak. If anything, the stirrings accelerated. I found that even listening to certain songs on an airplane could prickle my eyes. The first songs to do this were either rediscovered favorites from my childhood or those with a certain vastness of story, like Brandi Carlile’s Highwomen.

And then, on one fine flight last year, I unlocked the motherlode: a rediscovery of an album my parents had played over and over again after I had first immigrated to the United States. An album in Mandarin, by an old 80s pop artist.

I listened to it and I wept.

I got off the plane, still listening to it on the taxi, and I wept.

As soon as I got into my hotel room, I furiously searched across every fragment of every Chinese song I had ever recalled hearing, in desperate awe over the power of the Internet. When I first came to the US in the early 1990s, I left an entire universe behind. Songs in my first language were inaccessible to me; I was too young to remember artists or albums or song names. But now, I only had to hum a melody or remember a turn of phrase, and there it was: a Wikipedia page with a title. Paste the title into Spotify and pieces of my childhood came pouring back into my ears.

I listened to the music for hours, and I sobbed.

That was my first Big Cry.

vii.

In this era of AI, our conscious human minds are in competition with currents of electricity running through silicon.

Already, this technology produces faster calculations and write more coherent essays and remembers more details and win more games.

AI will increasingly predict what we like. Plan our itineraries. Entertain us. Tell us what’s important.

We are creating a superhuman overmind who can extend our ice kingdoms beyond our grandest conceptions.

We haven’t yet found perfection in our 300,000 years on this planet. But it always seems to dangle just one new innovation away.

viii.

There are many emotional roads that lead to tears, each with its own biological signature.

Loneliness brings tears of absence, when the body aches for connection. As oxytocin and serotonin fall and cortisol rises, the brain’s pain centers light up as if the body were physically hurt. Tears here act more as a distress signal, a way of saying come back and help me.

Grief floods those same circuits but with the finality of loss. As a result, each cry marks another small step towards acceptance by releasing stress, creating moments of relief amidst sorrow. Crying becomes both expression and repair as the body transforms pain into memory.

Then there are tears of awe, when we see beauty beyond comprehension. The stress response shuts down, and our rattling minds quiet as we are flooded with calm. In those moments, crying feels like dissolving into something far grander and more ancient, a homecoming of our brief humble lives into the vastness of the universe.

Finally there is kama muta, the Sanskrit term for “moved by love.” These tears arrive with moments of intense social communion: reunions, shared songs, gesture of care. Oxytocin surges, warmth spreads through the chest, and we weep not from threat but from safety. Scientists describe it as the body’s reflex to connection, the nervous system recognizing love.

ix.

Some people meditate or go for a long run or do yoga. I’ve taken to Big Cries.

Since tears are a bodily rather than conscious experience, I cannot will myself to cry. But what I can do is create an environment more conducive to feeling grief or awe or love.

The whole thing feels a bit like a ritual summoning. Time must be set aside, with nothing scheduled for the next block. There must be no obligation to look put together. The phones are shut off, the lights dimmed. I unwittingly found the airplane to be one such sanctum; a quiet house or a secluded trail in the woods are others.

The second ingredient for me is music. For some reason, certain tracks deliver me a quicker path to tears, like an IV tap. My guess is that we all have certain subconscious sensory triggers that bring us closer to our bodies; mine happens to be songs that evoke long journeys, sacrifices, nostalgia or the cyclical nature of time. Maybe yours are photos or poems or scents.

The third ingredient is focus. My mind is prone to wandering into lighter territory once deeper feelings penetrate, a kind of resistance to the intensity and vulnerability of crying. It takes some intention to stay with it, to wade deeper into it, to allow oneself to really feel it.

Some sessions, I can only access the outer layers. The tears are shallow, a trickle down the cheek here and there, as if the doors to the inner realms are barred. I notice this more when my conscious mind tries to exert its will, like when it gets the idea that doing a Big Cry now will help me be calmer tomorrow!

In other sessions, given the time and space and proper relaxing environs, the summoning works. I enter into that iridescent swirl of grief and awe and love. Sometimes, surprisingly, it’ll be with a brand new song. Sometimes, it’ll be with a specific chord progression. Sometimes, it’ll be an old favorite track that I now interpret in a completely new way. With practice, the path to that place becomes easier to access, the once-wild terrain now grooved with a trail.

My Oura Ring tells me that my stress levels plummet, and I am “restored” or “relaxed” when I cry. Right afterwards, I notice more compassion in myself. I get an intense urge to declare my love for my family and write thank letters to friends. Situations that made me feel wronged in the past now appear like simple misunderstandings. Of course they were acting with best intent! It was my prickly sensitivity that led to the tension!

My mind clears, my footsteps lighten, my patience stretches.

It turns out, there is an alternative to trapping emotions behind walls of ice.

You could simply dismiss the guards and invite them to step into the sun.

x.

I still enjoy constructing kingdoms of ice.

There is beauty in the structure of snowflakes, in well-laid plans well executed.

But I no longer want my heart to be cold.

And so, I must let my vast dominion thaw.

As the temperature rises, the fine, crystalline edges of my towers and turrets will give way to something messy and organic. The melting ice will flow into rivulets of tears, as I rediscover the lost art of crying.

Around me, the machines will grow more intelligent and powerful, perhaps even more wise. They may supplant our logic, our knowledge, our taste, perhaps even our ability to invent.

But they will never be able to truly feel what we feel.

It’s time to make some time, close our eyes, and enjoy the kaleidoscope.

It irked the hell out of me.

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Besides some refreshed examples in the original 10 chapters, it comes with two brand spankin’ new sections on Managing Remotely and Managing in a Downturn. In the years since publication I lamented not having addressed these two topics more deeply, especially after the pandemic and the various market downturns and layoffs we’ve seen.

To commemorate the book’s (re)-launch, I wanted to share my take on some of the most common questions about management as we enter an AI era. Got other q’s? Drop ‘em in the comments!

Pure middle manager roles will decline

The promise of AI is that you can do more with less, which means we’re entering an era of leaner teams, as I’ve written about before. Why summon all the Avengers when one Captain Marvel will do?

Remember the “telephone game” we all played as kids, where we’d whisper a sentence around a circle until it came back hilariously garbled? The role of middle managers unfortunately sometimes felt like that.

Leaner teams means fewer roles whose primary function is coordinating information. This is a good thing! Even when information does need to pass between humans, AI tools are highly competent at drafting updates, surfacing data, and generating summaries. Messages can more easily travel directly from source to decision-maker with less distortion.

The need for management skills will only increase

What is the skill of management? In my book I define it as getting better outcomes from a group by the use of three key levers: purpose (aligning on what success looks like), people (defining who is needed to achieve the goal), and process (defining how the work should get done).

Now imagine that formerly large Avengers team being compressed into one or two Captain Marvels, thanks to AI. The headcount shrinks, but the need to manage work doesn’t. Those remaining individuals have to think like managers in deciding what to prioritize, how to split tasks, and how to keep themselves accountable. In other words, certain parts of the management function must shift into the hands of the Individual Contributor.

This is why there’s so much chatter about how AI rewards high-agency people with a clear sense of purpose (some great reads on what “high agency” is here and here). Instead of waiting for someone else to help coordinate or define next steps, these folks experiment quickly, learn and share. Instead of expecting coaching and feedback from humans, an IC can ask, Help me critique this presentation or Point out blind spots in my argument and get an instant second opinion from AI.

AI also gives ICs better tools to improve collaboration with other humans. Worried about how to tell a colleague that their proposal sucks? Have AI help you draft a direct-yet-kind script and roleplay the conversation with you. Trying to make sure your higher-ups know what’s up? Have AI draft you clean exec summaries.

The old boundary lines are blurring. Just as we’ll see fewer “pure managers,” we’ll also see fewer “pure ICs.” Instead, more people will live in the messy middle: sometimes executing, sometimes designing processes, sometimes coordinating.

Like switching hats in a fast-moving improv show, the distinction between manager and IC becomes less about rigid role definitions and more about moment-to-moment needs.

Managing AI is like managing humans, with one big exception

If you’ve ever managed a very literal intern, you already have a sense of what managing AI is like. Give clear instructions, and they’ll execute them earnestly. Leave things vague, and you might get back something kinda accurate but totally irrelevant (like asking for “a picture of a cat” and receiving a Renaissance oil painting of a lion wearing a ruffled collar).

Remember our core principles of good management? Not much changes with an agentic report!

• Defining your purpose is critical: What does success look like? This needs to be spelled out explicitly for AI to have any shot of hitting your target. This is why prompt engineering is an art.

• Pick the right people model for the job: Different models have different personalities and strengths, just like people. Get to know their unique quirks so you can send the best model for the task.

• Build clear processes for how you ensure good work: Trust, but verify. This is why constructing evals is an art.

Of course, there is one major difference between managing AI and managing humans, which comes down to the difference in physical and emotional needs.

An AI can work around the clock without faltering. An AI can take your curt, snappy tone without offense. An AI does not need you to empathize with its circumstances or feelings.

For some people, this makes the task of managing AI much less daunting!

AI will make leadership both easier and harder

We’ve already spoken at length about the easier part: AI can act like the world’s best coach, teacher, and assistant—patient, tireless, and available 24/7.

And yet, leadership has never been harder. We’re living through a massive shift where entire categories of work are changing or disappearing. People are anxious. Fear can easily calcify into cynicism or transactional relationships: Why should I invest in this if it may vanish tomorrow?

In times like these, leaders need to be stabilizers. We’ve got to learn to manage our own psyche. If you project only cheer, you’ll come across as out of touch. If you project only worry, you’ll amplify everyone else’s anxiety. The art lies in holding both sturdiness and flexibility at once, like a tree that bends in the storm but does not break.

That balance of steady while adaptable may be the hardest and most important leadership skill of this era.

AI is changing what it means to manage and lead. Fewer layers, blurrier roles, more tools at our fingertips. But the heart of management remains timeless: setting purpose, building trust, helping people grow.

If you’re reading this, I expect you’ll manage. In both senses of the word. Let us stay sturdy in the storm, flexible in the unknown, and deeply human in how we guide others forward.

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You conjured an image of yourself making—nay willing—something important into existence. What?

A one-way ticket to immortalized greatness?

A thrilling adventure to fill the pages of your own personal hero’s journal?

A bank account fat enough to guarantee you security for the rest of your days?

Whether you sought to change the world or change your fortunes, you believed it possible. You had the magic of conviction.

The first few months fly by like a convertible under California sky. Brilliant ideas slip into your mind effortlessly as sunsets. It all feels so fresh, so free, so possible. This is the honeymoon period, where your story bursts of sweet, juicy promise. You share it with hungry seekers who sign on to your team. You serve it up to those with fat purses as they wave money in your direction.

You live in the future, which is to say you live in a dream. Everything feels as airy as cotton candy.

But of course, reality comes knocking.

Reality is patient; it knows you’ll eventually open the door. Reality is also a tempest. When you finally step through, you’ll find yourself in the arena where your conviction faces off against an onslaught of fearsome creatures: Rejection, Failure, Disappointment, Comparison, Opportunity Cost, Chaos.

Each beast charges towards your conviction. At first they are easily swatted aside. Your energy is electric and you are ready for these early setbacks. After all, you expected challenges on your quest. A smooth path would be boring.

But the attacks are relentless. Week after week, new crises emerge. Things always take longer than you expect. The situation is always more complex than you initially thought. Your idea is never as good in execution as on paper.

Soon, you find yourself winded and even a little bit wounded. Certain rejections have sunk their teeth into your conviction and torn out great chunks. As belief whittles away, dark questions descend like vultures:

1. Am I as capable as I thought?

2. Is the dream still possible?

3. Do I still want this, knowing what it’ll cost?

This is the founder’s real battle: reality against conviction. The only true death of a start-up is the death of conviction.

You can lose customers, lose colleagues, lose co-founders, lose all your money. There are founders who have faced these and more, only to ascend to ever greater heights. As Ben Horowitz says, “There is always a move.” But do you still care to make that move?

No single setback is a killing blow; but it may well be the straw that breaks your conviction’s back.

In the making of any successful founder, this much can be said: through the daily clash of dreams against reality, she kept the fires of conviction alive.

Where does conviction come from?

There are three founts whence conviction springs:

1. Conviction in where the world is going

Like the oracle at Delphi, you’re blessed with clarity of foresight. You can see that which is inevitable. Your ears hear how history rhymes, your heart thumps to the sinusoidal rhythms of history. The tectonic plates of culture collide in predictable ways, and you can tell where we’re going even if you don’t know exactly when we’ll get there. You see what the world needs and why long before everyone else wakes up to it.

This is conviction in a market, conviction in customer needs, conviction in human nature, conviction in the steady arc of destiny.

2. Conviction in the self

Like Hercules, so confident in his strength that he took on his Twelve Labors with a sense of inevitable success, you too know your shit. Everything in your life has led you to the precipice of this next grand challenge. You have lived and breathed the problem; you have peered into its dark cavities from a thousand different angles. You know your domain cold; you were born to do this.

This is conviction in one’s skills, conviction in unique knowledge, conviction in the intelligence and strength and force of will that lies within.

3. Conviction in the process

Like Odysseus and Penelope during his agonizing ten-year journey home, you tread in patience and practical optimism. You are well aware that every journey of a thousand miles starts with a single step, and taking that step is nothing magical or even memorable. Your faith finds repose not in the flashy but in the unseen compounding of daily life: roots must take hold before the tree can rise, buds must open before seeds can be sown. Every win or loss is nothing so momentous as another page in a story that’s still being written. You learn and adjust, adjust and learn. Eventually you’ll land on the sandy shores of your destination.

This is conviction in learning, conviction in a way of being, conviction in principles, conviction that the game itself is worth playing.

Every successful founder has their own unique blend of these three convictions, a signature cocktail if you will.

The formula is simple: the stronger their drink, the more likely they are to succeed.

Cultivating conviction

How do you grow in each type of conviction? Here’s seven ideas to consider.

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You were quiet as a breeze, your manner good-natured, your visage a buddha smile below crinkled eyes. But something about you felt larger than life

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Wittgenstein once wrote that when the eye sees something beautiful, the hand wants to draw it.

This line, from the The History of Love, runs through my mind almost daily. The eye and what it admires is how I think of taste.

Today’s popular opinion is that great taste is a key advantage that humans have over AI. But is this true?

To explore this question, I had a chat with Ivan Zhao, CEO and co-founder of Notion. I was particularly eager to sit down with Ivan both because Notion is one of my favorite products and because he's a founder whose taste I greatly admire. (Case in point: how much I adore everything on this page.)

The below essay weaves together some of the threads of our conversation.

The three elements of human value

In what ways do we contribute to the world?

Ivan posits an elegant framework to the above question that breaks down value into three components:

1. Our capabilities — these are the skills and knowledge that we possess. Can you build a fire? Calculate the trajectory of a rocket? Craft a website? Determine who stole the cookie among a group of kindergartners?

2. Our taste — these are our values and preferences. What draws you more: Art Nouveau's organic curves or Bauhaus's clean functionality? Are you moved more by a single person's suffering right in front of you, or by the possible harm that might affect thousands of future generations? Does your focus lean toward an impressive end, or an elegant means?

3. Our agency — this consists of our will and drive. Even if we know how to do something, will we be sufficiently motivated to do it? Do we care enough to be moved to action?
   

   These three elements work together to determine how we actually contribute: our capabilities define what we can do, our taste guides what we want to do, and our agency determines what we will do.

AI is winning the capabilities race

Every generation has watched technology surpass us in new domains.

First our physical skills were defeated: machines could plow fields, move loads, and spin thread faster and more tirelessly than we ever could.

Then our analytical skills fell: calculators could multiply and derive thousands of numbers in the time it takes you to read this sentence. Algorithms began trading stocks, detecting fraud, and recommending ways to part with your money more effectively than any human brain. One by one, computers defeated our greatest champions of strategic games in chess, go, and even Starcraft.

Now, even our creative skills are under assault. ChatGPT writes a sharper essay than most college graduates. Midjourney creates more professional artwork than many artists. Whether it's code or music, videos or graphics, dozens of startups are ruthlessly competing to demonstrate how AI can produce work that's indistinguishable from what we used to call a marvel.

The most skilled humans today still outcompete AI in complex reasoning and innovation. But as AI grows smarter, its infinite patience and inexhaustible speed will make it even more capable of taking over more and more human lanes.

Taste is a fragile fortress

Today's conventional wisdom is that great taste is one of the last remaining bastions of human superiority. Whereas taste we’ve defined as one's values and preferences, great taste is when one's values and preferences are so refined that they can consistently spot excellence before others see it.

We’ve clung to this driftwood of taste because AI's current attempts at curation feel laughably generic. When AI recommends music, it tends toward safe, billboard-hit choices. When it tells jokes, it recycles material from generations of dads past rather than crack something worthy of a Netflix comedy special.

Perhaps some part of us believes taste is safe from AI dominance because it’s subjective. After all, who can know my values and preferences better than me?

But great taste is more objective than we assume. To be deemed excellent implies social validation; some group of others must affirm the judgment!

If you say a friend has “excellent taste in music,” it’s because you’ve witnessed this friend selecting songs that you and other music-lovers vibe with. In other words, you believe your friend is a damn good predictor of what a discerning audience will appreciate.

This skill isn’t just luck or innate musicality. Your friend is well-informed and I’m willing to bet good money she isn’t the type who only listens to Top 40 stuff.

Tastemakers are voracious students of their discipline, obsessing over details that others might find tedious in their quest to uncover hidden gems. When they say "this song is great," it carries the authority of someone who has evaluated hundreds of similar tracks and can articulate exactly what makes this one distinct. They've built a foundational understanding that lets them discern the craft involved—what was technically challenging, what was innovative, how it connects to broader musical lineages.

Despite experts occasionally butting heads, well-informed communities tend toward consensus on greatness, especially over time. How many designers do you know who strongly feel Windows is better designed than MacOS? How many engineers do you know who sing the praises of C++ or Perl?

If excellent taste operates through pattern recognition across vast cultural knowledge, then it isn’t a stretch to imagine that AI systems can replicate this process. They can absorb the same foundational context the best tastemakers do; they can track the preferences of frontier communities and learn to predict with increasing accuracy what a discerning individual will value. Seen as a prediction engine, human taste is far more vulnerable to AI competition than we'd like to admit.

That said, at the highest echelons, taste is not just prediction, it’s also movement making. The most significant tastemakers take social risks. They might champion work that others find unfamiliar and stake their reputation on bold judgments that initially seem out of touch. The writer Zora Neale Hurston died in obscurity but Alice Walker introduced a new generation to her work during the civil rights movement. The composer Johann Sebastian Bach was considered old-fashioned during his lifetime but recognized as foundational nearly 80 years later when Felix Mendelssohn conducted the first public performance of his work after his death.

In a landscape of shifting cultural winds, these people didn’t just conform to existing preferences but convinced others of entirely new ways of seeing and valuing greatness. This dimension of taste, which requires cultural courage and a willingness to be wrong, may prove more resistant to AI replication than mere pattern recognition.

Agency is the uniquely human moat

If AI can meet or surpass humans in capabilities and taste, what remains distinctly ours?

The answer is agency. The will and motivation to act on our values. Moving the hand to draw what the eye admires.

Even as AI becomes more capable, humans are still the ones to unknot problems that deserve attention. Human drive is what made AI in the first place; it’s what will direct the work of this technology.

We talk of the “agency” of AI systems, but what we mean is letting these systems optimize for some programmed objective. Who sets these objectives? Ultimately it’s still us.

Human agency emerges from our subjective experience of life’s purpose. We choose to play chess not because we're the best at it, but because the struggle of the game matters to us. Sometimes we choose to write so we can better connect with others; other times we write to think or feel. Who can determine the why except the self?

Of course, this raises disorienting questions about the future. Will AI eventually develop its own sense of purpose? Could it one day care about outcomes beyond its programming?

For now, at least, we humans remain the source of intentional choice in the world. We choose what to optimize for and what to preserve. We determine whether technology serves our flourishing or something else entirely. We can opt into making things with our hands instead of with machines.

Our unique agency allows us to exercise a higher plane of creativity to direct our attention. Our specific will is what determines whether we progress toward our vision or slip into chaos.

Whether this advantage lasts depends on questions we're only beginning to understand about consciousness, purpose, and what it means to truly care about something.

But in a world where capabilities and even taste becomes commoditized, the will of the hand to act according to our values may well be our most rare and precious resource.

Other articles in the Looking Glass AI series

I see you for the fiftieth time and wonder, What the hell are you doing here?

It’s not because your work falls flat.

In fact, the work you show me, is smooth like river rocks. There is care in its making, a touch of personality even — a riff here in the content, a flourish there in the presentation.

But something is missing. A sparkle. A kind of dazzle that cannot come from more polishing

Read more

Last year, I wrote 189,214 words.

Not because a boss demanded it, or a paycheck dangled at the finish line. I wrote these words for me. I like writing words; I fancy myself reasonably good at it. And I enjoy the feeling of total immersion trying to capture a sea of images and ideas within my mind.

It isn’t just words. The other week, itching to add some flair to Sundial’s marketing page, I rolled up my sleeves. My inbox and socials are practically overflowing with AI tools promising instant-ramen results. Instead, I spent hours nudging pixels like a gardener pruning bonsai. (My team eventually staged an intervention to gently tug the page edits away from my hands. Thank you ;)

I’m not alone. Recently I spoke with an exceptional engineer, someone whose output is easily that of an entire team’s. When I asked how much he used AI, he replied cautiously, "For the typical stuff — unit testing, boilerplate code. But I don't trust it on anything substantial."

On the surface, this is a story about love: how wonderful to express our hard-earned expertise, to pursue the pinnacle of our craft!

But as the movie rolls on, the seeds of our downfall are already sown. AI is nipping at our roles, identity, our very careers.

Those of us most likely to be disrupted are the one most attached to our work.

ii.

There are three main reasons why experts struggle to adapt to AI.

1. Automatic comfort

Most mornings, I brew coffee without thinking. My hands move like clockwork through the ritual. Those habitual neural pathways are worn smooth as river stones. There is where years of practice — writing that SQL query, manipulating that vector tool, drafting that Slack post — have ingrained our work inside of us. We don’t think hard as we do it; it feels so natural.

Doing something new like incorporating AI into our workflows demands conscious attention. We are rerouting rivers in our minds and it takes effort.

It’s not just the effort of making the change; there is also effort to overcome the initial bursts of frustration at the outcome. If you’re expert at something, AI probably won’t deliver you the kind of results you’d expect from yourself, at least right off the bat.

The mind doth protest: let’s fall back into the comfort zone, where it’s plush and easy! Sometimes, our areas of expertise become such cozy havens that we scarcely realize the world outside our windows is fast changing.

2. Identity attachment

How many times have you been been face-to-face with a stranger being asked the question: So, what do you do?

For me, I’ve rattled off thousands of repetitions of I’m a designer or writer or founder. Each time I do, that particular identity inks itself a little more deeply into my skin.

With attachment to an identity comes sharp pricks of fear when that identity risks slipping away. Wait a minute, if I’m a designer / writer / founder / engineer / marketer then I should be designing / writing / company building / engineering / marketing! Especially if we’ve been handsomely rewarded for it in the past.

AI taking on more and more of what we traditionally used to do feels like a threat. What happens when attachment is threatened? We grip on even more tightly.

3. Love of the craft

The biggest hurdle to changing habits is love of the craft itself. The engineer who hand-optimizes code for elegance. The designer who obsesses over kerning invisible to users. The animator who inks each cell by hand.

Telling someone they shouldn’t love what they do, or do what they love, is a losing position. Anything that comes from love is pure and good. Sometimes, it explains with great eloquence and truth why we resist change.

iii.

Tech history repeats the same comedy.

When photography emerged in 1839, French academic painter Paul Delaroche reportedly declared, "From today, painting is dead!"

The art establishment saw photography as the ultimate threat in its ability to capture reality with perfect precision. At the time, most painters were creating portraits for the wealthy or documenting historical events or recording what things looked like, which took years of training to master.

In one sense, Delaroche was right — what died was the careers of those painters who photocopied what they saw.

But in the broader sense, Delaroche was dead wrong. Photography unshackled painting from its utilitarian purpose.

New painters emerged that captured different realities—Monet sought to convey the aura of light; Picasso played with multiple perspectives; Rothko dissolved forms into color fields of emotion. The market for painting exploded.

This pattern repeats itself with stunning consistency. In 1840: Painters raged at pre-mixed pigments in tubes ("Real artists grind their own!"). In 1990, Photographers boycotted digital (“Buy film not megapixels!"). In 2025: Writers and artists eye ChatGPT warily (“AI will kill creativity!”).

Every new technological marvel brings death and loss, yes, but it also invites an explosion of birth.

Entrenched experts are the ones most likely to miss the lesson of history: new tools open the playing field for a new generation of expertise.

iv.

If you're reading this with a sinking feeling that expert describes you, fear not. As they say in every single growth book on this planet, awareness is the first step.

The best way to counteract a bias is to be exposed to the fact that you have it. Consider this essay a public service announcement (you’re welcome!) that you are on the verge of being disrupted.

The good news is that every mindset has its perfect antidote. Here are the three against ones discussed above.

Automatic comfort → Intentional discomfort.

Combat muscle memory by deliberating scheduling friction into your workflow. Block out AI experiment time on your calendar and treat it like any other important meeting. Set explicit goals: "This week, I'll use Claude to help me with 5 writing tasks" or "I’ll prototype 2 new ideas using Lovable and Cursor."

The key is making it unavoidable. Take inspiration from other people’s experiments (the podcast How I AI hosted by my friend Claire Vo is perfect for this). Follow AI builders on Twitter and allow gentle peer pressure to compel you to try something new.

Create artificial constraints that force discomfort: "No spending more than 20 minutes on a first draft" or "Draft this presentation using only voice-to-AI tools." You’re not trying for perfect; you’re building new neural pathways through deliberate practice.

Identity attachment → Identity expansion.

Stop defining yourself by your tools and start defining yourself by your outcomes. Designer doesn't mean "person who pushes pixels"—it means person who brings about intentional outcomes (read: Higher Level Design). Engineer isn't "someone who writes code"—it's someone who builds systems that solve problems.

And who says you have to stick with labels like designer or engineer in the first place? They’re imaginary constructs. These days, I like to think of myself first and foremost as builder.

Expanding your identity ensures that AI doesn't threaten your core sense of being. A designer who uses AI to generate fifty screen variations isn't less of a designer; they're a designer freed to focus on the strategic choices of app design. An engineer who uses Cursor isn't cheating; they're an engineer who can now tackle bigger, more complex challenges faster.

Your expertise isn't in the mechanical execution of tasks; it's in the judgment, taste, and strategic thinking that guides that execution.

Love of the craft → Love of many crafts.

Love of craft is wholly pure and good because it comes from a deep care and respect for the infinity that lies within. I’d never want to convince anyone to abandon something that comes from love.

What I will point out is that love does not have to be limited. The advent of AI allows for new playgrounds of exploration. Who is to say that the animator who once lovingly inked each cell by hand might not fall in love with directing AI to create entire sequences? Perhaps their love of the visual craft may spill into a love for architecting the emotional beats of a story.

The engineer who hand-optimized code for elegance can now obsess over architecting systems of elegance; the writer who agonized over every word choice can now agonize over prompt engineering precision. I’m not saying they should want this; I’m saying they have the freedom to.

Just like there is infinity within a domain, there is infinity beyond. We are all capable of falling in love over and over again.

vi.

Last year, I wrote 189,214 words, but not all of it served the same purpose.

Sometimes I wrote to connect. Sometimes I wrote to feel. Sometimes I wrote to think.

Even within the bucket of writing to connect, the intent splits further. Sometimes in a Sundial context, I’m writing to transfer the specifics of an idea in my head to another person. Sometimes I’m sharing feedback. Sometimes I’m trying to persuade or entertain.

Today’s AI does a far better job on many of these above dimensions than I do. It writes specs more clearly. It supplants hypotheses with research. It drafts 10x faster than me. If I find myself wary about harnessing its strengths, it’s only because of my pride.

And yet. When I write to think, AI can only play a supporting role. The entire process of putting what I know in front of me IS what makes my brain sharper. There is no shortcutting this process.

And when I write to feel, what would be the point of using AI for that? It can’t feel my feelings for me.

The same can be said for coding. Maybe you hand-code on a Sunday afternoon and it’s your relaxation time. Great, no reason to give that up.

But maybe you code because you’ve promised your client something wonderful and you really really want to deliver. That’s the perfect reason to learn to use better tools.

AI isn’t an all-or-nothing proposition. There are some good reasons to stick with your status quo; there are many better reasons to notice which way the wind is blowing.

The most meaningful work will always have human soul infused in them. Somehow, in subtle ways, we can always feel when love has been poured into creation.

But meaningful work evolves as our tools do. It’s time to abandon our old shells of expertise and find newer ones to grow into.

There are many opportunities yet to invent the future.

Other articles in the Looking Glass AI series

ChatGPT launched from OpenAI on November 30, 2022, and in two short months, broke consumer app records like a bull in a china shop. It felt to many like magic.

But what was really so magical about ChatGPT? Certainly much has been said about its intelligence, aka the quality of its answers. It performs at the level of a high schooler college student now junior employee! It generates an endless stream of bedtime stories and marketing copy! It offers a sympathetic ear.

But the true magic of ChatGPT as a consumer product goes beyond its encyclopedic knowledge.

Its interface — a conversational text box that’s instantly usable by the entire world — quietly ushered in the next era of user experience design.

Alas, the conversational interface is also where AI design innovation is stuck today. Let us deconstruct and examine closely its strengths and weaknesses.

ii.

When I was a kid, I ate novels for breakfast, lunch and dinner. But the absolute worst thing you could have given me to read was an instruction manual on how to program a VCR or write a BASIC function.

Now, mind you, I was plenty technical. As far as my parents could tell, I was an electronics wizard who spoke incantations into our devices. Presto! My mom would get her daily fixing of soap operas, and my dad his cherished vacation video footage.

But how I accomplished this was puzzling over the device and trying random things. If that didn’t work, I’d peer at examples. The technical manual fell to glazed eyes; it might as well have been gobbledy-gook.

Years later, I felt the same haze when I was introduced to linear algebra. I frowned and toiled, my mind trying valiantly to do mental gymnastics. It wasn’t that the concepts were too difficult, it was something about the representation of letters and symbols and jargon. A professor one day explained state machines by drawing a series of diagrams with arrows, and suddenly my mind lit up. What do you know, I was a visual learner!

Once I learned this, life became easier. I began to see equations as scales, trees as branching arrows, ideas like clusters of constellations in the sky. Ikea manuals are my jam. Legos are my spirit toy.

Our brains are quirky, distinct things. My partner learns better through his ears than his eyes. My co-founder is ruthless about stripping complex topics down to essential math equations. I love myself a good metaphor, but one colleague finds all my best attempts confusing.

The bittersweet reality is that we humans are desperate to express ourselves and be understood, yet we speak different languages even if we share a native tongue. Too bad we haven’t invented mind-reading yet.

The next best thing? Effective translation.

The entire design discipline can be distilled into the craft of translating a creator’s intent into a user experience that fulfills the desired intent.

This is precisely where AI technology shines.

iii.

What makes for an exceptional user interface?

The most powerful rule of thumb is merely this: it feels obvious to use.

Something obvious needs no explanation. It’s as if the instruction manual has already been downloaded into the user’s brain.

And in a way it has, because the most obvious user interfaces are the ones that tap into what users already know.

When tabs for navigation were first introduced, they felt obvious to use because they mimicked physical file folders.

Digital buttons like the below feel obvious to click because they’re rendered with depth and shadow, like a real physical button.

The iPhone is more obvious to use than previous generations of phones (with up/down buttons or click wheels) and computers (with mouse inputs) because we humans are used to direct manipulation following the laws of real-world physics.

And the AI chat box interface, popularized by ChatGPT, feels obvious to use because it banks on two interactions every digital citizen already knows:

1. Conversing in natural language — something we’ve practiced since we were two years old.

2. Using an SMS / messaging interface — 25 billion texts are sent a day. A DAY. So yeah, this pattern is already well ingrained in our minds.

Sometimes designers will go to great lengths to make a user interface novel, or minimal, or simple. This is the wrong goal. Novelty, minimalism or simplicity are good heuristics for obviousness, but do not mistake the means for the end.

The technology powering ChatGPT had already launched prior to November 30th, 2022. It was just wrapped in a different interface. Very few people paid attention.

Why did ChatGPT explode in popularity? Because of its obvious chat interface, which everyone intuitively already knew how to use it.

iv.

"If you have a hammer, everything looks like a nail."

The problem with any innovation that succeeds, of course, is that it lights up a neon sign (“HEY THIS WORKS!”) that quickly grows into a neon building that then explodes into an entire Vegas Strip beckoning every dream-chaser to fast follow.

The bandwagon becomes a caravan. Our brains become like poor data models that overfit: Conversational chat interfaces for design! Conversational chat interfaces for images and videos! Conversational interfaces for coding! For news! For games!

There are 5 major problem areas today with conversational chat interfaces. Let’s examine each closely.

1. The blank page problem

Gartner famously noted when it comes to data that “80% of the value is in asking the right questions.”

Even before the era of ChatGPT, the Internet was chock full of ways to get answers.

YouTube, Khan Academy, Coursera, and Wikipedia offer free knowledge in nearly every subject. Yet average adult learning has barely increased — OECD surveys show that less than 10% of adults in many developed countries engage in any structured learning annually.

The problem with a blank chat box on a blank page is that it violates the first rule of a high-quality user experience: it isn’t obvious what I can do.

This is not a problem for early adopters and high agency people (aka everyone reading this), who love the game of exploration and thrill of discovery.

But for the broader world, a blank page box is intimidating. A blank page box is lazy.

A blank page box reminds the user of Google Search, which famously designed itself to be an efficient router to other destinations. The founders felt people should spend as little time on Google Search as possible, which I doubt is the goal of today’s AI companies.

The user experience of a conversational chat interface should help people understand how to get the most out of it.

Where are the templates for key use cases? Where are “trending prompts” and highlighted examples so users can learn from the community? Where are suggestions to continue past conversations?

Today, Twitter operates as the user manual for how to use AI services; there is enormous opportunity for the services themselves to seize the opportunity to grow engagement and discovery.

If the success of social media platforms has taught us anything, it’s that starting with something to react to works far better than showing a blank page.

2. The iteration problem

You know what’s awesome? Asking an AI agent to create a raccoon battle game and getting something that works in <10 minutes.

You know what sucks? Trying to refine that raccoon game to match the vision in your head.

If you want to swap out that raccoon image with something that looks cuter, or try out different game titles (would “Raccoon Rodeo” or “Battle of the Bandits” look better on the title screen?) or experiment with whether the game should start with character or battlefield selection, a conversational interface is extremely cumbersome.

Nothing wonderful comes out fully formed. A good creator’s journey is one through the dark ravines and jungles of refinement. Conversational UIs are great at quickly getting to the first 70%, but suck at offering easy controls over narrower areas for iteration.

If I want to play with different titles for my game, for example, the obvious thing I’d want to do is select the title and start typing out my various ideas, or click on the raccoon character and swap out the image with different ones.

Typing instructions to my agent “Can you change the title from X to Y?” or “Can you change the raccoon to be cuter?” and then waiting while they execute the change is a frustratingly slow experience. (Not to mention—sometimes they change other elements of the game I didn’t even intend!)

There’s a reason we’ve invented WYSIWG buttons and selectors and inputs. Let’s not throw that away. Sometimes, it’s faster to click on a button and rapidly change the button radius from 10 to 12 to 16 just to see how it’ll look.

I’m heartened to see editable canvases with documents and code emerging as a pattern (although I do hate “modes”). I expect we’ll see more adoption of AI-gives-multiple-variations for creative refinement.

There’s plenty more opportunity for conversational UIs to get married to traditional UIs and make beautiful babies that enable faster iteration across the full gamut of creative exploration.

3. The input-output problem

Text is an awesome medium because using the written language is obvious to many, and because there’s thousands of years of prior art invested into making language rich and expressive and clear.

Text is a limited medium because typing and tapping sucks. And a picture is worth a thousand words. And I’ll know it when I see it was the best a Supreme Court justice could come up with to define obscenity.

It’s faster for humans to speak instructions than to type them. It’s faster for eyes to scan a response than to listen to a voice read the same content.

And yet, the status quo is to assume that input and output modes should be the same. This assumption holds if I’m driving, or there’s multiple people in a room, and I want voice in and out. But if I’m doing solo productive work (which is most of the time), why not default me to the more efficient input / output mode?

If AI services can understand the user’s intent, it becomes even more obvious what the ideal input and output modes should be.

Want to get a team aligned on what we should build? Skip the PRDs and essays and go straight to prototype.

Want to help a user redecorate their room? Let the user express what they want via moodboards rather than sentences.

Want to cheer a user up? A warm voice does far more to show support and connection than words on a screen.

Before we slap a conversational interface on everything, let’s ask ourselves: what are we trying to accomplish? And what is the most obvious method of input and output to achieve that goal?

4. The scoping problem

Ever had an oblivious friend? Someone who is well-meaning, but has an opinion on everything and has no real clue what they’re actually good or bad at?

Ask them about politics and they’ll confidently rattle off what really needs to be done. Complain about a problem and they’ll tell you how to fix it.

Wise people know their scope. They can predict with great accuracy what they know better than you, and what they’re ignorant about.

When you ask an AI agent to produce something outside its zone of competence, it doesn’t inform the user: “This is beyond my current capabilities.” After repeated attempts and corrections, the agent does not suggest: “Let’s take a step back and try a different approach; this one doesn’t seem to be working.”

The AI doesn’t know whether it’s 90% or 60% or 20% confident, it doesn’t yet analyze the trustworthiness of its sources, it doesn’t fess up: “I’m not sure. My opinion leans X because…. but I’m uncertain about....”

The best-performing human teams operate with clarity on one another’s scope. Because of my engineering strength, I’m the best person to select which database we should use. Ask me a question about the design of the registration page, and I’ll refer you to the designer.

In the human world, we know that good feedback mechanisms not only improve an individual’s work, they also reflect back to that person what their strengths and weaknesses are. With that knowledge, the person can do a better job of selecting the appropriate scope for their work and asking for help when a task is beyond their level.

One day, if AI gets to superintelligence, there will be no topic where it remains more ignorant than us puny humans. But that day isn’t here yet.

Before then, why not design for awareness and clarity of scope? After all, authenticity breeds trust.

5. The personalization problem Golden Opportunity

This is the one I get giddy over because it’s the next step function change for user experience.

“I contain multitudes,” noted Walt Whitman, and its obvious truth strikes a chord. All of us present different facets of ourselves in different contexts—we don’t greet our partners the same way we greet our cousins or colleagues or strangers on the street.

Human interactions are slippery, dynamic things, the alchemy of not just each participant’s unique brain but also the group’s shared history and the moment’s specific context.

The tech world has already embraced personalization, having built an era on recommendation engines from Tiktok’s “For You” to Instagram’s (eerily) relevant ads to Netflix’s “Up Next.”

If a service knows that I am a visual learner, who likes metaphors, who prefers an honest-no-bull-shit style, then translate the message to best connect with my brain.

If I’m asking for an explanation of fluid dynamics, give me an interactive diagram. If I’m struggling through a decision, relate it to a plot point from my favorite movie. If I’m asking for an essay critique, for the love of god do not give me a compliment sandwich.

Get to know me! Check in with me on how I like things! Ask me questions not because the algorithm is optimizing for more of my time spent, but because it’s trying to get smarter about delivering me a superior experience.

One particular area of low-hanging fruit that I’m surprised hasn’t gotten more attention is AI-assisted onboarding. I’m not talking about heavy-handed wizards that everyone races to skip past; I’m imagining the feeling of a great first meeting with a new team member.

Sure, an AI service can quietly observe a user’s reactions and behavior over time to learn how to personalize—we humans do that too, but our most obvious method is asking relevant situational questions. If our boss says, “Hey, I need you to do X,” we might follow up with, “Why is X important?” or “What does success for X look like?” Knowing this makes us more likely to do work that matches or exceeds our boss’s expectations.

Today, many AI chatbots seem nearly indistinguishable from one another. Without active direction, the answers I get are nearly indistinguishable from the answers the next person gets. The opportunity here is vast.

Through better questions and better listening, through a deeper understanding of our quirky, distinct brains, the next generation of products and services can 10x their translation efficacy, whether for learning, productivity, entertainment or support.

v.

Conversational interfaces are magical, yes, but let’s not get stuck at the hype station and forget that the train of quality continues on in its pursuit of ever more obvious interactions enabled by AI’s technological breakthroughs.

The holy grail of effective translation is there for the taking. Yes, it’s a wonderful time to invent.

Other articles in the Looking Glass AI series

i.

Less than a month ago, the Internet went ablaze with ChatGPT’s new 4o image launch. The killer use case was seeded first in an OpenAI launch video, and then by one Grant Slatton: Turning photos into an art style made distinctive by Japanese animation studio Studio Ghibli.

Within a day, legendary movie moments, Olympic highlights, photo memes and world leaders were were all rendered in the dreamy, gentle style of Hayao Miyazaki.

“Art just became accessible.” one X user declared.

Unfortunately, this statement confuses the definition of art. It supposes that quality work comes from the power to recreate an artistic style.

But art is not style. Quality work has always been preoccupied with hovering at the precipice’s edge. It’s arresting because it’s novel. It’s striking because it’s rare.

Rather than making the art of Studio Ghibli accessible, ChatGPT’s launch has turned it into something else entirely: a commodity.

It has staged a coup on quality work, erasing and redrawing the lines for where the edges of greatness now lie. Let’s investigate how.

ii.

It’s been a month. Ask yourself: how do you feel now when you see an image rendered in Studio Ghibli style as you scroll along your merry way? (Say, for example, catching a glimpse of Sam Altman’s profile pic out of the corner of your eye?)

Do you still marvel to yourself, “Wow!”

Do you muse at the decades of advancements that made such an avatar possible?

Do you take the time to appreciate the delicate lines and expressive eyes?

Or do you breeze past, dismissing it as another person late to the trend, the whimsy and color now registering as background noise while your eyes dart around searching for a more thrilling next hit of dopamine?

The second watching never commands the same awe as the first. The 20th bite doesn’t dance on the tongue as exquisitely. And the 200th anime portrait certainly no longer impresses the way it once did.

The sad truth is that oversaturation strangles quality. Nothing too easy can truly be tasteful.

iii.

What made Studio Ghibli so quality to begin with?

There are a few reasons. The first is that when you see an actual Studio Ghibli still, it cuts differently.

Whereas the ChatGPT versions traffic in the mundane — people at the park, at home, at a restaurant—stills from an actual Studio Ghibli film feel otherworldly.

There are translucent ghosts keeping company with children, adorable bunny(?)-like creatures romping in a garden, determined protectors scowling next to their badass mythical sidekicks.

And they’re not really still images. As any Studio Ghibli fan will tell you, much of the magic of the pictures come from the actual movies they are a part of.

Grant Slatton's wife, presumably a Studio Ghibli fan, would likely have seen the image he created within the backdrop of its moving epics—ones where troubled children convene with spirits, where colorful characters are swept away by the magic of the everyday, where blades of grass rippling in the wind evokes a feeling of emotional presence. She might have imagined the soaring soundtracks of Joe Hisaishi in her ears.

The quality of seeing a Studio Ghibli image can't be separated from the quality of the movies themselves.

Of course, part of the awe surrounding Studio Ghibli comes from how its films are made. Director Hayao Miyazaki, often called the world’s greatest living animator, personally storyboards each film by hand and oversees every stage of production. Now in his 80s, he remains deeply involved in the studio’s creative process.

A typical Ghibli film may take over 100,000 hand-drawn frames, crafted over years by teams of skilled animators. (A single 4-second scene may take months!) In an era dominated by CGI, the studio remains committed to the traditional, painstaking beauty of 2D animation. The reverence many fans have for Ghibli is not just for the stories it tells, but for the rare artistry behind them.

And let us not forget the prestige the studio has earned. Spirited Away claimed an Oscar. The Wind Rises drew crowds at Venice. Princess Mononoke turned heads in Berlin. At the Studio Ghibli office, fan letters from Pixar Animation Studio are on displayed. Billie Eilish quoted Spirited Away as her favorite movie. Guillermo del Toro and James Cameron cited its influence in their own work. Many who apprenticed under Miyazaki have gone on to found studios of their own. Like wind through grass, his influence ripples across generations.

AI-generated images in the “Ghibli style” may borrow its surface features but they don’t capture the soul of what makes Studio Ghibli exceptional in quality. They lack the narrative depth, the handcrafted devotion, and the cultural resonance.

Like a celebrity impersonator, the ChatGPT images borrow from the cache of the original. But sadly, hollowly, it’s not the same. What made the original shimmer is lost in translation.

iv.

But aren’t the ChatGPT-generated Studio Ghibli images also quality?

Yes, but of a different sort, in a dimension that’s inherent to its technological innovation.

You see, ChatGPT could offer a flavor of magic that Studio Ghibli could never achieve, the magic of personalization.

Placing oneself within the context of another world is cutting edge, novel, rare. After all, one of the noblest purposes of art is connection. Around Japan, you can't go a block without stumbling across Totoro merchandise enticing you to take home a piece of a beloved story. But how much more exhilarating, how much more connective, is seeing yourself as a part of that world?

The quality of Ghibli-fication is the quality of the new image model itself, one that could produce so convincing an on-the-fly facsimile of a photograph in a particular style that it created a "moment" in public consciousness. ChatGPT 4o beat out a number of other image foundational models for this prize.

And let us not forget Grant Slatton's insight, for it is quality also — being among the first to discover a use case for an emerging technology that not only won points with his wife, but also inspired widespread mimicry. (His post saw more than 50M views and inspired many thousands of others to try Ghibli-fication). He himself recognized this as alpha, the secret knowledge before it becomes mainstream, borne from an aha moment of exploration and discovery.

There are scores of these novel discoveries made every day with each new AI model. Collectively, the world is learning which models are precisely better for which tasks when directed in which specific manner. Every discovery grants its originator a fleeting advantage—a window to create something more useful, delightful, or efficient. Yet, as knowledge disseminates and competitors copy, this edge diminishes, leveling the playing field.​

This is the game of technology, and why playing at the cutting edge offers abundant opportunities to find and deliver exceptional quality.

The key is not confusing the quality of a technology with what it makes easy. What we are seeing is a quality coup. Producing a Ghibli-fied image or a Mona-Lisa-style portrait or a Picasso-like painting will not create quality art; those islands are already too well mapped. In fact, all visual imagery as a category may soon feel tired for this very reason.

Perhaps here we can learn from Studio Ghibli itself. To ascend to the next plane of quality-hunting, we need the richness of a narrative, commitment to a specific craft, and multiple mediums of expression.

Quality, like a dazzling sunset, is dynamic. Ever second it is changing and receding until it flickers out. You cannot grasp it for long. You can only keep turning a new corner of exploration and hope you're lucky enough to encounter it again.

v.

Was it good for OpenAI to enable Ghibli-fication of images?

Some called it “AI slop.” Artists decried AI being trained on copyrighted work. Any new disruptive technology threatens the livelihoods of countless humans.

Hayao Miyazaki himself, in a 2016 documentary, said after seeing a demo of AI-generated art: “You can make horrible things if you want, but I want nothing to do with it… It is an insult to life itself.” (Granted, the demo was extremely grotesque — exactly why those guys decided to show it to Miyazaki is a head-scratcher).

If this is still how he broadly feels today, one imagines he must have been shocked and appalled by last month’s events. The wound must have cut deep—oh, the cruel irony that his life's devotion to hand-crafted art would culminate in a flash-in-the-pan AI meme!

Yet others call this progress. There are those that argue the exposure Studio Ghibli has gotten, even if it hadn’t been compensated for the model training, is likely worth untold millions in new revenue. The exposure further cements Studio Ghibli's legacy! (Would any of us be writing these essays otherwise?)

Miyazaki is at the twilight of his life, without a clear successor for the studio. Another way to tell the story is to view AI as humanity's collective brain, allowing individual creations to live on in the ever-changing tides of evolution.

We don't yet know the facts of how OpenAI’s anime images came to look so similar to Studio Ghibli’s style. Did they explicitly train on Ghibli’s work? Did they have permission? No one has said anything definitive. For many, knowing these facts may change their judgements of whether this was morally "right”.

Yet a similarly important question is: how much does it matter? What's past is past. Studio Ghibli had its AI meme moment. There will be many more to come in the days and weeks ahead.

The Pandora's box of technology cannot be slammed shut. AI will continue to grow more powerful. Like any tool, it can be used poorly or wisely.​

It's up to us now to make like explorers and discover all the quality ways to harness it.

i. The EPD stool and the two-pizza team is dead

When I was a kid, I loved Captain Planet—that ’90s cartoon where five teens with magic rings (Earth! Fire! Wind! Water! Heart!) teamed up to fight eco-villains.

At the time I thought the series was so incredibly original. (I mean, the planet personified in an aqua dude wearing tights?!)

Little did I know I was looking at a well-known archetype emulated later by the likes of Power Rangers, Teen Titans, Avengers, and tech product teams across the globe.

For decades, the traditional tech team looked something like this: Engineers (3-5 of them) + PM + Designer = good stuff built. Sometimes, we’d add more “rings” (Sales! Data! Marketing! Customer Success! User Research!) to fight bigger villains while trying to abide by the best practice that 2 pizzas should be able to feed this group.

In the era of AI, all this breaks. It’s time for a new group of heroes to take the stage.

ii: The death of mocks and docs

Traditional product development has been best practice-ized until it resembles an Ikea instruction manual:

1. The Idea (conceived in enthusiastic brainstorming chats deemed “groundbreaking” and “innovative”)

2. → Mocks (polished until it’s a sparkling good storyboard for stakeholder alignment)

3. → PRD (a beautifully formatted 12-page novella admired by many but read closely by precisely zero)

4. → Code (with deadlines extended as frequently as the MCU)

5. → Launch (with ample hopes and dreams and craft beer and pizza)

6. → Surprise! (most of the time, the surprise is why users reacted with a collective shrug rather than thunderous applause)

This worked when software moved in cycles of months. But now that we have AI at our disposal (who is today an insanely productive, cheap yet junior talent that must be aggressively micromanaged), that tidy linear path is going the way of the dinosaurs. Ask yourself:

• Why brainstorm for hours when AI can generate 50 ideas (and roast the bad ones) in minutes?

• Why show static mocks when AI can build a version of the damn thing for your stakeholders to play with?

• How much effort should you put into your PRD when AI changes the rules of what’s possible every other Tuesday?

• Why spend a bunch of time debating engineering flows when you can’t deterministically predict what the technology will do?

• How much more would you achieve if you could learn the Surprise! of your launch in a fraction of the time?

iii. The prototype-and-prune path is the future

Forget IKEA manuals. You don’t want to be stuck in a situation where you follow every step, screw by screw, only to realize halfway through that what you actually need is a ladder.

The future of product development looks like this:

1. The Idea Garden

   Don’t settle prematurely. Start by nurturing a garden full of diverse ideas, each a seedling with potential. Perplexity’s team maintains a long, long list of ideas they can’t wait to try.

2. → Prototype-and-prune
   The bulk of future product development will be spent researching whether an idea has legs. Say goodbye to cycles of mock and doc feedback, and say hello to code-first prototypes with constant iteration (on prompts, models, etc) to answer three key questions. If the answer to any of the below is no, the idea is pruned.

   1. Capability: can this idea be done with today’s technology?

   2. Accuracy: Will the results consistently meet the user’s expectations?

   3. Speed: Can it perform smoothly and quickly enough for real-world use?

3. → Polish-and-productionize
   Once an idea demonstrates clear promise, it can now get refined for real customer launch, whether to a small beta group or beyond. This is the time for optimizing, aligning with brand vibes, and coordinating release logistics and communication.

4. → Launch
   Still with plenty of hopes and dreams and craft beer and pizza

5. → Further pruning
   Selectively prune ideas that don’t thrive in real-world testing, swiftly retiring unsuccessful experiments to free up space for fresh seeds.

iv: AI favors the individual contributor

Imagine you're assembling a team for an escape room challenge. Would you rather have six managers debating strategies or two sharp thinkers who rapidly test every combination to unlock the door?

Welcome to the era of AI-native companies, where individual contributors (ICs) reign supreme.

Prototype-and-prune calls for teams with the following 5 characteristics:

1. Tiny teams working in parallel — teams with a handful of people (think 1-3) can simultaneously explore a wider range of ideas to see if they work.

2. Blurred functional roles: why do you need a stool with three (or more) legs when a classically-trained engineer can use AI tools to iterate on mocks, a classically-trained designer can use AI tools to iterate on marketing copy, or a classically trained product manager can use AI tools to get insights from their data?

3. Reduction of “management” roles: the cost of communication overhead shrinks drastically when you go from 7-10 people to 3. The PM-as-coordinator, or manager-as-coordinator role is no longer needed until (maybe) the polish-and-productionize step.

4. Good taste: taste is the ability to distinguish excellence from mediocrity. The hand can never consistently produce better than the eye can discern.

5. High agency: AI favors those who bias towards action and see themselves as problem solvers with the power to get shit done. Those who prefer structure, consensus, and waiting to be told what to do will find themselves struggling.

v: How to Survive (and Thrive)

For leaders:

• Hire curious generalists, not specialists.

• Track speed of feature development: ensure that it’s going up.

• Reward doers over sayers: look for the proof in the problem solved, not in the discussion had

For ICs:

• Identify as a problem-solver: not an engineer / designer / pm.

• Make AI your constant collaborator: experiment, experiment, experiment with doing things you would have previously relied on a teammate for. Experiment with doing whatever you know how to do well even faster.

• Just do it: try stuff out, don’t wait around for permission.

For Everyone:

• Embrace the chaos. The future isn’t built on plans—it’s grown in gardens.

Other essays in the Looking Glass AI series

i.

A prominent billionaire gave a graduation speech the other day. The key message? Work hard to be successful.

Another prominent billionaire gave a graduation speech a year later. The key message? Working hard is bad advice. Do what feels fun for you to be successful.

Europeans mock Americans for working too hard. Boomers lament Millenials for laziness and entitlement. Republicans fume that the work ethic America was built on is eroding like cliffs against crashing waves of handouts. Democrats believe that too much work is making us sicker and lonelier.

Today, hustling competes with YOLO. The search for spirituality wrestles with the quest for commercial success. Slow down and meditate! Hurry up and embrace AI! Technology will reduce our toil. Technology will kill our spirit.

At the heart of these debate lies the ever-pulsing question: what is the merit of hard work?

I don’t care to argue here whether hard work leads to material success.

What I want to suggest instead is that hard work is necessary for our happiness and well-being.

As it turns out, our souls needs proof of work.

ii.

What exactly is hard work?

I’m going to go with the simplest definition: hard work is whatever you personally feel is hard for you.

Hard means effortful; hard means discomfort; it takes something out of you to do it.

Hard is deeply personal.

For some people, the repetitive labor of digging weeds under the hot sun would be considered hard. For others, gardening is a relaxing hobby. For some, being in front of a crowd feels like chewing glass. For others, it’s as effortless as breathing.

You know what’s hard for you.

iii.

Let me ask you — what do you want for?

Perhaps you aspire for the keys to a gorgeous house with amazing light. Perhaps you wish to sample croissants in Paris and curry in Kyoto. Or perhaps your dreams are simpler — a rocking chair with a good book, cat purring on your lap.

I have gone through a million incantations of wants. When I was younger, I wanted what I saw on every fifth cartoon commercial — the doll that could whirl through the air when you pulled a string, the dog stuffed with three or four or five babies (surprise!), the miniature playground that fit in a compact (hi Polly!). I wanted the honey-blessed cereals and the jiggling jellos. I wanted freedom in a shopping cart.

As I grew older, those wants switched styles. Now it was bell-bottom jeans and tiny backpacks. Now it was tickets to the latest shows, the smile of a cute boy, the privacy of my own space. My wanting was ferocious; some call it ambition. I was the cliched American dreamer, wanting the lives I read about on glossy pages, in young adult novels, on rich people shows.

You know what they say. Be careful what you wish for, because you just might get it.

iv.

My father wasn't around
I swear that I'll be around for you
I'll do whatever it takes
I'll make the world safe and sound for you

Alexander Hamilton and Aaron Burr, Hamilton the musical

It is a tale as old as time: loving parents who have suffered want nothing more than to shield their children from pain.

Those who labor tirelessly to put food on the table push their kids onto certain paths (competition, college, medicine/law/engineering/mba) so they can attain the North Star of being comfortable.

Comfort is our religion. We hear its seductive whisper everywhere: Isn’t your life stressful enough? Why keep talking to people you disagree with? Why endure inconvenience when groceries, meals, and weed can come straight to your door? Why brave the hassle of your car when you can Zoom from home, fuzzy bunny slippers and all?

And if you must travel, why not let a car drive you? And if you want intimacy, why expose yourself to awkward introductions when you can effortlessly swipe? And if even swiping feels tedious, why not dig into the infinite carousel of graphic videos just a few clicks away?

And let’s not forget our new friend, AI. Humanity is about to be made over by the power of intelligence. Why should only the privileged have assistants? AI will plan your week, do your shopping, write your emails, curate your movies, gather your research.

This is just the start. Soon, AI-driven robots will tackle our cleaning, dishes, and childcare. AI therapists will say exactly what we crave to hear. AI will craft films tailored precisely to our personal tastes, and write novels so perfectly attuned to our desires that disappointment becomes obsolete.

Every new technology, service, and business promises to sweep away life's inconveniences. With a magician’s sleight of hand, they dangle attractive people and catchy jingles at every turn, beckoning you towards an endless buffet of fulfilled wants.

The siren song of the world’s largest corporations echoes the enduring message of devoted parents throughout history: to be comfortable is to be happy.

Yet this just might be the greatest lie we tell ourselves.

v.

Wanting has a mascot, and its name is dopamine—those tiny carriers of motivational signals zipping around our brains.

When dopamine first captured scientific attention, it was dubbed the chemical of pleasure. We believed that more dopamine equaled more happiness, but that’s only partly true. Dopamine is less about experiencing pleasure and more about driving us to seek future rewards. It's the thrill of anticipation rather than satisfaction itself.

Normally, our brains maintain a balanced dopamine state. But when something rewarding happens—the sweetness of honeyed cereal melting on your tongue, the joyful cha-ching of the register as you clutch a shiny new purchase—dopamine floods your system, spiking above your usual baseline. Suddenly, you're on cloud nine; angels sing and life feels incredible!

Soon enough, however, that sensation fades. Dopamine levels return to baseline, leaving behind a lingering whisper in your brain: Didn’t that feel great? Do it again! And so you do.

Yet each subsequent reward tends to deliver a slightly weaker dopamine spike—a phenomenon economists call diminishing marginal utility, explaining why the tenth bite never tastes as delicious as the first.

But dopamine has another, darker trick up its sleeve. Repeated dopamine surges alters the brain's wiring, reducing sensitivity to natural rewards. Each surge, like a crooked accountant skimming profits, subtly changes the way your brain responds, reducing your ability to feel pleasure and increasing your craving for more.

When dopamine hits are few and far between, your brain has time to reset. But constant dopamine stimulation starts changing your brain's chemistry, lowering its sensitivity to rewards. You begin to feel worse by default, craving increasingly intense stimulation just to achieve your original baseline of pleasure.

This destructive cycle is at the core of addiction, explaining why addicts become increasingly irritable and desperate without their fix. Their brain chemistry now needs the addictive substance or behavior just to feel "normal." Feeling pleasure demands ever-higher stakes.

Even if we’re not talking about heroin or slot machines, this pattern is everywhere. Remember when 12 likes on social media felt amazing? But then you posted a puppy hugging a koala—10,000 likes! You’re ecstatic! Yet future posts garner just 300 likes, leaving you disappointed, even though 12 once thrilled you.

Like an insatiable investor, dopamine constantly screams for Bigger! Better! More!

Satisfying dopamine’s demands is a losing game. The only way to win is to .

vi.

In Japan, often seen as a harbinger of the future, birth rates are declining sharply. Family units are unraveling, and there is the troubling rising of hikikomori—people who choose to no longer leave their homes.

These individuals, ensconced in the womb of modern conveniences—limitless internet, endless food deliveries, on-demand entertainment—have relinquished real-world connections. Yet this group is six times more likely to experience mood disorders than the general population.

This is the hidden trap of comfort: the easier and quicker our desires are fulfilled, the more our brains recalibrate. Getting what we want, without struggle or delay, numbs our ability to experience real joy and satisfaction.

In short, being too comfortable actually makes us miserable.

vii.

Have you heard of the Ikea effect?

In one study, subjects were willing to pay 63% more for furniture they assembled with their own hands than for an identical pre-assembled piece.

We tend to love what we pour effort into.

Comfort and convenience are valuable for the time it frees up. But how we use that time matters. We need voluntary challenge, not the empty victory of quick dopamine hits. Research into discomfort—like ice baths or cold showers—shows these short bursts of voluntary hardship boost mood, reduce stress, and build greater resilience.

Similarly, intermittent fasting — voluntarily making yourself hungry – has been linked to better emotional stability. Individuals experienced in fasting show greater resilience to negative events than non-fasters.

Paradoxically, doing hard things makes us happier. Putting ourselves through struggle makes us better equipped to enjoy life.

viii.

After my first big payday, I treated myself to all the things I’d ever wanted.

I flew to Paris and Tokyo. I ate the croissants and curries. I got a cat and read books with her. I found a gorgeous house with amazing light.

With each want fulfilled, my dopamine soared. But you know the story by now—it always came crashing back down, sometimes lower than before.

I became a food snob, I complained about my cat’s shedding, I declared I could no longer work productively in rooms with poor lighting.

And the list of wants never shrunk; as soon as something was checked off, the next one zipped in to take its place.

I designed and shipped countless iterations of software promising comfort and ease. My best works were greeted enthusiastically for about a week. And then the world moved on, sniffing for the next innovation. Nothing lasts except the hunger.

It took me far too long to spot the pattern: nothing I ever attained satisfied the fundamental wanting; ergo there is no thing that ever would.

But I noticed something else: there was long-term satisfaction to be found in my journey. It wasn’t in the attaining but in the becoming.

The process itself, of becoming the kind of person who could make useful things and earn a living doing so, was a joy. As was the process of deepening the craft of exploring or reading or writing.

A new type of wanting crept into my mind.

What if, instead of easy comfort, we wanted for challenges that transform us into better version of ourselves?

I want to be a person of warmth and depth and courage. Perhaps you want to be the kind of person who can run a marathon, or make a room belly-laugh, or be a young kid’s superhero.

We’re going to have to change something of ourselves. And this capacity for change is rooted in the extraordinary plasticity of the human brain. Can you guess what it takes for our brains to learn new skills?

Yep—effort and strain. Growth demands focus, alertness, and perseverance. We must embrace mistakes and grind through the hard. Only through discomfort can we feel the pride of accomplishment.

Don’t work hard for the money, or the promotion, or the accolades. All of that fades.

Don’t work hard because some authority figure said so. Life’s too short to live someone else’s script.

But ignore the whispers that beckon you towards the easy wins. The deepest human relationships come from accepting the best and worst of one another. The greatest love for a craft comes from discovering all the endless ways to be humbled by it.

Work hard for yourself, for the joy you feel when you’re one step closer to the person you’ve always wanted to be, whether it’s getting in the dirt to make things grow, getting in front of a crowd to speak your truth, or going out to find love behind all those brambles.

Our souls needs proof of work to sing.

Other essays in the Looking Glass AI series

Here’s a seeming paradox:

1. Every great manager I know tells me that the reports they find most valuable are the ones who convince them to do things differently.

2. However, most reports believe they are most valuable when they do what their manager wants.

These axioms have been true in hundreds of promotion discussions I’ve been a part of. They’ve been true in my own life. The people I value the most are the ones who regularly challenge my thinking to present different and better ideas.

So how do we circle this square? I present to you the midwit curve, which is my favorite encapsulation of everything in life:

The worst reports…

…do what they want but in a way that goes against the team’s interests.

These are the folks who blow past deadlines because the sequel to their favorite video game just came out that week. The ones who put up an “off-the-grid” message right after checking in a massive buggy commit. The ones who decline a double-digit percentage of meetings because they’re slightly inconvenienced—it’s too early, or too late, or they’re too hungry, or their brains are too fried.

Since a manager’s job is to make teams successful, a member who lets the team down because they are optimizing for themselves is obviously a thank u, next.

The average reports…

…support and do what their manager says. If the manager goes, “Let’s do Project X” they shrug their shoulders and ask “When?” and “How?” even if Project X is kinda loony.

There are a few reasons why folks adopt this strategy:

1. They are optimizing for promotions and they genuinely believe that “Do what my manager says” is the best path to attain that.

2. They are optimizing for team success but they genuinely believe their manager always makes higher quality decisions than they do.

3. They are optimizing for comfort / ease and thus prefer to avoid the energy-consuming work of critically evaluating how they feel about Project X.

Since a manager’s job is to make teams successful, this type of “yes-boss” report is generally useful to have around. They are reliable. They get shit done. They don’t spin up drama.

However, their presence doesn’t do much to strengthen the team. In fact, the team’s success is fragile, banking entirely on the quality of the manager’s judgements.

The best reports…

…do what they want but in a way that furthers the team’s interests.

If the manager goes, “Let’s do Project X” they ask themselves, “Is Project X smart or loony?” If they think it’s loony, they dig further until they either a) now believe it’s smart or b) propose an alternative that’s smarter.

Even if they do support Project X, they ask, “Am I the best person to work on Project X?” If yes, then they’re all in. If not, then they volunteer for some other project.

Since a manager’s job is to make teams successful, these keen people who peer critically at plans with the goal of spotting and strengthening holes are worth more than a truckload of rubies. Most CEOs I know would trade multiple “Yes-boss” types for a single one of these Jedi.

So, what does this mean for you?

If you want to be a top performer, if you want to be a leader or among the most valued folks at your company, you’re probably not going to get there by yes-bossing (unless your workplace is one of those super hierarchical types).

Instead, to become a Jedi, you’re going to need to:

a) care a ton about your team’s success

b) develop excellent judgement

c) do things your manager isn’t directing you to do because you care about your team’s success.

The good, bad, and ugly of hierarchy

What’s wrong with workplace hierarchy? Aren’t we humans by nature hierarchical?

Before we go critiquing hierarchy, let’s first define it:

In a workplace setting, this is generally taken to mean that some employees are considered above, below, or at the same level as others.

This is nothing earth-shattering; after all, it’s no secret that CEOs are higher in level than other employees, and that the Board is higher even than the CEO. On the flip side, at the lowest rung of the ladder we have the intern.

But what do we mean when we say “level?”

One common definition is the power to decide. For example, a CEO can choose to fire Bob. An intern can’t fire Bob.

This power to decide is useful because imagine if the intern, Bob and the CEO disagreed on whether Bob should be fired. They’d talk in circles until the cows came home, which would be wildly inefficient! So one way to cut the conversation short is to assign a decision-maker. Hooray! Now someone makes the call and we can all move on.

But hang on. We don’t just want fast decisions, we want great decisions, decisions that propel our company into the starry echelons of success.

Most of us would agree that a CEO likely has better judgement than an intern on whether firing Bob is a smart decision for the company. So another job of hierarchy is to identify and enable the most qualified people to make the best decisions.

If we lived in perfectly perfect hierarchy, all of us can sleep easy trusting that our CEO would always make better decisions than a VP, who would always makes better decisions than a director, who would always make better decisions than a senior, who would always make better decisions than a junior, who would always make better decisions than the intern.

Alas.

Alas, alas. I hope you can see how laughably far we are from that world.

The reason the Valuable Employee Paradox exists is that company hierarchies are far from perfect.

While a CEO is expected to make higher-quality decisions than a VP of Engineering on matters such as How to hire a CFO?, Should we move our product upmarket or downmarket?, Should we merge with Company Y?, the VP of Engineering is typically better equipped than the CEO to decide Where should we look for the best engineers?, Should we use a streaming or non-streaming database? Should we fire Bob the engineer?

You see this pattern recursively down the entire organization. An engineering director may be better positioned to know the ins-and-outs of the Android platform than an engineering VP. A senior engineer with a background in machine learning may create a better ranking model than a director. A junior engineer may fix a bug in a code base they know well faster than a senior engineer.

Whatever well-meaning system of levels or titles a workplace may come up with, it simply cannot encapsulate all the nuances of good judgement that come from skill and domain knowledge.

If you become a zealous adherent to the idea of hierarchy—a person at a higher level will make better decisions than a person at a lower level—you’re going to be wrong. A lot. Being hierarchical is a mindset—company cultures can be overly hierarchical, and so can individuals.

A strongly hierarchical company CAN operate well if the higher level folks are humble and self-aware enough to know when they should make the call and when to defer decision-making to someone else. But if they aren’t self-aware, or the problem space is highly complex (which leads to greater % of unknown-unknowns and therefore worse judgement of who knows what best), then the higher-level managers will make a lot of shitty calls. The company will eventually pay the price.

The point of any system of hierarchy is to enable faster, better decisions. Things get bad and ugly when people forget that.

There are 3 more chapters in this issue for paid subscribers

1. Is your workplace too hierarchical? A checklist.

2. Are you too hierarchical? A checklist.

3. The antidote to hierarchy

Big thanks to all my paid subscribers! You all keep this newsletter going.

Read more

Where has the time gone? The sun casts its daily spells and now the twilight of another year upon us.

I’ve spilled much digital ink this past year, but I’ve been negligent on this blog as of late. My mind has been in other places — with my company, my family, or simply trying to observe itself like some kind of ouroboros. I’ve watched roiling waves. I’ve lived weather.

I’ll conclude 2024 not with any recent insights, but with a portion of a project that I’ve been working on and off on. It’s a series of letters to my daughter, about everything I’d like her to know about the world. Which of course raises the question: What do I really know about the world?

The honest answer today is: Very little. Even now, when I look back on earlier letters I’ve written, I find myself doubting what I say. It seems that everything I put into words, my mind can also find a way to negate. More and more, this experience leaves me humbled. What a trip this continued search for Truth is!

Thank you for being with me for another year, dear Readers. I wish the warmest glows upon you this holiday season. I wish you every type of happiness there is.

Yours,

~Julie

Aladdin and the Three Types of Happiness

Dear LenLen,

Do you remember the movie Aladdin, about a poor boy from the slums who, along with his ill-mannered monkey, goes to the Cave of Wonders and finds a lamp inhabited by a magical genie?

The genie tells Aladdin he’ll grant him 3 wishes.

Now, this is the kind of scenario that all of us dream of.

3 wishes!

What would you wish for, LenLen? Write it down below:

Here were some of my answers from when I’d play this game as a kid:

1. More wishes — alas, this is cheating and not allowed as per genie-rules

2. World peace — who wouldn’t want less fighting in the world?

3. Ability to fly — because that sounds so fun

4. Ability to read minds — never be stumped on a test again

5. Everyone always like me — particularly useful during those angsty teen years

6. Ability to control time — keep those amazing Saturday nights rolling for weeks… or months!

Honestly, I thought Aladdin did a poor job of making wishes. His first wish was Make me a prince in order to impress Jasmine, which has 2 big problems — 1) Jasmine is zero impressed by princes 2) wishing for a finite amount of gold and elephants is obviously less useful than wishing for a skill that can create an infinite amount of gold and elephants.

Imagine if he had wished to be the world’s most effective salesperson instead — then that gold and elephant train would never end!

Aladdin’s second wish was Save me from downing! — again, a C-plus wish at best because why not go for something longer-lasting, like Let me be strong enough to break my chains or Let me breath underwater?

To Aladdin’s credit, his third wish was pretty good. (Plus, he got the ability to fly without even wishing for it, with that adorable magic-carpet-puppy.)

Now that I am older, the question of “What should I wish for?” becomes cliche as to be boring: I wish for unending happiness for every living!, a sentiment also shared in a three-hundred year old popular Christmas song.

Could anything be more aspirational? After all, isn’t the whole point of everything we do — marrying a princess, acquiring gold, freeing a genie — towards happiness?

But as we’ve discussed before, happiness is an elusive rainbow that never stays. So how could a genie even fulfill this wish?

The good news, LenLen, is that there’s been quite a bit of research done by scientists on what happiness is and how we can capture more of it. Through their good work, we have some clues on how we can live happier.

It helps to start by asking ourselves: What does happiness feel like, and what things cause us to feel happy?

You might notice that there are actually a few different flavors of happiness.

For example, how would you compare the below?

1. The happiness of eating a plate of your favorite sushi

2. The happiness of working on and then completing a challenging Lego set

3. The happiness of helping your teammates work together to win a soccer game

Happiness researchers notice this too, and they have theory for what makes these buckets different.

The first (eating your favorite food) we’ll call pleasure — that momentary feeling of joy that you get from rushing down a water slide, or taking a bite of cold, creamy cookies-n-cream ice cream, or listening to your favorite Taylor Swift song.

If it feels good in the moment and delights our senses, we can say that it is pleasurable. The pleasure of a moment tends to increase if we do it with others (imagine going down a water slide with a friend) because it’s more likely to turn into a long-lasting happy memory.

The second bucket is enjoyment. Enjoyment is different from pleasure in that it needs an element of challenge. The reason we enjoy a complex lego set, or passing a video game level after failing a bunch of times, is that it feels fun to master the challenge.

We crave a sense of accomplishment and pride, which only comes when we’re working in our challenge zone. Of course it can’t be too hard — then we get discouraged. (This explains why you don’t want to play Peek-a-Boo all day long—when things are too easy and lack challenge, we call it boring.)

Finally, the third bucket is satisfaction. Satisfaction is different from the other two because it is rooted in a sense of greater purpose. When you feel a sense of purpose, you aren’t just trying to help yourself, you’re working for something that is bigger than yourself.

For example, a player on a soccer team typically cares more about helping their entire team win than gaining prestige for themselves. When they do their best to defend an opposing player, or pass the ball to a better scorer, they feel immense pride in the overall team’s victory.

What’s interesting about looking at these distinct flavors of happiness is that we need to do different things to achieve them!

For example, increasing pleasure means you would focus on doing the things you like more often, and try to do them with more people, even if there isn’t much challenge or greater purpose. More sushi! More water slides! More Taylor Swift songs!

Increasing enjoyment means seeking out challenges which might actually conflict with increasing pleasure. For example, you might choose tough exercises that tire out your muscles (which doesn’t feel as pleasurable as lounging around watching Netflix in your PJs), but after some weeks or months, you feel pride in being able to easily scale the Ninja Warrior challenge course.

And finally, increasing satisfaction means dedicating your hard work towards something that gives you greater meaning.

What is that greater meaning? This is something we all have to find for ourselves.

Your Daddy and I feel that raising you and your siblings have given our lives a deep sense of purpose — even if it’s hard work and not especially pleasurable in the moment (let’s be real—when you kiddos are all crying your heads off in the car, it’s certainly not pleasurable!) But we feel fulfillment when you learn and grow and experience the wonders and joy that every day brings.

Some people feel this sense of meaning with their jobs (I do with creating Sundial!), or volunteering for their community (like Daddy does when he hosts events for your school), or fighting for their country, or advocating for a cause they passionately believe in.

The day-to-day work may be grueling and difficult; it may not pay much (if any) money; it may not even always be properly recognized or appreciated. But these people don’t do it for pleasure or glory. They do it because they want to make a difference for others, and that creates its own rich well of happiness.

So, if there’s anything for you to take away from this letter, LenLen, let it be this: 1) Aladdin should have made better wishes 2) I hope you’ll find happiness in spades and 3) Think carefully about how you balance seeking pleasure, enjoyment and satisfaction — in my experience, doing more of the second and third tends to last longer.

With tremendous love,

Mommy

I used to think the glittering prize of a hard-fought battle, of a well-played game, was winning.

But winning what, exactly?

Was it the glory, the pride, the winner’s identity? Was it the smug satisfaction of rightness? Was it the cha-ching of the bank account, was it the compliments scattered in my face like petals?

Here’s what I want to win now: trust.

This essay is adapted from a letter I sent to my team at Sundial.

Warmly,

~Julie

A definition of trust

Let me posit something both stupidly simple and outrageous — trust makes the world go round. Our team will be nothing without it.

Because it is so fundamental, so life-giving. I want to excavate and understand it deeply.

Let me offer first a definition for trust:

Right away from this definition, we can see that trust is a relational idea. It exists between me and you, and it exists within some particular context.

If I trust you to tackle Problem X, I am saying that I believe you will do what it takes to find a solution to Problem X that fulfills the criteria I have in mind.

If I say “I trust you with my life” and we are in a high-speed car chase, I am saying that I believe you are a capable enough driver and that you care deeply enough about me to ensure I don’t die.

Why does trust matter?

Trust matters because everything would be painfully inefficient without it.

Imagine you and I are complete strangers, plucked from the lottery of life by alien forces that conspires to bring us together for an important task—making an apple pie. How will we go about this?

Since we don’t know anything about each other, I will start with an empty trust bank for you. I have no idea what you are capable of, or what you care about. Many doubts flit through my mind, like:

• Do you even know what an apple pie is?

• Do you know the ingredients in apple pie?

• Do we know where to get these ingredients?

• Do you know the tools we need?

• Do you care at all about this task?

• Do you do what you say you will?

• Are you capable of operating an oven?

• Can you handle slicing apples?

• Do we agree on the right proportion of these ingredients?

• Do we agree on the distribution of tasks between us?

• … and so forth and so on

Getting signal on this entire list of questions will take time. Some of the above I can try to get at through conversation (for example, asking you in a friendly manner about your familiarity with apple pie / ingredients / tools / etc).

But a bunch of these I can’t know without seeing you in action. For example, I can’t know whether you’re a person of your word until you show me you are. Until then, the jury’s still out and I’ll need to observe you carefully.

Contrast this with making apple pie with a sibling. It’s probably going to be way more efficient. Why?

For one thing, we can assume shared knowledge. My sister knows what apple pie is, what the ingredients are, where to get those supplies in the kitchen, etc. We don’t have to spend time talking about that.

For another, I have a deeper understanding of my sister’s skills and experience. I know that she can handle an oven. I know she’s diligent, so she will measure the right proportion of ingredients. I don’t have to monitor the process.

For my sister and I to make apple pie together, we don’t need to say anything more than “You prepare the filling and I’ll do the crust,” especially if we’ve done this task before together. In the rare instances where we need to exchange words, it’s on the salient differences, like “Are you feeling nutmeg today?” Or “How sweet should this pie be?”

Trust is the lubricant against the friction of human collaboration.

Nothing could happen quickly and efficiently in this world without some levels of trust. Everything would quickly spiral into constant surveillance and the discussion of minutiae.

Trust is contextual

Recall my proposed definition of trust — “This person will fulfill my hopes for his/her behavior in this specific context.”

This specific context is incredibly important to call out. I might say to my roommate, “Why don’t you order our dinners for the next week? I trust you,” and what I am specifically saying is “I believe you to be responsible enough to remember to put in a daily dinner order, and I believe that what you choose will be acceptable to me.”

I am NOT saying that I now trust my roommate to: a) drive my car b) complete my coding task c) keep my secrets, d) … a million other things.

Not trusting him to drive my car or complete my coding task doesn’t mean I don’t like my roommate, or that I don’t respect him. Trusting someone in some specific context can be completely orthogonal to my like or admiration for them.

This may seem obvious in my example above, but it’s nuanced in the day-to-day.

For example, I have enormous respect and like for my colleagues on Team X. Given what I know about them, I believe they will make better decisions than me in many contexts. I believe they will make worse decisions than me in some contexts. I suspect they feel the same way about me.

In fact, everyone should feel the same about me. For example if I popped into a production support channel and said “Data pipeline issue can be solved with this PR, please review,” you should be skeptical and monitor my work very, very closely. You should not think to yourself, “Because I trust Julie to write a blog post, I’ll automatically trust her to fix our data pipeline issues.”

Same goes for you. If you earn my trust in being an expert on brand and color, it does not mean you’ve earned my trust in front-end implementation, or even in a different design domain like onboarding usability. Even if you trust in your own skills, I might not — we all have blind spots after all.

For example, I thought I was a pretty capable and experienced manager when I started Sundial, and I’m sure many folks trusted me in that capacity, but it turns out I was only decent in the context of being an exec at a particular, in-person, large tech company. I was actually terrible within this new context of a start-up that is remote and cross-cultural!

Luckily, realizing I was terrible was the first step to getting better.

That is why it’s our job to hold up mirrors for one another — feedback helps us see ourselves more clearly.

The 3 ingredients for trust

For me to trust you to make a decision or take an action, I will have to check 3 boxes in my head:

1. You have the intent — we should be aligned on the outcome we want. In our cooking example, I have to believe that you care about making a delicious apple pie.

2. You have the skill to do the task — the thing I am asking you to do is something you are capable of doing well. With apple pie, these skills include: measuring ingredients, peeling and coring apples, operating an open. Another way to think of skill, especially in high-ambiguity areas like product sense or systems thinking, is “How high-quality is your decision model?”

3. You have the necessary context — you have all the crucial information to do the job well. In our apple pie example, knowing what apple pie is, where we should get the ingredients, how much to make, how sweet it should be, to whom or what occasion it should be served for, etc.

If I want the best pie of my life, I won’t ask my husband — while he’s perfectly capable and knowledgable about apple pies, he doesn’t particularly care for baking; I won’t ask my 5-year-old — while he loves apple pies and is eager to help in the kitchen, he can’t operate an oven; and I won’t ask my mother, because while she’s happy to help and skilled at baking Chinese goodies, she’s not familiar with western desserts.

I find this breakdown useful because “I don’t trust you to do X” should not automatically translate to: “I think you are immoral or unintelligent” (although that is what many of us on the receiving end might instinctively feel.)

I may not trust you to do X because I suspect how you see success and how I see success differ. This is so typical in a workplace setting because we are different people, perhaps working on different teams with different goals.

My primary goal as a designer might be “ship an excellent user experience”; your primary goal as an engineer might be to “ship quickly and with high performance and very few bugs.” This does not mean either of us are bad people! In fact, we can probably agree that both of these aspirations are noble and good; the nuance comes from exactly how we trade things off.

I may also not trust you to do X because you don’t have the context. Let’s say you are an excellent sales person, way more charismatic and persuasive than me, and we need to try and close a sale. However, I am the person who knows the most about this particular customer — their problem space, the way they think, our past conversations with them. Who should handle the sales conversation? You have the upper hand in skill, but I have more context. Again, this is not a judgement on your talents or worth as an individual!

Breaking down trust into its 3 components — intent, skill, and context — allows us to have a deeper conversation about exactly why we do or don’t trust each other on some specific task.

Shared intent matters tremendously

Of the 3 ingredients for building trust — shared intent, the right skills, and the necessary context — shared intent is the most important to explicitly align on.

When I trust your intent, I can come up with many generous interpretations to the inevitable bumps or mistakes that will pop up. When I am wary of your intent, I will feel the need to scrutinize your every decision, even if they seem good on the surface.

Usually when people say “I trust you” this is a shorthand for saying “I trust you care about me and have my best interests at heart.” It’s enormously connective to know that we matter to others!

In a company setting, shared intent should be a given. After all, we both want our company to succeed.

Alas, the challenge lies in how narrowly we define out intent. For example, because we both work at Company X, I of course care deeply about X succeeding, same as you. But as a front-end engineer, I might also care deeply about producing high-quality sustainable front-end code. Meanwhile, you, as customer success manager, may care deeply about responding to a client ask quickly. We may clash over these misaligned intents — speed to new feature, or sustainable code?

We may start feeling suspicious that the other party does not care as much as we do about our precious intent! Imagine that arguments of the variety of “new feature vs. sustainable code” flares up every two weeks or so. After a few months, worn out by the constant clashing, we may start to develop an “us vs. them” mentality. We may feel a growing urgency that we are Right in our intent, and that that they are WRONG!

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What do you feel when you hear the word judgement?

Is it a hit of cortisol—Oh shit, I hope you’re not judging me.

Is it resigned—I wish we’d learn to accept rather than judge.

Or is it a surge of pride—Yeah, I know exactly how to separate the wheat from the chaff.

The notion of judgement is a wonderful swirl of contradictions. In today’s issue, let us explore its necessity and cultivation.

Warmly,

~Julie

In this issue:

1. One skill to rule them all

2. An equation for judgement

For paid subscribers:

4. How to judge who has good judgement

5. Improving your decision model

One skill to rule them all

If I ask a room of people, “Do you want to grow your career?” The answer will be “F— yeah I do.”

If I ask the room, “What do you think you need to do that?” the answers will be a cooking pot of skills: Learn Python! Improve my communication! Get better at systems thinking! Access my creativity! Get rizz! The list goes on and on.

These lists can be helpful, but they’re also scattered, endless, and occasionally too specific. Let’s try a simpler approach:

The way to grow your career is simple: get better at making good decisions.

Pretty non-controversial, right? Making better decisions = greater chance of success in whatever you’re trying to do.

What does it take to make better decisions? This skill is judgement.

Judgement is the ability to transmute information into actions that achieve the desired outcome.

So, if your goal is growth, try to see the predominant skill you are focused on as honing your judgement.

Let’s explore how we do that.

An equation for judgement

What makes up excellent judgement? Here is my take:

Quality of decision model

Whenever any of us has a strong feeling about something, it will be based on a framework or algorithm we have in our brains. I call this the “decision model.” Our decision model typically lives in the subconscious, but if we are particularly aware, we manage to pull parts of it into our consciousness to be described or analyzed.

For example, if you are a skilled engineer and I give you working code samples from two new grads and ask, “Which candidate would you hire based on their code?” you will probably have a gut feeling that one code sample is “better” than the other.

If I asked you, “Why?” and the difference is really obvious, you’ll be able to explain your framework to me — “Candidate A put all their code in one function, while Candidate B created simpler, reusable functions which will scale better, and is easier to read and debug.” You are giving me a glimpse of your decision model, which is that Breaking code into functions → demonstrates proficiency in scaling / debugging → more skilled engineer.

Of course, the framework above is coarse and not terribly controversial. Any engineer who has taken an intro computer science class would agree. But let’s say now that the two samples are not that different. They both use functions, and they both work. Does that mean they are equally good?

That n00b engineer fresh off her intro CS class might say, “They both seem fine to me!”

However, a more skilled engineer will be able to spot minor differences that makes her believe one code sample is better than the other — everything from variable naming, to granularity of functions, to whether recursion or a ‘while’ loop was used, to specificity of variable typing, to how errors are handled.

In other words, the skilled engineer has a more complex and nuanced decision model. Her framework of “quality code” takes into account more signals than a lesser engineer. In fact, a master-level engineer (let’s call her Unicorn Engineer) operates similarly to an advanced LLM — as her eyes scan the code, she is processing thousands of such subtle signals, much of it subconsciously. It would be impossible for her to explain her entire decision model because it’s just so complex.

She might chalk it up to “intuition,” while others gape at her, amazed at her prescience and track record. It feels like magic, but it is not magic. It’s simply that the number of parameters she subconsciously considers, as well as the weights she assigns to each parameter, gets closer and closer to being a true predictor of a great engineer.

The compliment we can give to Unicorn Engineer is that her decision model for assessing code is high quality.

Richness of Data

Having a high quality decision model is awesome, but alas it isn’t sufficient. You also need to have enough relevant data to feed into the model.

Let’s go back to our example of Unicorn Engineer, whose decision-model can pick up thousands of subtle signals in assessing code.

What if the code samples we give her are 50 lines long? Clearly her capability to accurately predict the better engineer will be way worse than if we handed her thousands of lines of code!

Not to mention, any engineer worthy of Unicorn status will surely balk at this test in the first place. All Unicorn engineers know, in their Yoda-like ways, that writing quality code does not a good engineer make. How quickly can the candidate think on their feet? How easy is the candidate to collaborate with? How proactive will the candidate be in solving problems? These signals cannot be found in code alone!

So even if one’s decision model is incredibly well-honed, the amount of known context matters tremendously.

Most engineers will make better hiring decisions after seeing a candidate in action for 3 months (internship) versus 3 hours (interview). Most PMs will make better prioritization decisions if they look at the past 6 months of customer requests rather than just last week’s requests. Most designers will design a better user experience after taking to 100 customers versus 10 customers.

Clarity of Mind

The last piece of good judgement is having a clear mind. Our Unicorn Engineer may be brilliant, she may have the deepest wellspring of intuition the world has ever seen, she may have done all her homework in gathering context—but if she is seething mad, I promise she will make poor judgement calls.

It is impossible to make use of an excellent decision model or a ton of rich data if you are not in the right mental state.

Fear, stress, anger, sadness, jealousy — these all cloud our ability to make use of our gifts to the greatest degree.

Let’s take a simple example — “Be kind.” I bet you have a pretty honed decision model around what “being kind” looks like, and you’re resolved to be kind to people you like. And yet, have you ever yelled at a friend or family member? (If you never have, I salute you, please share your wisdom.)

We don’t mean to yell, but we do because we feel overwhelmed. We’ve lost mental clarity.

Mental clarity is just as important to judgement as any of the other components. If you find yourself struggling to see clearly, you should doubt the quality of your judgement and turn your attention instead to regaining some of that lost clarity.

There are two more chapters in this issue for paid subscribers:

1. How to judge who has good judgement

2. Improving your decision model

Enjoy what you are reading? Have strong opinions and wanna let me know them? Support The Looking Glass by becoming a paid subscriber!

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