The first sign I read said, THATAWAY.

My wife and I were walking into the visitor center at Art Omi, a sculpture and architecture park in upstate New York, when I stopped in front of it. The signpost had a garden-gnome-head-shaped bell hanging from the other side with a long rope inviting you to ring the bell.

On the floor beside it was another sign written in bright red that read, ALERT! PLEASE READ OTHER SIDE. I dutifully followed the directions and meandered around to the other side only to see it say, THISAWAY.

I felt like the artist had gotten one over on me. Between the humor of the gnome bell and the lack of specificity of the directions, I chuckled at myself out loud. Beside the sculpture was a plaque:

I stood there longer than the sign deserved, re-reading: A crack in our certainties. I thought about how I’ve been walking around signs my whole career, checking the back side, wondering if there’s something clearer on the other side.

I looked for signs everywhere. Curious what a law career might open up, I took the LSAT but never applied. I was always fascinated with public policy and followed the signs to a career at the Federal Reserve, only to realize it wasn’t the right direction. I tried many other routes, marketing, real estate, banking, each one taking me somewhere I hadn't planned to go.

Then, for once, when I wasn’t looking for any signs, I found myself throwing parties on Thursday nights. I was a pressed collar shirt Federal Reserve analyst by day, a NYC party promoter at night. When the doors opened and the crowd started dancing, I felt alive with pride for having been the host that curated the experience. It felt like more than just a release valve away from the spreadsheets.

I didn't know it then, but I was auditioning for a job that didn't exist yet. The host, the salesman, the guy comfortable working a room was someone the Fed had never asked for. When the chance came to leave and sell gold to central banks around the world, I already knew I could do it. I'd been doing it every Thursday. I just hadn't called it that. Now I do it in a classroom.

For a long time I worried my meandering career was a reflection of a lack of discipline or foresight. That the people who moved faster than me just got things quicker. But the gnomes had it right.

The certainty I kept looking for on the far side of the sign was never written there. It isn’t written anywhere. The question is what moves you in any direction. The answer just tells you where the next crack will open.

It’s a strange kind of freedom, realizing every answer only opens another question. But that’s the point the artist was making all along: you don’t need to know which way is right before you start. Thisaway, thataway— you find out by going.

Eleven years ago, I made a careful pro/con list to decide between returning to my previous desk at the Fed or to take a leap to NYU. On paper, the Fed won. But I chose NYU and I haven’t looked back since.

My solution didn’t come from my pro/con list, but rather from something I caught myself saying out loud.

We like to believe our decisions are rational, that if we just list the pros and cons, the “right” answer will reveal itself. But in reality, your most important decisions aren’t made by logic alone. They’re shaped by what you value, and even more importantly, what future you’re ready to create.

The Illusion of Rational Decisions

Cost-benefit lists don’t work.

They give you a false sense of certainty and control that doesn’t exist. The problem is that when you write a pro/con list, every item is treated equally. “Good boss” sits next to “long commute” as if they carry the same weight. The result is that you can end up choosing a path that looks better on paper but feels wrong in reality, and you won’t know why until you’re already on it.

The trap of a pro/con list is that in trying to be careful in capturing all the factors, we forgot instead to consider the weight of what matters most. In math we may think of this as a coefficient in an equation. Each variable is not equal in weight, so stop looking at them as if they are. And some variables are too difficult to categorize at all.

In 2015, my list said the Fed was the obvious choice. I wrote that it was intellectually stimulating, provided a strong career progression, and had a boss I respected. (To my Fed friends, I still think foundly on my time there!). Furthermore, on my NYU “cons” list I reinforced that I was “Not done with central bank career.”

The pro/con list was capturing my fear of changing careers, my inertia actually lived on both sides of the ledger! The problem was that the list couldn’t help me see what I actually valued in the moment.

The Missing Variable - Value Weighting

AI tools like ChatGPT or Claude will often give you the wrong answer to big decisions for the same reason your pro/con list does. They optimize based on surface-level inputs, not your internal value system. They don’t know what you prioritize unless you explicitly define it. Yes, they have some memory, but they aren’t capturing your motivations, desires, and psychological needs. If you outsource your thinking without clarifying your values, you risk making decisions that feel coherent but that are uninspired and not aligned with your goals.

When we look around at others that seem to make decisions easier, it’s easier to think they are just risk takers. That’s what many people believe about entrepreneurs, that they love risk. But the reality is very different. They just value what they are pursuing more. And that can range from seeking autonomy, to building a big idea, to leading a team. Arthur Brooks has been talking about this recently, and would probably say they are using their right hemisphere of their brain and tapping into excitement alongside of fear.

So what are we suppose to do? Before evaluating options on a tally sheet, define what is more important to you right now: stability or growth? mastery or exploration? past identity or future potential? Better analysis from AI tools won’t “solve” what we haven’t clarified and thought through ourselves. Actually the risk is that it accelerates our analysis paralysis loop, leaving us even more confused.

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Emerging Identity - The Real Driver

The word decide comes from the latin word decidere, which means “to cut off” or “to kill” an alternative. I learned about this surprising etymology history when I read Oliver Burkeman’s incredible book 4,000 Weeks. It’s shocking because killing off alternatives is exactly why it’s so hard to make a decision. We don’t want kill off our options.

But what I’ve found, whether it’s for yourself or for an organization, deciding when uncertainty is extremely high, is much more about revealing who you want to become.

The choice that wins isn’t the one with the most pros. It’s the one that aligns with the identity you’re ready to step into. If you ignore that signal, you stay stuck optimizing a life you’ve already outgrown. For a business, you become stuck in your past success, ready to be disrupted by the next new competitor.

Instead of asking “Which option is better?”, ask: “Which future am I ready to enter?” What pulled me to NYU wasn’t logic, it was observing my own language at the time. I wrote that it would be “exciting and new,” that I’d be “on the progressive edge,” working with students, professors, and businesses. I wanted authorship, responsibility, and a different kind of impact. And most of all I remember telling then NYU Stern Dean Geeta Menon,

“I want to be the person that takes this job.”

After you observe yourself saying something like that, you can’t turn back. At that moment I didn’t realize it but I had made a decision to end one career path and enter another, I stopped weighing options and chose a future.

Over the past several months I’ve been talking with senior leaders across a wide set of organizations: big tech, financial services, health care, education, and consumer tech. Across the board, AI is front and center of their concerns and specifically considering ways to enable their organizations to reap its benefits.

Some emphasized the challenge of raising awareness on their teams, others stressed the importance of quieting fears of AI replacing jobs. Many stressed how they felt like their organizations were moving too slowly to make meaningful transformations, saying, “we’re still getting started.”

Whether it’s customers, investors, or CEOs that are calling for AI adoption, what I heard is a chorus of significant pressure to make their companies the leaders in their industry in what’s to come in AI. There’s a sense that within each category, only a few organizations will emerge as winners in the adoption of AI. Thus while there is a strong sense of opportunity, it’s eclipsed by a fear of missing the moment.

The Logic of AI Is Being Decided Illogically

The reason there is such eagerness to adopt AI is the underlying belief that AI will help systemize work, lead to rapid, intelligent decision making that will automate workflows in ways that can unlock a new level of efficiency. This belief is fueled by early success stories of software engineers increasing their productivity 10x or radiologists improving their accuracy of reading a scan, saving hundreds more lives each year.

The irony is that the decision to adopt these tools and the process of onboarding them are not being led by cold hard logic, but by feelings of anticipated regret.

Some worry that what we are witnessing are “animal spirits,” the emotionally driven behavior that typically involves chasing returns that can lead to misallocated resources and market bubbles. But within many companies today the feeling driving AI adoption is a prudent bet on the future of the business. Both perspectives are probably right.

Data Isn’t Always the Answer

When making consequential business decisions we all prefer cold hard facts. The reality is most decisions are made in the absence of said facts. Sometimes that’s because decisions are made impulsively, reflexively, or on a whim. If not with rigorous analysis, most business decisions are at least made with strong intuition, general principles, or relying on gut instincts.

Researchers Lerner, Hunt, and Dimov wrote a fantastic paper that begins with the reality of the world that entrepreneurs use both calculated rationality and impulsive-driven logic, which can lead to good or bad decisions. As they map the space of how decisions are made they include an area that we want to avoid — where the primacy of affect is hot. Or in simpler terms where you’re being impulsive, emotional, or even reactive. Explaining to your board that you adopted AI because “it felt right” is not going to go over well.

They map on another side “logic of consequences” and “economic judgment” — these rationales are likely to play heavily in your memo to upper management. “We are pursuing AI because it’s a path forward to higher revenue and the consequences of missing out could be significant to our competitive positioning.” Both ends of these spectrums are well understood: one to avoid, and one as the gold standard for decision making.

When Analysis Stops Working

Most consequential decisions are situated in a problem defined by high degrees of uncertainty. This goes beyond being a risky situation of how much should we price something — to what should the future of business look like. This is not uncertainty that can be modeled; it’s a future that can’t be predicted. It’s unknowable.

When faced with a high degree of uncertainty, many managers — or even husbands, mothers, fathers, friends — get stuck. The term we use is “Analysis Paralysis.” We’ve weighed the consequences, we’ve considered the economic benefits, but there is no clear direction. Should we buy the house? Should we make the investment? And even, should we get married? This is the trap the best leaders learn to escape, not by getting more data, but by deciding differently.

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From “What Should I Do” to “What Could I Do”

One way to move forward with your decision making is to move from asking “What should I do?” to “What could I do?” We’ve spent so much of our lives focused on gathering data and evidence to validate or justify action. Whether consciously or not, we’ve learned to think that moving away from this type of process could be a retreat from logic toward the danger zone of emotion, reactiveness, and impulsivity.

What we’re forgetting is that there are many ways to make decisions that are equally logical and effective. My research with my colleague Natalia Levina on entrepreneurship revealed that most business frameworks are rooted in a conventional scientific management approach — the sort of cost/benefit analysis anchored in data collection. Yet as we move forward with imagining and creating a future that doesn’t exist, adopting methods that rely on different logics of intuition, pragmatism, and humanism may be more effective.

From my conversations with leaders, what became clear to me is that what’s leading today’s AI adoption is exactly an entrepreneurial instinct of “What could I do with what I already have?” Yes, companies are evaluating the top ways they can benefit in their organization, trying to reimagine their businesses to get the most optimal use out of AI. But often the first beta test or adoption looks more like an answer to “what could I do” — the project that most closely ties to where resources are already best situated to adopt AI.

This Has Happened Before

We are in the early days of adoption, so too early for leaders to share their notes. But my experience with business process outsourcing (BPO) in the commercial banking sector feels very familiar to what we are experiencing today. In the 1990s and early 2000s Business Process Outsourcing (BPO) became a popular industry practice to shift workflows to lower cost operators in another location. Many people associate this with Indian and Philippine run call centers but the practice extended into a wide variety of business use cases and destinations.

In our case we were moving mortgage underwriting operations to India. What our organization, GreenPoint Mortgage, did at that time was to start with what we could do. We didn’t begin with outsourcing the credit and home price evaluations, we started with simple secondary pricing of securities. It was math that was done in California at high costs that moved to India at a low cost. The results were outstanding and allowed for internal and external stakeholders to gain comfort with the people, the process, and the concept. Only as that model was proved did we move to higher value-add use cases.

The lesson wasn’t specific to mortgages or outsourcing. Starting with what you could do, with existing resources, in low-stakes terrain, is how organizations build the confidence to take on the harder changes. Only by starting there did we reduce uncertainty, build buy-in, and learn that moving before we had all the data wasn’t reckless.

But starting small is not the destination. It is how you overcome inertia. The risk, as I explored in a companion piece, is that organizations get comfortable under the streetlight, optimizing what is easy to measure and calling it transformation. The real work begins once you are moving, when you have to direct that momentum toward the questions that actually matter, not just the ones AI can answer fastest.

AI is taking your job, it’s becoming your boyfriend, and it will take over the world. At least that’s the narrative following every new model release, and lately they’ve been coming fast. Each leap forward on benchmark tests becomes fresh evidence that AI is changing everything, in every way, all at once.

Two Princeton Researchers disagree and think “AI is a Normal Technology” and even wrote a book entitled, “AI Snake Oil.” Researchers, Arvind Narayanan and Sayash Kapoor, argue that claims about how AI will immediately change everything are overly inflated and inaccurate. Specifically, they argue that much of the public discussion about AI is confusing two different stages of technological change: capability versus diffusion and adoption.

Why Benchmarks Tell Us Less Than We Think

Narayanan and Kapoor don’t disagree with the increasing capability of AI, but they point out that much of the testing happens only in controlled environments. The real impact depends on application, adoption, and ultimately diffusion throughout organizations and society. Benchmarks capture the first of these stages well as they tell us something about capability. What they tell us far less about is whether organizations are meaningfully changing how work gets done. And whether you’ll have your job on Monday.

New technologies rarely transform the world the moment they become possible. They transform the world, only once institutions, workflows, incentives, and human habits reorganize around them. This is where Narayanan and Kapoor’s argument is interesting as they are effectively arguing that our obsession with capacity is a lot like a drunk person looking for their keys under the streetlight.

The Streetlight Problem

The streetlight problem is part joke part business fable. The story goes that a drunk person drops their keys at night on a sidewalk. He begins searching for the lost keys under a streetlight, not because that is where the keys were dropped, but because that is where the light is.

In organizations, the streetlight is measurement. Organizations gravitate toward what can be easily quantified and optimized. Benchmarking capacity gives us easy ways to see visible progress, so they become the focal point of the conversation. But what is easiest to measure is rarely what matters most. Benchmarks can show that a model writes slightly better code or scores higher on a reasoning test. They don’t tell us whether companies are reorganizing how software is built. They can indicate improvements in language understanding. They cannot reveal whether entire professions are restructuring how expertise is used.

The research organization, Gartner recently published a report looking at adoption of emerging technologies and find a major gap between experimentation and true adoption. In their January report they wrote:

This problem speaks to the AI Hype cycle as it forces us to ask ourselves, what’s being measured? Are we looking only under the streetlight?

How Lean Startup Became the Streetlight

The streetlight problem didn’t arrive from nowhere. It was built into the dominant framework organizations use for experimentation itself. Some organizations code this behavior as piloting or validating, but the underlying approach is unmistakably lean startup. It’s the most popular entrepreneurial method and the primary operating system of most incubators and accelerators. But its increasingly acknowledged bug is tunnel vision or what some call the streetlight problem.

Lean is a powerful tool. Instead of writing long business plans that don’t materialize, the idea is to run small experiments, gather real feedback, and iterate your way to a solution. The logic is defined by an emphasis on being low cost, easy to follow, and works in many contexts. But when used as the only tool, it leads to confirming what you already believe instead of discovering what you don’t know.

The problem is not that organizations fail to experiment. It’s that they experiment inside the logic of optimization, and end up learning only how to make small things slightly better. This matters enormously in the AI context because AI is, at its core, an optimization machine. It is exceptional at running exactly the kinds of experiments lean was designed for, iterating on known variables, improving measurable outputs, and finding marginal gains within a defined space. If your organization’s experimental logic is already oriented toward confirmation and optimization, AI will accelerate that logic ruthlessly.

You will get faster at looking under the streetlight.

AI Can’t Tell You Which Questions Are Worth Asking

It cannot tell you which market shift actually matters for your business. It cannot identify the opportunity that doesn’t yet have a name, or the problem worth solving that hasn’t shown up in any dataset yet. It will not invent the next big thing. Those ideas and judgments require something different than processing power. They require a willingness to move toward uncertainty before the answer is visible.

The organizations most likely to capture real value from AI are the ones that direct the technology toward their most important problems — not their most measurable ones.

For organizations that will be part of the true AI adopters, moving past the snake oil, they will need to design experiments that can actually fail. They may need to look at their customers’ problems from angles their competitors haven’t dared yet. And they may have to linger in uncertainty to allow their boldest ideas the room to be explored fully.

All of this requires a human being willing to ask good questions before the data exists, and to get organizational buy-in to test it with real action. The base case for AI might be that it becomes a “normal technology.” It may never achieve the hype if organizations keep looking for the future under the streetlight, optimizing answers to questions that no longer matter, and calling it innovation.

Last month, Anthropic released Claude Opus 4.6, an advanced AI model that many developers are calling one of the most capable to date. Early tests suggest it reasons more deeply, sustains long and complex workflows, and excels at coding, planning, and tasks that once required entire teams. If these accounts hold up, the technical cost of building something new has dropped yet again.

But even the most powerful model cannot remove the fear of falling flat on your face.

Artificial intelligence is steadily lowering the technical barriers to starting something new. What it has not lowered is the human cost of being wrong in public.

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A Student’s Real Calculation

I was reminded of that tension last week while speaking with a graduating student who is building an AI-driven robotics startup aimed at reducing technology waste. If his idea works, it could put a real dent in the environmental damage caused by discarded electronics. Like most early ventures, the project still has many loose ends and untested assumptions. Yet the progress he has made is striking. At twenty-one, he has built a working prototype, launched a website, and conducted hundreds of conversations with users and industry experts. The technological progress he has achieved at this stage is something that would have been difficult, if not impossible, even a decade ago.

Because of that progress, I suggested it might be time to begin sharing what he was working on with a broader audience. If the idea is going to grow, he will eventually need collaborators, experts, and funding. Those things rarely appear without visibility. At first he brushed the suggestion aside. I know him well enough to press again, and when I did, he shifted in his seat and his expression changed. After a moment he said something that captured the hesitation many people feel but rarely say aloud:

His comment hit hard because it named the real risk many aspiring founders are calculating. Even people decades into their careers hesitate before making unfinished work visible. The early risks of entrepreneurship are rarely financial. Before capital is at stake, what entrepreneurs risk is their reputation. The real calculation becomes how much embarrassment one is willing to tolerate in order to explore an idea that may or may not work.

Fear of failure itself is not new, but the arena in which that fear plays out has changed.

Becoming a Founder Feels Like Putting on a Costume

Part of the reason is that starting a venture no longer feels like experimenting with an idea. It feels like announcing a new identity. Becoming a founder today can resemble putting on a costume and stepping onto a stage. Looking at how founders are portrayed, how they speak, and how they are celebrated can make more than just college students wonder whether they fit the bill. It is hard enough to grow into the identities of parent, partner, or professional. Imagining oneself as a tech founder while also worrying about a mortgage or a family can make the role feel strangely theatrical.

Entrepreneurs are increasingly treated like cultural icons, and their stage is our screens. Our feeds are flooded with side-hustle hacks, founder manifestos, and triumphant posts announcing new funding rounds. Founder-led marketing tells a heroic story of grit overcoming mediocrity, a narrative that often leaves little room for the uncertain, awkward beginnings that most ventures actually experience. The message that quietly emerges is that entrepreneurship belongs to the bold, the brash, and the already convinced.

The Real Barrier to Starting

Yet interest in entrepreneurship has never been higher. Millions of Americans say they want to start a business, but fewer than half take even the simplest first step. The practical barriers—forming a company, building a website, launching a prototype—are lower than they have ever been. A decade ago, building a credible product required a team. Today one person with AI tools can often do it in days.

The technological barriers to building have collapsed. The human barrier has not.

Different Ways of Acting Under Uncertainty

That tension becomes clearer when you look at how entrepreneurship is taught. While studying entrepreneurship programs at several highly selective universities, I expected to find agreement on how entrepreneurs should proceed when ideas are uncertain. Instead I found something more interesting. The tools were often similar, but the underlying philosophies were not. Some approaches emphasized prediction and careful analysis. Others emphasized experimentation. Others emphasized what scholars call effectuation—starting with what you have and shaping the future through commitments with others.

In other words, entrepreneurship is not governed by a single logic. Different approaches reflect different ways of reasoning under uncertainty.

What entrepreneurs learn, often painfully, is that uncertainty does not disappear before action. Action is how uncertainty begins to resolve.

Artificial intelligence may be lowering the cost of building to nearly zero. But it has not lowered the cost of acting before certainty arrives.

In the race to predict the future of AI, most of us are asking the wrong question.

Salesforce’s earnings release yesterday (February 25) offers a useful example. Despite beating expectations, the market response was slightly negative. On the investor call, Marc Benioff, founder and CEO of Salesforce, said, “You know, this is not our first SaaS apocalypse,” acknowledging the growing concern that AI agents and the falling cost of software development could undermine the traditional Software-as-a-Service model. Salesforce isn’t alone as all big name software stocks have been sharply underperforming this year. For Salesforce specifically, the fear is that the revenue it earns from licensing software to individual users could decline sharply if AI reduces the number of human “seats” needed inside organizations.

But that framing misses the deeper strategy at play. Salesforce’s long-term success has less to do with building the best standalone software and more to do with positioning itself as the best collaborator in an evolving ecosystem. We tend to romanticize companies that appear visionary: OpenAI for putting AI in a chat window or Apple for inventing the iPhone. We assume that technology winners are those that make bold, singular predictions on the future. Salesforce is not trying to predict how AI will unfold. That is precisely why it has a chance to win. It isn’t trying to be prophetic. It’s behaving entrepreneurially.

SalesForce Isn’t Betting on an AI Winner

While investors are evaluating software stocks through the lens of “who wins AI,” they may be missing Salesforce’s structural advantage: it doesn’t need to pick a winner. On the investor call, Benioff was unusually direct about the uncertainty of the moment. He acknowledged that the models we rely on today will change, and that Salesforce’s relationship to them will continue to evolve. “Could those models themselves become platforms? Could OpenAI then also be a platform? Could Anthropic be a platform? Can Gemini be a platform?” The subtext of this point is that the future of AI is still unclear.

Instead of pretending otherwise, he shifted the focus. The value Salesforce creates is not in predicting which model dominates. It is in sitting one layer above that volatility. As he put it, “our job as a software company is to help our customers create success… So we’ll deliver our products, our capabilities, our value proposition through our customer relationships.” That line is easy to throw away as sales talk, but it is the strategy. The advantage is not the software alone. but the service wrapped around it, the integration into workflows, and the long-standing relationships that allow Salesforce to embed whatever models win into real enterprise work.

Building with Customers

Last year, I had the chance to sit with Pallavi Sebastian, now SVP of Talent and Learning at Salesforce. What stood out in our conversation was her emphasis on co-creation. She didn’t describe innovation as something developed in isolation and revealed to customers at Dreamforce, their annual conference in San Francisco. She described it as something built alongside and with customers. Salesforce, she said, stays entrepreneurial by leveraging the trust it has built over decades and by “bringing customers in early to innovate with us… it’s critical to making sure we’re innovating in a way that’s relevant and resonates with our customers, and they can provide us feedback on the areas we may not have thought about.” I think this idea stands out because so often, whether you’re a solo entrepreneur, or an intrapreneur it can feel like you need to own all of the creativity and innovation. Yet, the secret to getting it right is often co-creation.

Benioff echoed that logic on yesterday’s earnings call. He described their partnership with SharkNinja, where they co-created a guided shopping agent in just eight weeks, right before the holiday season. They deployed their solution into real workflows under real commercial pressure, when their customer needed it most. The CIO of SharkNinja later explained that what made it powerful was not just the AI layer, but how it connected back into the history of their customer data that they trust Salesforce to manage. As Benioff put it on the call,

“The token (AI compute) on its own doesn’t know your customers, your pipeline, your org chart, but Salesforce does. The value isn’t in the token. The value is what our platform does with it—the work.”

What Benioff outlines in this comment is something more consistent and deliberate that just sales talk. It feels like a strategy focused on gaining advantage not by predicting the future, but by leveraging an earned asset, customer trust, and using that as a resource to build and co-create from.

No one will predict the pathway of AI correctly. That’s precisely why behaving entrepreneurially—leveraging the resources you already control and co-creating with those you trust is such a powerful strategy. For companies like Salesforce, this moment is not a crisis of prediction. It is a masterclass in building a future you can’t yet see.

The first is mostly imagined. The second is deeply human.

Creativity requires exposure. And exposure invites critique. Learning to separate feedback on the work from feedback on yourself is one of the most important entrepreneurial skills.

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If anyone was looking for a recipe for raising our anxiety level, just talk to Matt Shumer, because he found it yesterday.

He posted a reflection on twitter that was titled, “Something Big Is Happening.” He began with a society already uneasy about AI. Then he added our still-healing memory of Covid.

The delivery was a simple analogy. Shumer compared:

February 2026 to February 2020.

Or in other words T-1 month, only 30 days before everything changes.

Shumer wrote:

“I think we’re in the ‘this seems overblown’ phase of something much, much bigger than Covid.” He described watching AI go from “helpful tool” to “does my job better than I do.” He even said, “I am no longer needed for the actual technical work of my job.”

What followed was a flurry of commentary in the news media, on X, and on Linkedin. Many in agreement and plenty of anxiety and fear to go around.

Why did this story resonate so much?

I think it deeply resonated as we all remember the skepticism we had in February of 2020. We went about our business as usual, and then came the stark contrast of March: schools closed, friendships moved to Zoom, celebrations canceled, hospitalizations rising, jobs cut, lives altered.

So when someone says, “This is happening right now,” and warns that AI may eliminate large swaths of cognitive work, it’s not surprising that many people feel their back tighten. I felt it too. My mind started racing toward catastrophic outcomes.

In late February of 2020, I did the same thing. I projected terrible doomsday scenarios. In a panic, I stocked up on way too many black beans and tomato sauce. Took my kids out of school days before my friends and doom scrolled. The worst scenarios I imagined never materialized for me. But other challenges emerged that I could never have predicted.

Yet, ​the future rarely collapses in one dramatic sweep. It shifts in increments. In March 2020, my instinct to minimize risk amplified every catastrophic possibility until I felt paralyzed. The people who stay in motion get to shape the change. The ones who freeze, experience it.

I see this same emotional bundling every time I talk to a would-be founder that says entrepreneurship feels “too risky.”

Unbundling Risk: It’s Not Service Engine Light

In coaching students and early founders, I spend a lot of time separating out the different risks people experience. When someone considers starting a company, they often say, “It’s too risky.” But that risk is rarely singular.

They worry about the job they would leave, the money and time already invested, the embarrassment of failing, the reputation they’ve built.

With AI, many of those risks parallel quite closely. We tend to lump these together into one undifferentiated feeling of dread. When everything blends together, it feels larger and more dangerous than it actually is.

What if the hardest part isn’t financial risk, but identity risk, the feeling that the thing you worked so hard to become might no longer be scarce?

The alternative to dread is not reckless reinvention. It’s disciplined motion. Stay curious long enough to notice what is actually changing. Study the problem before racing toward a solution. Use AI at work and at play, not as a surrender, but as a tool to understand the terrain. The better you understand its evolving capabilities, the less there is to fear and the more agency you regain.

I doubt we’re in February 2020. But we aren’t standing still either. The future rarely announces itself all at once. It shifts in increments. So will I.

What Should You Do With an Idea? Apparently, for most people, the answer is nothing.

A large, multi-year U.S. study from 2019 found that while millions of Americans consider starting a business, fewer than half ever take even the simplest first step—like doing a basic online search or talking to someone about the idea.

So what are we actually doing with our ideas? Not very much.

The image above references a children’s book that captures this perfectly. It tells the story of a boy who encounters an idea, represented as a fragile egg. Unsure what to do with it, the boy simply walks away. The more interesting question isn’t why people have ideas. It’s why so many of us walk away from them and the sense of generativity that makes us feel alive.

After years of working with students, founders, and executives, I’ve come to see the answer isn’t fear or laziness.

It’s something more powerful: an inherited logic about action.

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How We Inherit a Logic About Action

We are taught, over time, to delay action until we feel ready, qualified, or certain. Early on, this shows up when we ask for permission. First from parents and teachers, later from institutions and credentials. Over time, we stop needing someone to say no, our identity (Quant, Creative, Operator) does it for us. By the time we reach college or get an MBA, this becomes formalized: action should wait until tradeoffs are calculated and risks minimized.

At first, this logic works because it rewards consistency. Others can see your path because you’re clearly on one. And when you get tempted to step outside of it, you don’t, because you can anticipate what you might lose.

But this logic breaks down when the question isn’t optimization, but direction and meaning.

In the children’s book, the boy admits, “I worried what others would think. What would people say?” That’s the moment most ideas stall, not because they’re bad, but because acting on them would mean stepping into uncertainty without guarantees.

Rebuilding ourselves doesn’t begin with feigned confidence or more clarity. It begins with action. An idea doesn’t need confidence to survive—it needs contact.

The boy in the story notices something simple: he feels better when the idea is around. So instead of walking away, he starts paying attention to it. He feeds it. Plays with it. Works alongside it. And only then does the idea begin to change.

This mirrors what I see in real life.

Staying With an Idea

A few years ago, one of my students, Jerry Chen, came to me convinced that LinkedIn-style networking was broken. It wasn’t working for new people entering the workforce, nor for those looking to hire and groom the next generation of talent. His first version of the idea, SWIPE, wasn’t right. Our first idea rarely is. But instead of protecting it or overthinking it, he worked on it. He shared it. He let it change.

He took a semester off, then another, and another. In that time he got his updated venture, Latte, selected into a top accelerator, TechStars. In addition to receiving funding, he earned time to iterate on his product and learn more about his customer. Last year he was working with one university on his mentor platform. As of our lunch yesterday, he is working with fourteen universities.

What changed wasn’t the quality of the original idea. What changed was his willingness to engage with it before it was fully formed.

A More Human Capacity for Action

This is the core of Entrepreneurial Intelligence: the human capacity to act, learn, and create meaning when the usual guarantees are missing.

Most ideas aren’t good when they first appear. Some won’t get better at all. But unless we practice engaging with them, feeding them attention, sharing them with others, letting them evolve, we end up like the boy at the beginning of the story, convinced that ideas are fragile, strange, and ultimately not meant for us.

And that’s how capable people stay stuck—not for lack of ideas, but because they were taught to wait.

For some reason I keep finding myself thinking about BeReal. BeReal was a photo-sharing app that was a reaction to the declining authenticity of social media. It would force the user to take a photo once a day, and at unexpected times. In 2022, I remember observing the growing excitement behind the app in my undergraduate classroom. At different moments during class, a student’s phone would buzz and you could feel a small ripple of excitement or urgency. It almost felt like different groups of students were part of a shared experience that was fresh and new.

BeReal was a reaction to the hyper-curated Instagram feeds that made people wonder what happened to the everyday moments. The moments before we had our make-up and hair done. When we weren’t #winning and instead feeling like crap–that we might be close to rock bottom. According to The Tab, part of BeReal’s decline is due to changes they made to the product. Initially, the photos were fully unscripted with a short timer catching you off guard and forcing you to take photos of your real life. BeReal introduced an opportunity to delay the picture, which effectively meant photos were scheduled around winning moments (like the photo of our BTE class at their signature Design Sprint above). With more curated photos, the app started to feel no different than Instagram and the buzz subsided.

From Unscripted to Optimized

The reason BeReal comes to mind in this current moment is that it was a response to the decline in authenticity and natural human awkwardness in user-generated content. AI is accelerating and exacerbating the inauthentic nature of social media but now has moved into the workplace as well. Starting with LinkedIn think pieces that used to feel grounded in the authority of the writer are increasingly feeling like bullet-pointed lists from queries on trending topics. Instead of watching the thinking out loud of middle managers and executives, I’m being given the polished conclusions with posts that read: “But here’s the truth” or “Nobody talks about the real reason…” The challenge is that the AI Slop extends outside of LinkedIn and follow through into pitch decks, emails, and project plans.

Maybe this phase will pass. Maybe the AI Slop settles as the novelty wears off. I just hope that around the corner is a new way for digital interaction to feel less rehearsed. Seeing the winning moment, hearing the final conclusion, being given the key takeaways leaves me yearning for the broader narrative. What did the middle point look like? What would we see if we caught you off guard? What was the struggle and what’s still unclear?

On Instagram many say the real joy is in the comments section. It’s a place where the town square gathers to loosely opine on memes. We love the unscripted conversation because it makes us feel seen.

Feel free to share your own unscripted thoughts below!

January is when identity gets renegotiated. Individuals do it through habits—eating better, procrastinating less, finally working out—all ways of embodying who they aspire to become. Even if they don’t talk about it that way, organizations do something similar. The block for individuals and organizations alike is not to simply change your actions, but to actually change the thinking that leads to your actions. The challenge is to find your reset moment, your January, to make that shift.

Over the past five years, I’ve worked with hundreds of startups. In my classroom, I look for startups that need help on strategic projects as a way of creating learning experiences for students. These projects often revolve around helping startups consider new directions, new products, and new identities. In the past year, my students worked with Terra, a YC-backed manufacturing company exploring different industries as customers; PlotTwist, as they changed their positioning within the dating app market; and Fulton, a D2C orthotics brand exploring a new product. For students, these projects offer a white space to practice entrepreneurial skills. For the startups, they offer a fresh outside perspective.

Talking to Customers Is the Easy Part

Students are increasingly comfortable and excited about engaging with customers directly. In my classroom, students learn the art and science of what is often called customer discovery, which can require a bit of cringe as you get out of your comfort zone to identify meaningful pain points. In a digital world where so much is done online, there is a novelty to talking to customers in real life. But what I’ve found to be a harder lesson is slowing down to represent and capture what they are noticing and hearing.

In design, this shows up as artifacting. In a modern business classroom, it looks like putting together a slide before it feels like it fully says something. Artifacting turns private thoughts and early insights into shared engagement. It facilitates our thinking and ultimately forces us to make a claim that a particular fact or idea might be important. The problem is that the faster teams move, the more students begin to believe that action equals learning, so updating a slide feels like standing still. This tension isn’t theoretical. It shows up in real startup decisions.

The Slide That Changed the Conversation

That resistance showed up clearly in our work with Fulton. In one of our early projects, students were asked to explore adjacent markets, including the sandal category. Teams talked to customers, visited shoe stores, and reviewed existing products. Much of the work looked similar across teams. But one team paused a bit longer between steps.

On a single slide, almost as a throwaway observation, they noted an indoor house shoe as an opportunity. At first, it seemed counterintuitive. People do not typically think of shoes as something you wear indoors. That may not matter if shoes are only about protection. But it matters a great deal if the product is about alignment, support, and long-term joint health. That pause and the willingness to put the idea down shifted the conversation.

Fulton took that insight seriously. The house shoe launched in October (pictured below) and has since become their best-selling product. More importantly, it helped clarify how the company saw itself. Not as an indoor shoe brand, but as a health-focused footwear company delivering quality, affordability, and style. Indoor was not a limitation. It was the place where their identity became visible.

Early-stage startups are constantly shifting what they build and who they build it for as they search for product–market fit. Looking for new pastures, trying new tactics, and even exploring new identities are all part of what it means to be a startup. In a world accelerated by AI, where movement is cheap and iteration is fast, the pressure to keep evolving can be overwhelming. Constant motion, a defining feature of hustle culture, risks causing founders to miss the value of pause and reflection. This is why January matters.

The Reset Most Startups Miss

January isn’t really about changing what you do; it’s about changing how you think about what you do. Someone can go to the gym because they feel they should, but that rarely forms a habit. When they start going because they see themselves as someone who works out, the same action produces a very different outcome. The same is true in startups. Even companies with only two co-founders can get stuck inside a particular belief about how learning happens. You can hear it in the language they use. Seeking to “validate” signals a belief that only data and evidence can provide direction, while cultures obsessed with “shipping” reflect a stance where output matters more than hitting the target. Each becomes limiting when treated as universal.

Nothing magical happens when the clock strikes midnight. But each year, individuals and companies use the calendar as an excuse to reset—to reexamine how they think, how they decide, and how they act. For startups, it’s always January. The real question isn’t whether you’ll keep moving forward. It’s whether you’re willing to change how you understand what your movement means and whether it’s still the right one for the moment. This is the kind of entrepreneurial intelligence I try to develop in the classroom: being fluent in different ways of learning, and willing to switch when the situation calls for it.

Yesterday I found myself standing beside the 80-foot sculpture entitled, “Water’s Soul,” in Jersey City. I was there with a friend, and together we walked around town, immersing ourselves in its vibrant public art. From afar, the sculpture appears like a mirage rising from the water, inviting quiet contemplation.

Walking away we began to trade stories of how we spent our winter holidays, and I confessed that despite being halfway through the first month of the year, I hadn’t yet taken stock of where I wanted to spend my energy this year. I shared that I felt like I was drifting. Typically I make it a practice to look at my list of goals and prioritize them in ways that feels fresh and intentional. Only as the words came out did I realize I’d been assuming that I equated a lack of a plan with being irresponsible or unserious.

This type of thinking, that action without direction, or playfulness for its own sake, is somehow irresponsible is exactly the type of thinking I spend my days pushing against in the classroom. Finding myself caught in the same trap, and hearing it out loud, felt embarrassing. But that’s how strong the pull of causal thinking rooted in scientific management can be.

Through formal education and into our workplaces, we internalize the consistent sequence: make a plan, then take action. Breaking from that pattern can feel almost brutish. As if action must always follow thought, otherwise we risk becoming something less deliberate, less human. And yet, when an animal senses danger, it doesn’t think—it moves.

Why is it so hard to trust our non-cognitive facilities like intuition, aesthetic sense, and pragmatism?

I look at the work that moments ago I said I was “drifting into” and they are all activities and workshops that I’m pretty excited about. Is that not enough? Reflecting on my own career path, it didn’t reveal itself all at once. Going from managing risk at the Fed to fostering entrepreneurial risk-taking in the classroom only makes sense in hindsight.

It reminds me to quiet my inner critic and consider that my annual check-in can also be about quieting the competing ambitions to see what it reveals. Jaume Plensa’s sculpture sits silently facing New York City but with the gesture of her finger to her lips, clearly says, “shh”. When asked why, Plensa said that the sculpture is telling us, “to listen to the profound noise of the water talking to us.”

My business students made this. By all accounts, there is no logical reason to give my business students an assignment to make art. Following a typical entrepreneurship syllabus, they should be learning how to size up a market or pitch a product, not drawing. Yet, the act of making something that doesn’t optimize—something with no clear business utility—unlocks something essential. It gives us permission to explore, to work with uncertainty, to bring our whole selves, emotion and intuition and feeling, alongside our analysis. This wasn’t a cute icebreaker. It was an intervention.

The Myth of Optimization

When we are young, almost every kindergartener will say they’re an artist. It’s an identity they claim without hesitation and one that adults validate with refrigerator wall space and heavy praise. Play, novelty, and craft come naturally when we are young. But think about it for yourself, how would it feel to sketch something and share it with a colleague today?

As we get older, the artist identity slips away. We’re taught everything must have utility. Every hour must produce. Every decision must drive toward measurable results. Initially we called them time management hacks, now they pervade all aspects of life as so called “life hacks” to get more done with less time. In this world, there is less time for novelty, and certainly less time for something that feels lacking in some immediate utility.

Yet this type of thinking and behavior costs us the ability to explore without knowing the outcome. To make things that might not work. To trust our intuition alongside our analysis. To pursue fleeting joys and whimsical goals. Many incredible companies have unlikely beginnings from tinkering or solving their own problem. Airbnb started with air mattresses to pay rent. Craigslist began as an email list about SF events. Patagonia grew from a climber making gear he wanted to use.

One of my students, Eric, captured this in his reflection on his piece—a twist on Banksy’s Girl with Balloon where someone pulls the girl away as she reaches for it. He shared this reflection about the piece:

He’s 18 years old. He’s just starting. And he’s already painting about losing his freedom to explore.

This is what happens when optimization becomes the only lens. We lose the very things entrepreneurship requires: exploration, intuition, the willingness to make things that might not work. You can’t build something new if you only do what’s already proven.

Rewire: Give Yourself Permission

There’s a fresco that hangs in Dartmouth’s Baker Library by José Clemente Orozco. Its title: Man Released from the Mechanistic to the Creative Life. I keep a replica in my office because that’s what this assignment is about—not teaching art, but releasing students from mechanistic thinking before they’re fully trapped in it.

My students are in a protocol—a transformation toward becoming entrepreneurial leaders. And a key part of that transformation is exploring art. Not to become artists, but to practice something essential: making things that don’t optimize, at least not right away.

This is harder than it sounds.

When I give the assignment, I can see the resistance. Not because students don’t want to make art, but because they’re wired to ask: What’s this for? How will this help me? The point is that there isn’t one. At least not an immediate, measurable one.

One of my students, Beckey, captured this struggle in her reflection:

“I really wanted to throw the piece away and restart but for some reason I just felt like that I would be giving up on myself, so I went through with it.”

She finished it anyway. And what she created, fractured clocks swirling above a girl’s head, tears falling, was one of the most striking pieces in the class. The discomfort was the point.

What Making Art Teaches

Loss has a way of clarifying what matters. Dr. BJ Miller lost both legs and an arm in an accident during his sophomore year at Princeton. The experience led him to spend years thinking about what makes life meaningful, especially for people facing death. He became curious about why humans make art at all. His conclusion:

‘Art is inherently kind of useless, and that seems to be part of its charm.’

Coming from someone who lived so close to mortality, the point wasn’t about uselessness. It was about perspective. Art matters because it shifts how we see.

In Art & Fear, authors Bayles and Orland write about the ceramics teacher who divided his class into two groups. One would be graded on quantity—50 pounds of pots. The other on quality—one perfect pot. The highest quality work came from the quantity group. Why? Because they were making, learning, and iterating. The quality group sat around theorizing about perfection.

Making teaches what planning can’t. When you create something, even something that doesn’t optimize, you learn to work with uncertainty. You learn that action reduces uncertainty. Business education trains us to privilege efficiency and analysis. But entrepreneurship requires the ability to make things before you know if they’ll work—to trust intuition alongside data.

When my students reflected on their work, many of them described a similar shift. Justin wrote:

This is the transformation. From needing certainty to accepting uncertainty. From optimizing to exploring. From perfect to good enough to start.

Start Making

You don’t need an assignment or a classroom to practice this. Pick one unfinished thought or half-formed idea that’s been sitting in your head. Don’t evaluate it. Don’t perfect it. Just make a first draft, messy, incomplete, and rough.

Write the bad first paragraph. Sketch the ugly prototype. Record the rambling voice memo. Movement creates clarity. The work isn’t about becoming an artist. It’s about giving yourself permission to explore without justifying.

You can see the full gallery of student work here

My kids love flying. They were lucky enough to travel at a young age and experience the adventure of the journey to new places and experiences. Unlike them, I was terrified of flying.

My fear began long before takeoff, while I was still packing my bag, and only intensified on the way to the airport. Once on board, I scrutinized every expression and gesture from the flight attendants, as if my life depended on decoding them. When turbulence hit, I gripped the armrests as my stomach churned and my heart raced. Despite being just a passenger, I acted as though I had some responsibility for keeping the plane in the air. It was exhausting.

Comparing entrepreneurship to flight is meant to capture the exhilaration and the potential for achieving new heights but also to emphasize the chaos, improvisation, and deep sense of uncertainty and fear.

But I think these sayings reinforce a myth that holds too many people back from starting new ventures, new jobs, or new initiatives. They reinforce the idea that entrepreneurship is terrifying and that fear and turbulence are signs to turn back. I'd like to offer a different metaphor for flight—one that reflects a truth I've experienced personally in my own journey of overcoming fear.

I'm no longer afraid of flying.

The same reframing that worked for my flight anxiety can transform how we think about entrepreneurship. What changed wasn't the turbulence—it was my thinking. A book called Flying Without Fear by Duane Brown helped me learn what all the plane sounds meant, how often pilots train for emergencies, and how much redundancy is built into modern aircraft. But more importantly, it helped me understand myself. I didn't fear crashing—I feared losing control.

I didn't need to conquer those fears. I needed to acknowledge them, then reframe the risk. I rewired my thinking, and flying stopped being something I had to endure. I stopped feeling like I was being shipped across the country like cargo. Instead, I imagined myself as an explorer, discovering new lands. I wasn't being forced to fly. I was lucky to have reasons to fly and resources to pay for it.

Over time, my career has taken me to 34 countries—from Korea to Bahrain, Peru to China. I still find myself with a nervous edge during significant turbulence. But what's different today is that I accept my lack of control. I accept that I may feel uneasy sometimes. I accept these things because I chose to be on the adventure. I'm not falling; I'm exploring!

Entrepreneurship can produce the same knot in our stomachs as turbulence. It taps into our fear of uncertainty, public scrutiny, and falling flat on our faces. But the myth that it's too risky—and only for the boldest among us—is one of the most damaging false narratives out there. An academic study published in 2023 revealed that nearly everyone has a business idea, but fewer than half even took basic first steps, like searching online or talking to a friend to explore it. People aren't just failing to launch; they're afraid to even give voice to their ideas.

Rewiring Your Mind by Accepting Loss

Just like I reframed the risk of flying for myself, entrepreneurs must learn to reframe the risk of starting something new. The key is not to eliminate the fear—but to name it, understand it, and recognize that the biggest risk might actually be not trying at all.

One powerful tool successful entrepreneurs use is the Affordable Loss Framework. Instead of asking "What can I gain if this works?" they ask, "What am I truly willing to lose to try this?" To try out the Affordable Loss Framework, first think through that very question. Start by making three lists:

• Time: How many hours a week are you willing to dedicate to this new venture or initiative? We often think activities are all or nothing, but what if you gave up only a few hours on Sunday mornings?

• Money: What's the financial risk you're comfortable with? Most people assume a new initiative or venture will require a financial commitment. But how much really are you putting at risk?

• Reputation & Emotional Energy: What difficult conversations are you prepared to have? Your venture may cause some people to think of you differently, and not always in terms you'd prefer. Get clear on how much energy you're ready to expend in your relationships.

Once you've done this exercise, you know what personal resources you are committing. This approach keeps the fear and risk bounded and the learning alive.

Unlearning Opportunity Cost

While this approach seems very simple, it’s a radical shift from what most of us were taught about decision-making. Traditional business logic is grounded in opportunity cost—we're always weighing trade-offs. If I spend time on big clients, I'm doing it at the cost of new clients. If I attend my daughter's concert, I miss presenting to my boss.

That mindset assumes we're always weighing two equally clear outcomes. It puts us into a strange business mindset, in which every action forces us to compare what we've done with what we could have done. Instead of enjoying your child's concert, you're wondering if this spring concert was different enough from the fall concert to be worth your time.

The Affordable Loss approach flips the script. It starts not with optimization, but with desire. It asks:

• What do I want to do?

• Where do I value spending my time?

A distinguished scholar, Professor Melissa Cardon, has spearheaded research examining the motivations of entrepreneurs which reveals that entrepreneurs are mostly NOT driven by wealth or achievement. Instead entrepreneurs are driven by deep passions with specific activities—inventing, growing a company, working with people, having an impact. That kind of passion isn't reckless. It's aligned. And alignment makes risk or turbulence feel meaningful, not paralyzing.

Reframing Turbulence

The myth of the reckless entrepreneur keeps too many people stuck. It says: Don't move unless you're sure and be careful of the free fall!

The reality is that entrepreneurs aren't fearless. They're just tuned in to their goals. They move not because they're brave, but because they've found something worth the risk.

To be sure, things will go wrong on your new venture or initiative. You will face uncertainty and fear. The fear isn’t a stop sign. It’s just turbulence on the way to somewhere new. You don't have to do this; you get to do this. So get on your plane and chart your course.

On Friday, I visited Asbury Park's "Anti-AI" Art Show, and the magic that artists Michael LaVallee (Better known as Porkchop) and Bradley Hoffer have pulled off with their works reveals something deeper than just a critique of artificial intelligence. Their show is a reminder of what we risk losing—not just in art, but in the way we engage with creativity itself.

The ArtSpot, a new art haven just steps from the Atlantic Ocean, is the kind of place that feels like a response to the times. Asbury Park has long been known for its music scene—Bruce Springsteen's hometown—but today, it's increasingly becoming a vibrant hub for artists, makers, and cultural experimentation. In this show, longtime friends and collaborators Porkchop and Hoffer strip their work down to its most basic form: cardboard. No color, no embellishment—just light, shadow, and precision.

What stands out most to me from the cardboard artworks is the tension they capture of being both monumental and yet fragile and ephemeral. These are not small projects–filling the art studio with a range of explorations from a robot, to apparel, to a space ship control station. Each in their own right are impressive for their detail, the subtle interplay of shadow, depth, and layering. There is no color beyond the beige of the cardboard and yet the art feels alive and substantial. As you engage with the artwork, more details emerge that all speak to the careful craft of bending, cutting, and placing paper to fit the distinctly human imagination.

Why the Anti-AI Art show challenges us to think about AI

Have you ever made a cardboard fort as a kid? Or maybe a car, like my son in the picture? A common parenting experience is buying your child a new toy, only to watch them become more fascinated with the box it came in. The toy—let's say a truck—has a defined form, a set purpose, and an expected way to interact with it. The cardboard box, on the other hand, is a blank slate. It can be anything—a spaceship, a house, a costume. It invites creativity, exploration, and transformation. Below you see the various explorations my kids have had through the years with boxes.

Cardboard is usually just a container, something meant to be thrown away. But in this show, it becomes art. It forces us to reconsider what we overlook—not just in objects, but in effort, in process, and in the slow work of making something real. It also speaks to the importance of impermanence, made of paper, this artwork is for now, in this present moment.

What Porkchop and Hoffer are reclaiming through cardboard is what philosopher Matthew Crawford calls "the world beyond your head" – the tactile engagement with physical materials that grounds us in reality. I first was introduced to Crawford’s writing when I read about his journey from a Think Tank to running a mechanic shop in his book Shop Class as Soulcraft. In Crawford’s body of work, he speaks to our detachment from the material world and from using our hands. He references how a shop teacher once said:

This sentiment of connection to the medium of our work is exactly what PorkChop and Hoffer are speaking to. When they cut, fold, and assemble cardboard, they're navigating constraints that AI simply doesn't encounter. Every slice of the blade represents a decision that can't be undone, every structural solution emerges from physical experimentation rather than algorithmic probability. This embodied knowledge—knowing not just intellectually but through your hands—is precisely what's at stake in our increasingly AI-mediated world.

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It’s Ironic, But I Used AI on this Article

There's an undeniable irony in writing about the value of human-made art while using AI tools to help shape these very thoughts. In drafting this piece, I've collaborated with AI to refine my language and challenge my thinking—a fact that doesn't invalidate the exhibition's message but rather complicates it in necessary ways.

Like the cardboard in Porkchop and Hoffer's hands, AI is ultimately a tool. The difference lies in how we employ it: do we outsource our thinking entirely, or do we maintain the "rough edge" of our own discernment? Do we accept what the algorithm produces without question, or do we approach it with the same critical eye we'd bring to any human collaboration?

The cardboard artists remind us that the material itself isn't what matters most—it's the relationship between creator and creation. Similarly, our relationship with AI doesn't have to be one of passive consumption. We can engage with it actively, pushing back against its suggestions, questioning its assumptions, and using it to amplify rather than replace our own creative instincts.

And Here’s what ChatGPT Wanted Me to Say

The AI wanted me to write about the perfection of AI’s output, the expediency of the experience, and ultimately the downside of missing out on the messy middle. It wrote:

Sounds true, but it isn’t quite aligned with my experience. I do navigate the messy middle. In fact, sometimes when I've used AI to write an email, I find that I spend even more time on the email than I would have without AI. When I engage AI, I'm actually trying to figure out why my view is different from the median view of humanity. Do I really have anything new to contribute right now? If the AI can predict what I wanted to say and say it better than me, what's the need for my own writing?

And that’s the reason that this Cardboard show matters the most. While it is labeled an Anti-Ai show, I don’t think it's a rejection of technology. Instead, it's a call to re-examine our own humanity. When we stare at the blank canvas of a document, how do we rekindle the imagination of our youth seeing a cardboard box? It reminds us that as we engage with AI's capabilities, we need to first understand and appreciate the irreplaceable humanity of the creative process. To be human is to see through our imagination more than what’s in front of us. ChatGPT may tell us a cardboard box is a container, we need to keep showing each other that it's so much more.

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What’s your experience with AI and Creativity?

Each of us picked a pattern from the instructor’s pile, and I got to work—extra motivated to make mine even better than my wife’s and two boys’. But instead of impressing the instructor, I got a brutal reality check. She was direct, no sugarcoating—mine was completely wrong. I had decided to gradate the pattern from light to dark, thinking I was adding a creative twist. She was not having it.

But I wasn’t there to win. I was there to learn. So, I took the feedback, set my ego aside, and embraced the rejection. After all, mastering a new skill requires humility. That experience stuck with me—not just because my mosaic was a disaster, but because it was a reminder that learning anything new requires a willingness to be wrong. You can’t improve if you refuse to take feedback. And as it turns out, that lesson applies just as much to entrepreneurship as it does to Roman mosaics.

Recently I had a chance to chat with ABC’s Shark and NYC’s Real Estate Queen, Barbara Corcoran. Almost unprompted, I asked her about entrepreneurs, and she said with utmost confidence that the key trait of a successful entrepreneur is being able to manage rejection.

“To hear 10 no’s and wait for the yes.”

The idea that entrepreneurs need resilience to overcome obstacles, rejection, and impossible odds is a common refrain in startup lore. I recently came across a clip of Elon Musk sitting next to a pile of debris from a failed SpaceX rocket launch, a visual reminder that innovation often comes through failure. And of course, Thomas Edison famously said that it took him 10,000 errors to get one success. At the same time, we also know that Elizabeth Holmes, convicted felon and former CEO of Theranos, once echoed a similar sentiment: “At first, they don’t believe you.”

So the question is, can entrepreneurs conjure an imagined world, a vision for the future, dream big—without being arrogant or, worse, deceptive? I think about this balance every time I introduce students to the Founder Challenge at NYU.

The Founder Challenge: A Different Kind of Confidence

Frustrated with the pace of new venture creation at NYU, I spoke the idea of the Founder challenge into life during a class session. I challenged the students to:

1. Become a founder.

2. In three months.

3. Be modest.

The first two parts push students to take action—quickly. Instead of waiting for the perfect idea, we ask them to adopt the identity of a founder, pick a problem, and put forward an imagined solution. Action and speed help them overcome inertia and analysis paralysis.

But the third part—be modest—is just as critical. The best founders don’t pretend to have all the answers. Instead of stubbornly defending their first idea, they treat it as a hypothesis. They go out, gather evidence, and let reality shape their thinking. The ones who succeed lead with curiosity, not ego—they’re not trying to prove they’re right; they’re searching for where they’re wrong.

This mindset isn’t just theoretical—it’s exactly how some of today’s most successful entrepreneurs built their companies.

Move Fast, Stay Humble

Some of the best founders know that confidence isn’t about blind conviction—it’s about taking action while staying open to learning. Whitney Wolfe Herd, when launching Bumble, didn’t wait for a perfect plan. She moved fast, bringing her vision of a dating app where women make the first move to life within months. But she didn’t assume she had it all figured out. Instead, she listened—adapting the platform based on how people actually used it, expanding into friendships and professional networking. Brian Chesky, co-founder of Airbnb, took a similar approach. Instead of insisting that people would rent out their homes to strangers, he and his co-founders tested the idea directly, knocking on doors in New York, talking to potential hosts, and tweaking their model based on real feedback. Both founders had bold visions, but neither relied on arrogance or empty claims. They let action—not ego—prove their ideas.

Confidence without Arrogance

This is the difference between vision and deception. The best entrepreneurs don’t just believe in an idea—they test it, refine it, and stay open to where they might be wrong.
That’s the kind of confidence that builds real, lasting ventures. Not blind faith, not arrogance—just the willingness to take bold steps while staying humble enough to keep learning.

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I probably shouldn’t be the one writing this blog.

Let me explain.

For most of my life, I was obsessed with getting it right—or at least, avoiding getting it wrong. My best friend used to joke about how many plans I made. At one point, he even suggested I catalog them all, just so I could track the ever-revised versions. Is this plan 654 or 652? he’d ask, smirking.

And he wasn’t wrong.

I spent six years being trained in risk reduction. I studied business and economics, learning how to analyze every possible scenario before acting. Then, I went to work at the Federal Reserve, where my literal job was to identify risks before they happened. If there was uncertainty, I learned to hedge against it. If something wasn’t proven, I learned to wait.

Then I left to sell gold—an ancient hedge against uncertainty itself.

For years, I traveled the world, meeting with governments and institutions, pitching gold as the ultimate protection against volatility. I sold the idea that when things go wrong—when the markets crash, when currencies fail, when uncertainty takes over—gold is the thing you can rely on. It’s safe, stable, untouchable.

But at some point, I started to see things differently.

Because here’s the thing about gold: it just sits there. It doesn’t create. It doesn’t adapt. It doesn’t do anything. And yet, for so long, I believed security was more valuable than motion.

I had spent years trying to plan my way into certainty. Years believing the safest route was the best one. But the truth?

Certainty is an illusion. And chasing it keeps us stuck.

So how did I end up here, at NYU Stern, teaching some of the best and brightest students how to unlock their entrepreneurial potential? How did someone trained to mitigate risk end up championing uncertainty, action, and embracing the unknown?

Call it a mindset. Call it a spirit. Call it "founder mode."

It’s the thing that makes you take action instead of overthinking. It’s what pushes you to pursue the idea sitting inside you, even when the world tells you it’s too risky.

And yet, I keep coming back to this one hang-up—the same one I hear from so many students, professionals, and would-be entrepreneurs:

"But I’m not an entrepreneur."

This blog is about why that’s a lie.

Not just for you. But for all of us who were taught to wait for permission, to find the “right time,” to analyze instead of act. We’ve been conditioned to avoid risk instead of engaging with it. To trust the security of the gold standard over the fluidity of action.

I used to believe that, too.

This blog is about how I unlearned it.

And how you can, too.

“Move fast and break things.” While this phrase originates from the early days at Facebook, it has come to encapsulate an ethos of entrepreneurship that is both pervasive and flawed. Over the past several weeks, we have witnessed this Silicon Valley approach seep into government at the highest levels—sending shockwaves from Canada to Gaza. We see it most vividly in Elon Musk’s near-mythic power: while stacking achievements in the private sector from PayPal to Tesla to SpaceX—his approach to government is more reckless than revolutionary. From abruptly shutting down USAID to boldly acquiring sensitive US Treasury data, it's not clear if he’s destroying or repairing. The U.S. government isn’t a startup, and Silicon Valley-style entrepreneurship isn’t the answer. Real health, security, and lives are at stake. True entrepreneurship is about building, not breaking.

The Entrepreneurial Boom

Entrepreneurship’s popularity is undeniable. The number of new businesses launched annually now nears five million, and applications to accelerators like Y Combinator have more than doubled in recent years. Universities are responding in kind: The Wharton School opened a 68,000-square-foot space dedicated to student entrepreneurship, meanwhile K-12 programs have incorporated startup skills into curricula.

Beyond formal education, the broader cultural fascination with entrepreneurship is undeniable. Shark Tank, entering its sixteenth season, fuels at-home visions of “making it big.” Podcasts like How I Built This attract millions of monthly listeners, and social media brims with influencers—from Tim Ferriss to Erin on Demand—who champion hustle culture. Whether or not people start businesses themselves, the allure of entrepreneurship remains inescapable and irresistible.

Idolizing the “Lone Genius”

Prominent entrepreneurs like Musk, Zuckerberg, and Bezos are celebrated as the ultimate self-made men—the Ayn Rand ideal of individual achievement. In my own classroom, Musk’s name comes up first whenever I ask students for an example of an entrepreneur. His accomplishments are impressive, but his outsized glorification can obscure how entrepreneurship is deeply collaborative and interdependent.

When this hyper-individualist lens is taken to an extreme, it obscures the systemic barriers that hold many people back. Women and minority founders remain dramatically underrepresented in entrepreneurship: Less than 2% of venture capital funding goes to female-led startups, and Black entrepreneurs receive less than 1% annually. For the majority of new founders, the reality is worlds apart from the lone-hero stories portrayed in the media. Yet the myth persists: that anyone can make it, if only they hustle hard enough.

At the same time, rapid changes in the workplace are pushing some people to embrace entrepreneurship, not by aspiration but by necessity. Employees no longer expect to spend decades at one firm, and the regularity of tech layoffs have reinforced the need for employees to be entrepreneurial about their career. The rise of AI and automation might further accelerate this shift, creating pressure to stay relevant, adapt quickly, and compete in an increasingly unstable job market. For many, entrepreneurship is less about chasing unicorns and more about reclaiming agency—whether by launching a startup or adopting an entrepreneurial mindset within a larger organization.

Rethinking How We Define Entrepreneurship

I teach entrepreneurship, it isn’t a silver bullet. In 2021, I launched a new entrepreneurship-focused degree at NYU Stern’s Khubani Business, Technology, and Entrepreneurship (BTE) program, where first-year applications made it the most competitive of all programs at NYU. Recognizing the risks of perpetuating Silicon Valley’s culture of hyper-individualism and disruption for its own sake, we built BTE to actively resist that model. Based on my research of top business schools in North America, I found that how you conceive of entrepreneurship impacts who becomes an entrepreneur and which stakeholders benefit. We leaned into forming a culture around a unique set of BTE values like “Human-Centered, Not Ego-Centered” and “Community Is the Answer.”

“Human-Centered, Not Ego-Cenetered”

Our goal was to encourage creative, inclusive, collaborative ventures—rather than lionize disruption at all costs. So far, that’s exactly what we’re seeing. They remain zeroed in on making transformational impact, expecting rewards, but alongside it care deeply about society's wicked problems and approach their action with equal parts humility and bravado.

Building Over Breaking

I think it’s time we rethink what we celebrate about entrepreneurship. Instead of idolizing power-hungry disruptors or championing a one-size-fits-all path to success, let’s foster an entrepreneurship that builds responsibly, collaborates widely, and acknowledges the systemic barriers ahead. The next generation deserves more than hustle myths; they deserve a model that values solving real problems for all. The era of worshiping figures like Musk—where disruption is glorified over meaningful impact—is overdue for its sunset. By broadening who we fund, support, and celebrate, we can reclaim the true essence of entrepreneurship—not “move fast and break things,” but build bravely for the greater good.

As a dad of two tween boys, I have a superpower: embarrassing my kids. Not a week goes by without them telling me I’m cringe.

From research I've done and through tons of real life experience, I've found that this is actually a major hurdle for entrepreneur. That is putting yourself in uncomfortable, even icky situations and asking for help/feedback. A prime example? Customer discovery and design thinking interviews.

These conversations are meant to accelerate your learning—about the problem you’re solving, the people you’re solving it for, and whether your solution even makes sense.

Some of the best ideas come from exploring places where insights are harder to find—where the real gems require a bit more digging. For students, this might mean visiting retirement homes or hospitals to understand the nuanced challenges of aging or serious illness. In B2B, it could mean navigating the complexity of corporate decision-making by reaching out to a VP to learn how internal purchases are made. These insights aren’t always in plain sight, but the effort to uncover them often leads to the most meaningful discoveries.

So many things can stop you from putting yourself out there:
😨 Why would they take a call from a 20-year-old?
📚 I don’t have domain knowledge—they’ll think I’m stupid.
⁉️ I don’t even know what to ask.

But my research—and experience—shows that people are incredibly forgiving, generous with their time, and eager to talk—especially if you’re genuinely curious about their problems and interested in helping solve them.
So embrace your inner cringe. Get out there. Ask. Learn. Repeat.
That’s how the best entrepreneurs grow.

Why wasn’t Tony Stark in the Meta Super Bowl Commercial? If you’re a Marvel fan like me and my family, it’s impossible not to think of Tony Stark talking to JARVIS when you see the Meta glasses. So when Meta’s Super Bowl ad featured Thor (Chris Hemsworth) and Star-Lord (Chris Pratt) instead, you have to scratch your head. 🤔

But this was no mistake!

Back in 2021, when Meta launched these glasses, I argued in TechCrunch that co-creating with Ray-Ban was a brilliant strategy. Now, I have to applaud them again. Why? Because the key to mainstream adoption of wearable tech isn’t making it feel like it belongs only to a Tony Stark-level genius. Instead, they’re positioning it as something even Chris Hemsworth and Chris Pratt types can wear.
If these two lovable lugheads can rock smart glasses, doesn’t that make them feel a little more accessible for everyone else? Love Robert Downey Jr., but this casting choice was a great play by Meta.

And if this is what ‘masculine energy’ means to Zuck—lughead charm over alpha bro—I can live with that

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