On Saturday, a nation of five and a half million people will play England for a place in the semi-final after beating Brazil.

It feels like another sporting miracle. It is nothing of the sort.

Look beyond football. At the last Winter Olympics, Norway won more medals including most gold medals than any other nation. Magnus Carlsen has sat at the top of world chess for more than a decade. Casper Ruud has reached three Grand Slam finals. Viktor Hovland has won on the biggest golf tours in the world.

These are completely different disciplines. They demand different physical abilities, different training methods, different environments and different training cultures. A cross-country skier and a chess grandmaster do not win for the same reason.

Whatever explains Norwegian success, it cannot be climate, genetics or coincidence. The same tiny country keeps producing world-class performers across fields that have almost nothing else in common.

The explanation is a system, and that system works in a particular order.

It starts with the individual. Someone ambitious sets themselves a goal most people would consider unrealistic and begins doing the work long before anyone is watching. No institution can supply that ambition. It has to come first.

The skier is out on the trails in November, in the dark, when there is no audience and no reward, because the goal is theirs.

Before the national system takes over, there is usually a smaller one. Families support and make sacrifices. Local clubs provide coaching. Schools create opportunities. Communities notice potential and help it grow. The support is modest at first, but it creates the bridge between individual ambition and elite development.

Then, once the potential is real, the resources become deeper and far more specialised. Funding. Facilities. Sports science. Medical support. Performance analysis. The athlete is surrounded by people whose profession is developing champions.

That is the real Norwegian advantage.

It is not simply money. It is accumulated expertise in developing elite performers.

The athlete still carries the ambition. They still do the work. But the system around them knows how to transform raw determination into world-class performance.

Ambition comes from the individual. Method comes from the system. That combination explains why Norway succeeds across sports that have almost nothing else in common.

Now compare that with the way Norway tries to build new companies.

For years we have asked why Norway struggles to produce the number of high-growth companies that countries like Sweden seem to generate. The debate almost always lands in the same place. We need more capital. We need more talent. If only there were more money and more people willing to go all in, more successful companies would emerge.

Those arguments focus on inputs.

But sport already shows us that inputs are not the difficult part.

Norway has ambitious founders. They often have an early support system too. Families encourage them. Friends become the first believers and, in many cases, the first investors. What is missing comes later.

What Norway lacks is the equivalent of the specialised development system that elite athletes enter once their potential becomes clear.

Look at the difference.

An elite athlete receives coaching from people whose profession is developing champions. A founder receives capital from people whose profession is allocating capital.

Those are not the same craft.

Investors are selected because they can assess opportunities, manage risk and allocate capital. They are not selected because they know how to develop founders. We would never expect a skier to reach Olympic level with funding but no coach. Yet that is remarkably close to the support we offer entrepreneurs.

We built a financing system and mistook it for a development system.

This is worth reflecting on.

Norway already knows how to build world-class performers. It demonstrates that every winter, on the football pitch, on the chessboard, on the tennis court and on the golf course.

It understands that extraordinary performance begins with individual ambition, grows through early support and depends on expert development.

The real mystery is not why Norway succeeds in sport.

The real mystery is why we have never built the equivalent system for company-building.

On Saturday, eleven Norwegian footballers will walk onto the pitch against England with a place in the World Cup semi-final at stake.

However the match ends, one thing should already be clear.

Success on that stage is never an accident. It is the visible result of a system that spent years developing talent before the rest of us noticed.

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A few weeks ago I was at a summer get-together. The usual mix of founders, investors and people from around the startup world, with everyone a little more relaxed than they are the rest of the year.

I got talking to a founder. He was building something he clearly cared about, and at one point he said the thing I hear surprisingly often now.

I know I would make mistakes. I know my startup might fail. I have made my peace with that.

I admired it. If the fear of failing stops you before you start, you never build anything worth building.

Later that evening I ended up next to an investor. He asked what I do. I had barely said I work on reducing startup failure before he started shaking his head. No, he said, you cannot remove failure from startups, that is not how this works.

He was not being dismissive. He was defending something that matters to him.

Walking home, I realised they had reacted to the same misunderstanding from opposite ends. The founder thought I wanted to take away the risk. The investor thought I wanted to take away the failure. I want neither.

Some companies should fail. Many will.

When a company starts, nobody knows whether the opportunity is real. Not the founder, not the investor. Sometimes the market is not there. Sometimes customers do not care enough. Sometimes the economics just don’t work. Finding that out early is a good outcome. It means people, capital, and time can move on to something with a better chance of succeeding.

What interests me now about startups is everything that happens before a company commits serious money, time and people to an assumption it has never actually tested.

You hire because you believe the demand is there, or will be once the product is ready. You build a feature because you believe customers need it. You spend on paid marketing because you believe you have found something repeatable. Every one of those is a decision resting on an assumption.

And when the assumption turns out to be wrong, you rarely lose only that one decision. You find out that months of hiring and building and spending were all sitting on top of it.

Here is how I have come to think about it.

Every stage of a startup asks you for another commitment of money, time and people. You have to earn the right to make it.

Earning the right to commit more time, money and people is not complicated, but it is rarely impressive-looking work. At any given stage a company is sitting on dozens of assumptions. Most of them are not yet the assumptions that determine the next decision. One or two do. They are the ones that decide whether the next bet makes any sense at all, and everything else can wait. The skill is knowing which one or two you are actually standing on right now, and going straight at those instead of spreading yourself thin across all of them.

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So you go at them. The companies that do this well spend surprisingly little time debating. They go to customers. They run a series of experiments, small and cheap. They look for evidence that would prove them wrong rather than confirm what they already hope is true.

Most of the time the experiment does not give you the answer you wanted.

That is exactly the point.

A failed experiment costs almost nothing next to building the wrong product, hiring the wrong people, or scaling something that was never ready. And what you are left with afterwards is not a guess. It is a conviction you have tested, so you know where the money should go next.

None of this is a promise that the company works.

You can test the right things, challenge your own thinking, make every decision well, and still find the market was not there. The bet at the centre of it can simply be wrong. That risk never goes away, and it should not.

So the founder was right, and the investor was right. Failure is part of building something new. The only question that interests me is what you fail because of.

If you tested the assumptions that mattered, went looking for the holes in your own thinking, and still found the opportunity was not there, that is a failure worth having, and one you can be proud of. You learned what the market had to teach, and you learned it without spending years pretending you were certain when you were not.

Failing because you spent the money before you checked is a different thing altogether.

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The Avoidable Startup Failure publishes in August. If you want to read it first, you can sign up at anjali.no/book

People start companies for all sorts of reasons. Some are looking for meaning. Some are convinced they can do a better job than their employer. Some become obsessed with an idea and cannot let it go. Increasingly, many are drawn in by the stories they hear. How hard it is. How big it can become. How much you can win if you get it right.

The reasons are personal. For me it was the first one. Today it is often the last one. Most founders are probably driven by some combination of all three.

I have always loved the entrepreneurial spirit because I grew up around it. In India there is a word for it: Jugaad. It is often translated as frugal innovation. Researchers have written about it and business schools have studied it, but the idea itself is simple.

When you have very little and face a never-ending stream of problems, some of them tied directly to your survival, you do not stop at the obstacle. You find a way around it using whatever resources are available. The solution is rarely elegant. It only needs to work well enough to get you to the next step or next problem.

Paul Graham, the cofounder of Y Combinator, noticed the same sort of drive in founders and described it as being relentlessly resourceful.

It is an unusual quality. Most people do not have it. The people who do often find each other and end up building companies together.

What is often missed is that jugaad consists of two separate instincts.

The first is determination and drive. The refusal to give up when confronted with a problem.

The second is a frugality discipline buried inside the jugaad mindset. You try the thing first. You get it working once, in the smallest way you can manage. If it breaks you patch it, again with next to nothing. If it holds you keep it going and make it sturdier as you go. If it falls apart completely you start over, and starting over does not hurt, because you had hardly put anything in. The small-spending is part of it.

When you are wrong, and founders are wrong frequently, you discover it early and at low cost. You learn faster because mistakes remain affordable. That cycle of trying, learning, adjusting, and trying again is what allows resourceful people to make progress despite limited means.

Somewhere along the way, that second instinct began to disappear.

In the last twenty to twenty five years this instinct ran into a particular kind of money. Venture capital.

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The venture model rests on a few things being true. A fund backs a lot of companies, expects most to come to nothing, and needs a few to pay for everyone. So the winners cannot just do well. They have to get huge, and get huge fast enough for the fund to cash out in time. For about twenty years the world cooperated. The internet meant you could reach everybody, so a winner could get bigger than winners used to get. Software models implied that once it worked, it worked at almost no extra cost and with significant margins. The VC model depended on exits, and there were plenty. And money was cheap, so you could throw it at a young company to grab the market early and sort out whether the business made sense afterwards. They even named it. Blitzscaling.

For a long period, the environment supported that approach. The internet made global distribution possible. Software businesses could scale at costs that traditional businesses could only dream of. Capital was abundant and interest rates were low. Investors could pour money into young companies in the hope of capturing markets first and figuring out the economics later.

The model produced some remarkable companies and generated enormous returns. Entrepreneurs studied those successes and were inspired by them. Investors searched for the next one. Books were written about them. Conferences celebrated them.

Gradually, venture-backed growth stopped being one way to build a company and became the dominant story about what building a company looked like. Other paths continued to exist, but they attracted less attention, less capital, and fewer headlines.

That shift had consequences.

The founders who came in lately did not learn this from doing it. They learned it from stories. And the stories were the big ones. Those relentlessly resourceful had applied themselves using money to reach scale, value and personal gains. Nobody was telling you about the relentlessly resourceful that stayed small and fine. Nobody told you about the ones that got huge amounts of money and still died, some fast and most slowly. Because who gives that kind of talk.

What reached new founders was therefore a highly curated sample. The lesson was drawn from survivors.

This is survivorship bias.

The stories kept the first part of what jugaad means and lost the second. Of course they did. The relentless drive is what sounds good and given success makes a good story. The frugal, slow, test-it-first part does not make anyone lean in. That just sounds slow and boring. So that part just fell out of the success story, and the founders who learned from the story never knew it was supposed to be there.

Over time, many founders amplified their inbuilt drive without learning the restraint that originally accompanied it.

Capital amplified the imbalance.

A resourceful founder with substantial funding still possesses the determination to move quickly. What disappears is the pressure to validate each assumption before making the next investment. Mistakes that would once have been exposed immediately can remain hidden for months or years. Money does not create bad decisions, but it can delay the feedback that would have revealed them.

I fell into the same trap.

The jugaad mindset shaped much of my life long before I became an entrepreneur. Yet I absorbed the same stories as everyone else. I moved faster than I should have. I forgot the part of the instinct that had made the rest of it work.

That experience is one reason I am writing this book.

The Avoidable Startup Failure will be published in August. If you would like to read it first, you can sign up at anjali.no/book.

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One way of talking comes from inside the startup world itself. You hear the phrases. Failure is the cost of trying. The founder learned, and now it is time to move on. All credit to the founder who took the risk. And similar. In the end, nobody cares to go through what actually went wrong. The other way comes from outside the startup world, from the older established business world and parts of the financial press. There, a failure is talked about as a failure. Something to be ashamed of. It looks like waste. Too much money lost, and too many broken promises.

People usually end up on one side or the other without being aware of it. Both camps hold a piece of the truth, and between them they lose all the nuance and depth and leave a hole. Neither one asks the only question that matters afterwards. Was this failure avoidable, or was it not? The first camp produces stories that skip the hard parts. The second produces shame and silence. Neither produces the examination that would tell you what actually happened.

I have always been the kind of outsider who does not like being placed in a camp without noticing it happen. A physicist does not work that way. So I ended up looking at the hole and examined it from both sides.

But first let me tell you about a relevant incident. Who it was and who did what does not matter. About five years ago I watched someone from outside the startup world ask a fair question in the press about a shooting star, a fast-growing, fast-raising company that was on everyone’s lips. He asked whether the numbers would ever add up, given the kind of business it was and the unit economics underneath it. The reaction was not a discussion. It was a public fight. He was attacked for not understanding innovation, for being too cautious, for missing what the new economy was about. The startup world closed around the company, and the questioner became the outsider who did not get it.

I was watching from the side, and I could see what he saw. The numbers did not add up, and they would get worse, not better, the bigger the company got. I said nothing in public. I did not dare to lose my standing as someone who understood the startup world and supported it. I knew enough to ask the question. I did not ask it. The company collapsed a few years later. The questioner was right. The people who had attacked him did not go back to him, and both camps moved on to the next thing.

Before this gets read as an argument against ambition, it is not. The optimism that builds companies is not the problem, and the people asking sharp questions from the sidelines are not automatically right. The problem is that the question itself, the one about whether the foundation holds, dies in the gap between the two camps. One side will not ask it. The other asks it in a way the room has already learned to ignore or dismiss.

Then it was my turn, and I did not ask it of myself either.

I used to think Tørn failed for many reasons, all arriving at once, within one year. Someone called it the perfect storm. The term made sense, so I started using it myself. The capital market contracted sharply. The DIY market tightened. A major supplier walked away. Germany, which was supposed to rescue us, got postponed. All of it alongside three rounds of downsizing. Each reason was true on its own, and together they made a story I could tell people, and believe myself.

In the months after Tørn I started working with other companies, and the story stopped holding.

The companies I looked at were not failing for many different reasons. They were failing for the same reason, wearing different clothes. A startup moves past its current stage before it has secured the proof that stage should have required. It hires, it spends, it raises, as if the proof were already in hand. Months or years later the missing proof surfaces, and by then the hires, the spend, and the story told to investors have hardened into something too expensive to unwind.

Most companies never look this closely at their own ending. Very few do a postmortem. Most just shrug. It was bad luck. It was a shame, but this is how it goes, and they move on. The ones who do look usually start at the end, with running out of cash, and then write something on the death certificate. No identified need. Poor product-market fit. Premature scaling. Broken unit economics. The wrong team. When I looked at the companies in Norway and brought together similar statistics from the US, I stopped reading these as separate diseases. They are the same mistake, caught at different stages, given different names.

That is what happened to us in Tørn, and I can now name it at each step. We built supply before we understood demand. We committed to economics that worked on the first customers and broke when we tried to acquire more of them. We expanded into a second country before the first one worked the way we believed it did. Every name on our certificate would have been recognisable from any study of why startups die. None of it felt avoidable from the inside. All of it looks avoidable now.

This is what I keep coming back to. Some failure is the honest cost of building something new, out at the edge of what is known. Those bets are supposed to fail sometimes, and no discipline removes that risk. I am not arguing against that kind of failure. But that is not what I was seeing. I was seeing companies get wrong the things that other companies had failed on before them. It just keeps repeating everywhere.

What surprised me, once I started asking questions, was how unwilling people are to look. Not founders only. Investors, boards, advisors, the whole ecosystem. The pattern is not hidden, and many people half-see it, but almost nobody wants to examine it out loud. I think the reason is that the last two decades made it affordable not to. Capital was abundant, the next round was usually available, and a company could outrun a weak foundation long enough for the question to stop mattering. When money is cheap, an avoidable failure looks like an acceptable loss. You write it off and fund the next one.

That era is already over, and it changes what a failure costs. Every avoidable failure is a waste, and the waste does not stay private. Investors lose money they now raise with difficulty. Employees lose jobs and years. The same scarce talent disappears into companies that were never going to work and does not come back easily. The investor who takes the write-down grows more cautious about the next unfamiliar idea. In a small ecosystem, these costs do not get absorbed quietly. They compound.

What troubled me most afterwards was not that Tørn failed. It was that I had felt something was off the whole time, and ignored the feeling. I have asked myself why, and the honest answer is that the capital came with pressure attached. Raising money felt like validation, like proof that the company was working, and the message underneath it was always the same. Go. Use the money. Move fast. Stopping to ask whether the foundation held would have meant slowing down at the exact moment everything around me was rewarding speed.

When I went back through the companies I had studied, the failures seemed to start at the same kind of moment. Not at the end, when the company ran out of money, but earlier, when the big commitments were made. The first serious hires. The product built out. The expansion into a new market. Each of those commitments rested on assumptions that had not yet been tested, and there was a short period beforehand when testing them was still cheap. Once the commitment was made, the assumption hardened into something expensive to question, and usually nobody went back to it.

Those moments, and the questions that are still cheap to ask inside them, are what I am writing my book about. I wrote it as the thing nobody handed me.

The avoidable startup failure is available for pre-order signup now.

Any comments or input? I can be reached at contact@anjali.no

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I became a beta user of reMarkable in 2017. Almost nobody had heard of them then. A Norwegian company making a tablet that was supposed to feel like writing on paper, with no email, no browser, no notifications. Just a screen, a pen, and the thing you were trying to think about.

I have used a reMarkable ever since. Nine years. I am writing notes for this article on one right now.

Everything that follows is the view from outside. I have never worked at reMarkable. I have no idea what discussions have taken place inside the company, what trade-offs the management weighed, or what they knew that I did not. All I have is what every customer has, the product in my hand and the stories I have read in the press. This is one customer, who happens to also be a founder, trying to make sense of what I have observed.

Start with the simplest picture of a business. Someone wants something (demand). Someone else provides it (supply). When the right supply meets the right demand a transaction happens. Do that repeatedly, at a cost that leaves something over, and you have a business. That is the simplest explanation. Everything else is details.

Now picture demand on one axis and supply on the other, low to high on each. That gives you four quadrants, and almost every company you can think of sits in one of them.

Low demand and low supply is the bottom-left corner. Not many people want this thing, and not many people make it. There is usually a reason both are low. The need is not strong enough yet, or it does not exist at all. Most new ideas start here. Some of them stay here forever. A lot of startups die without ever leaving this corner because they built something nobody actually wanted.

High supply and low demand is the graveyard. Lots of people make this thing, not enough people want it anymore. Companies in this corner are fighting each other for customers who are not really there. Most go out of business. This is what happens to a category after the demand has faded but the supply has not yet caught up to that fact.

High demand and high supply is the busy corner. Lots of people want it, and lots of companies make it. This is where most companies end up. The product is there, the market is proven, but you are one of many suppliers. Customers compare you against the others on price, on features, on delivery time, on whatever they can compare. You compete on the margins. You can build a business here, but it is hard work and there is always someone underneath you on price.

And then there is the corner every founder aims for, whether they say it out loud or not. High demand, low supply. The market for a given need or want is proven. Almost nobody else provides it. You provide it in a way that your customers cannot find anywhere else. You are not a better version of something, you are the only version of something, and for a specific customer there is no real alternative to you.

Alex M H Smith, a strategy expert and my esteemed teacher, said this better than anyone.

Being the only is better than being better than others.

That corner is the prize. It is also rare, because reaching it requires a discipline most companies do not have. You have to decide who you are not for.

This is the thing reMarkable did better than almost anyone.

Most companies cannot bring themselves to narrow. They want the big market, the broad appeal. They look at a larger audience and cannot say no to any part of it, so they build something a little bit for everyone and end up being the only choice for no one.

reMarkable did the opposite, early and on purpose, it seemed. They were not building a tablet for everyone. They were building it for a particular kind of person. The writer. The thinker. The creative who wanted to get away from the screen they were already on all day. Someone who would pay for focus, for a beautiful object, for the absence of everything a normal tablet does.

The branding was disciplined in exactly the same way. The ads were calm and confident. They were not shouting about specifications, they were showing you a different way to think and trusting the right person to recognise themselves in it.

One of their first ads was called Get your brain back. I still send people to find it on YouTube when I want to show them what good branding looks like. It did not sell a device. It named a problem the right customer already felt, and it made reMarkable the answer to it. I watched that ad and recognised myself.

By around 2020 to 2022 reMarkable had what most founders only talk about. For the customer they had chosen, nothing else came close.

And then they had to keep it.

Here is the part that is easy to miss, and I think reMarkable missed it too.

The only position is not a trophy you win once and put on a shelf. It is a job. It has to be done again every year, because the moment you occupy that position you have told the whole market exactly where the demand is. Competitors can see it now, and some of them will come.

Holding the position means working on hardware, software, and pricing at the same time. Let any one of them drift and the position starts to go, even if the other two are still excellent. Customers do not experience your company as three separate things. They experience it as one thing, and one thing is only as good as its weakest part.

reMarkable kept working on the hardware. New devices, new models, a steady cadence of releases. That part got attention.

The software did not keep up.

The hardware always felt thought through. The software often did not. There were two separate desktop applications and it was not obvious which one did what. The usability was weak in a way the hardware never was. It improved slightly over the years, but it never felt as premium in the hand as the device itself. For a company whose whole promise was a seamless, calm experience, the software was the part that did not feel that way.

And while the software drifted, the price went up.

This is the part that should have worried them. I am still using my old reMarkable, the one from 2017. There were moments when I looked at the newer models and thought I should upgrade, but I did not do it. The price was too high for what the upgrade offered me.

That is worth sitting with. I am not a reluctant customer. I am a nine-year fan, the exact person they built the company for, someone who recommends their old ad to strangers. And even I, looking at the newer device, decided the price was not worth it. When your most loyal customer starts saying no to the upgrade, the premium is no longer doing the job a premium is supposed to do.

I want to be careful here, because I am only looking from outside. What I could see was this. reMarkable was hiring quickly. The number of employees in strategy, design and engineering grew several times over in a short time. The spending looked generous. There was a striking, one-of-a-kind office building planned in Oslo that everyone was talking about.

A premium price can mean two completely different things, and from outside they can look the same.

It can mean we are the only ones who do this. We charge this because there is genuinely nothing else like it, and the price is part of how we keep the category narrow and the brand intact. That is what reMarkable’s price was in 2018. It was earned. It matched the position.

Or it can mean the company has grown to a size where it now needs the price to be this high. The team got bigger, the spending got bigger, and the price has to stay high to cover it. The price is no longer saying we are the only. It is saying we cannot afford to charge less.

From outside, in 2022 and after, I could not tell which of these reMarkable’s price had become. That is the warning sign. When you can no longer tell whether a company’s price is set by the position or by the cost of running the company, something has already shifted.

Some of the original discipline is still visible. Their newsletters today still sound like the company that made Get your brain back. They write about focus, about working without distraction, about thinking clearly. They mention new features and new hardware sometimes, but not as the main thing. The brand voice has held. Someone in that company is still protecting it, and it shows.

All of this was happening while the supply side of the picture filled in.

Amazon’s Kindle Scribe arrived. Boox. Others. Closer in hardware than reMarkable’s customers expected anyone to get, and priced lower. The customer who in 2018 had no alternative now had several.

This is the pattern, and it is not unique to reMarkable. A company finds real demand. The supply is scarce, so the first mover wins customers quickly. Then others see exactly where the demand is, because the first mover showed them. They build. The category fills. The company that was alone in the high demand, low supply corner gets pulled into the busy corner with everyone else. And unless it has made itself genuinely hard to replace, the competition shifts to price, and the only position stops being only.

reMarkable had a real chance to be hard to replace. The brand was a moat. The hardware was a moat. But the experience that justified the premium was not only those two things, it was the whole thing working together, and the software was the part that did not keep pace.

So by the time real competitors showed up, reMarkable was charging a premium price for a product that no longer felt premium all the way through. The hardware still did. The software did not. A customer notices that before any quarterly report does. They notice it when they look at the new model, think about the price, and decide to keep the one they already have.

I am not writing this because reMarkable failed me. They did not. I am still a customer. I am writing it because reMarkable did the hardest thing first, and may have mistaken it for the whole job.

Deciding who you are not for, narrowing to a specific customer, building a brand disciplined enough to hold that line. Most companies never manage it. reMarkable managed it beautifully, and that deserves to be said plainly.

But the discipline that gets you to the only position is not the same discipline that keeps you there. Getting there is a decision. Staying there is maintenance, on every front, forever, against competitors who now know exactly where to aim.

If you are a founder good enough to reach that position, you are also exactly the founder at risk of this mistake. The entry to the only position may have felt like the achievement. It was the beginning of the actual work.

The first sign of trouble is not in the numbers. It is in the customer you built the company for. They notice when one part of what you make stops keeping up with the rest, and they look at the new version, and they decide not to buy it.

I am still using the reMarkable I bought in 2017. I never replaced it. For a company in the only position, that is not loyalty. That is a problem.

• • •

I am writing a book, The Avoidable Startup Failure: How good companies lock in failure long before money runs out. It will be launched in August 2026. You can sign up here: https://anjali.no/book

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I built a company called Tørn. A marketplace for surplus building materials. Top VCs backed us. In four years we got to 120 million NOK in revenue across two countries. Strong team. Real market. Numbers moving in the right direction.

And we failed.

Not because we weren’t working hard. We were. Not because the market wasn’t real. It was. We failed because we had committed too much, too early, to things we had never actually confirmed. The signs were there long before the money ran out. Nobody asked the question that would have caught it. Not me. Not our investors. Not our board.

After Tørn closed, I kept asking myself one question. When did this actually start going wrong? The answer was not where I expected. Not the Sweden launch. Not the big round. Not any of the decisions that looked like the cause. It was earlier. Somewhere I had not been looking.

So I went looking. And once I started, I saw the same in companies all around me.

I came to Norway to do a PhD in Physics, and after finishing I worked across a range of tech and other fields. Even though I have not worked directly with physics for more than twenty years, a physicist way of thinking never really leaves you.

What physics teaches you, more than anything, is how to take a complex system apart in your head. You look at the parts, how they connect, where the load is concentrating. What looks like a one-off is usually a pattern in disguise.

I did not use that physicist’s lens while I was inside Tørn. I used it afterwards. And what I found was not a sequence of unique failures, which is what it looks like from the inside. I saw one pattern. Same shape across different companies, different industries, different amounts of money raised.

A pattern that almost always runs its course. And almost always could have been caught early.

Tørn went down exactly a year ago.

In the months after, a lot of people came to me. Founders, mostly. They thought my experience could help them. Some wanted to hire me full time. I told them, honestly, that they should be careful with the money they had just raised. I had built a programme that could get them growth ready in six to eight weeks. Cheaper. Faster. Easier to back out of if it wasn’t working.

The programme came out of work I had been doing with ideas from Alex M H Smith and Matt Lerner, applied to startups that were past MVP and trying to scale. I ran it. It worked. The results were really good.

So that programme turned out to be my own MVP. And like every other startup, I had to find a cost effective distribution of that product.

This is where it got interesting.

My first clients had come to me. They found me. When I went out to find more of them, I ran straight into the problem my book is about. I had a bit of traction. I was about to start building around it. And the underlying demand was not as solid as the first wave had made it look.

I had walked into my own meta pattern.

My potential clients, the founders who had just raised, felt great. Cash in the bank, story confirmed, time to execute. They felt no urgency for any help. The founders running short of cash felt only one thing was missing, and it was more cash. It was hard to convince them of the fact that failure starts when everything looks good, long before they run out of money or have to raise again on a declining valuation.

I thought investors would feel the problem more. I was wrong. Investors operate inside a portfolio logic that is counting on failure from the start. Help a single company avoid a preventable mistake and the maths of the fund does not change. State funds are getting tied more and more closely to those same VCs, even as the track record of deployed capital gets weaker every year.

The pattern I had seen in companies, I was now seeing in the system around them. Same shape. Different scale.

If you stop and look at it, it is genuinely strange. Maybe this is Norway in a nutshell. Despite having a lot, still want more. And not making what we already have work.

So that was my situation. A product that worked. A market that could not feel the problem the product solved. A system structured in a way that quietly rewards not asking.

My advice to others, usually, is this.

You cannot make people care about what you care about.

One option was to walk away. To take the consulting work I was being offered and let the bigger question go.

I decided otherwise.

There is another side of me that cringes at all kinds of waste. That side could not keep watching this much capital, talent and opportunity going to nothing.

So I decided to write a book instead.

The advisory practice is still there for the founders and investors who want to do the real work of creating successful companies. But the book had to come first. Otherwise the work I was being asked to do was always going to need convincing, over and over again, for a problem that should be obvious and plain in sight.

• The book is called The Avoidable Startup Failure. It comes out in a few months. You can sign up to be told when it is ready at https://anjali.no/book

• If you are a founder or investor who recognises something in this piece and wants to talk, you can reach me at www.anjali.no and contact@anjali.no.

• If you want more writing in this direction, subscribe below.

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Every seminar, investor get-together, and conference I attend right now has the same energy. A founder on stage explaining how they built their product in a week. An investor describing how a solo technical founder can now do what used to require a team of ten. A panel nodding along about the democratisation of building.

The room loves it. I find myself sitting on my hands.

Not because it is wrong. A solo founder can build faster now than at any point in history. The cost of creating a product is collapsing.

But building has almost never been the hard part.

Think about the startups you know that failed. Most did not fail because the technology did not work. Most failed because not enough people saw the value. Because the sales pipeline never filled. Because the cost of selling never matched the willingness to pay. Because the founder spent two years building something excellent that the market received with complete indifference.

That is not a building problem. That is a demand problem.

And demand has not gotten easier. It has gotten significantly harder.

Demand is always a human problem. Even when it is a business problem — a company needing better tools, faster processes, lower costs — it is always a person who feels it and a person who decides to act on it. A specific person, with a specific habit, who has made peace with an imperfect solution because switching is hard and convincing the rest of the team is harder.

People are slow. They are biased. They act on feeling as much as logic. They have already solved most of their problems — imperfectly, expensively, frustratingly, but solved them. The default, for almost everyone, almost all of the time, is to continue as before.

I am not talking about innovators and early adopters — the people who find new things exciting rather than exhausting. Those people exist and they matter. But very few businesses can survive on early adopters alone. At some point you have to cross to the slower majority. The people who do not read tech newsletters. Who adopted their current tool four years ago and have built their whole workflow around it. Who need to see something work for someone they trust before they will consider it for themselves.

That crossing is slow work. It requires patience, repetition, and time. No AI tool touches any of it.

Inertia — the customer’s preference to continue as before — is getting stronger, not weaker.

Because the before is getting better.

Someone who might have needed your tool to solve a workflow problem can now open Claude, Lovable or a similar and prompt their way to a rough version of it. Whether that rough version is actually good enough does not matter yet. The perception that it might be is enough to delay the decision to buy. Maybe indefinitely.

Every acquisition channel is getting more expensive, more contested, and less predictable than it was five years ago. Paid search costs more. Organic reach is narrower. Cold outreach conversion rates are falling.

The founder who launches a beautifully built product today is launching into more noise, not less, against a customer base that is more resistant to switching than ever.

So here is where we are.

The supply side got cheaper. Dramatically cheaper. Faster. More accessible.

The demand side got harder. More expensive to reach. More resistant to switching. More crowded with alternatives, including alternatives people now assemble themselves for free.

And the loudest conversation in the ecosystem is about the cheap part.

When building becomes cheap and fast, the temptation to build before proving demand becomes almost irresistible. Why spend three months talking to customers and running small experiments when you can have a working product in a week? Skip the hard, ambiguous, uncomfortable work of finding out whether anyone actually wants this — and go straight to the thing that feels like progress.

The result is not faster companies. It is faster journeys to the wrong place.

A product nobody wants, built in a week instead of six months, is still a product nobody wants. You just got there faster.

The founders I worry about are not the ones who cannot build. They can all build. Some of them can build extraordinarily well, extraordinarily fast, with a small team and an AI assistant, agents and infrastructure that would have seemed like science fiction ten years ago.

The founders I worry about are the ones who have mistaken the ability to build for evidence that they should. Who launched because launching is now easy, not because the demand was proven. Who are six months in, with a beautiful product and an empty pipeline, wondering why the growth is not coming.

The answer is not a better product. It was never a better product.

It was proof, gathered before building started, that someone wanted this badly enough to change. A specific someone. A slow, biased, habit-bound human being who had to see enough reason to stop doing what they were already doing. Getting that person — and then the next one, and the one after that — to move is work that no model accelerates.

It requires sitting across from a potential customer and understanding, precisely, what it would take to make them act. That work is slow. It is ambiguous. It produces nothing you can ship.

It is also the only work that determines whether everything else matters.

The ecosystem does not need better builders. It has plenty.

It needs founders willing to do the demand work first — before the building starts, before the runway burns, before the window closes.

That is the part nobody is celebrating. That is the part that needs to change.

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Paul Graham, cofounder of prestigious Y Combinator, called it relentlessly resourceful. Not just smart. Not just hardworking. The specific combination of someone who doesn’t stop and someone who always finds another way. Capital scarce — they find a path. Product breaks — they redesign. First ten customers say no — the fighter spirit goes up, not down.

It is rare. And it is genuinely what gets companies through the early phase. Without it, most never start. The first few rejections become the last few.

So investors screen for it. Explicitly and instinctively. When they back a founder, they are in large part betting on this quality holding.

They are right to.

What nobody has named clearly is what happens to that same quality when the environment changes - and the founder doesn’t.

After a raise, the problems look familiar on the surface. Something isn’t working. Find the cause. Fix it. Move forward.

But the nature of the problem has quietly shifted.

Before you had customers, most of what was broken lived in the parts you could design and control - the product, the process, the technology. You could reach it. Fix it. Ship it.

After you have customers operating inside their own organizations, more of what is actually broken lives somewhere you can’t touch directly. Inside other people’s incentive structures. Inside habits built over years. Inside decisions other people make based on what is good for them - not what is good for your product.

The relentlessly resourceful founder hears this and starts designing a solution. That instinct is not wrong. It is exactly what built the company.

But it has a blind spot. And the blind spot is predictable.

The activity itself becomes the evidence that the right things are happening.

Look at a portfolio of post-raise companies right now. Really look.

The team is growing. The product is shipping. New markets are being entered. The founder is genuinely busy, not performing it. There are new fires every week. Some get handled. The board updates show new activities.

And underneath all of it, the questions that actually determine whether this is a business have never been cleanly answered. Who is getting enough value from this that they will keep paying - and tell others? Can that value be delivered consistently without the founder personally holding it together? Are the unit economics moving in the right direction with each new transaction, or is growth making the underlying math worse?

Not because the founders are avoiding these questions. Because they never stand still long enough to see them.

The relentlessly resourceful founder has an innate preference for moving. It is not recklessness. It is identity. Standing still and questioning the foundation goes against everything they are wired to do. There is always another fire. Another piece of content to write. Another event to speak at. Another reason this quarter is not the right one to slow down. And always a way to read the current numbers as confirmation.

So the questions that need to be asked get carried forward. One quarter. Then another.

This is when failure gets locked in.

Not in the dramatic moment. Not when the company hits a wall. In the quiet period when everything seems to be working. When the team is hustling and some metrics are moving and the founder is doing exactly what they were backed to do.

The decisions being made in this period are expensive. Not because they are wrong. Because by the time it becomes clear they were built on untested ground, reversing them costs far more than testing them would have.

I lived this at Tørn. We were solving the right problems, with the right amount of energy. We were just solving them at the level we could control - the product, the process, the system - while the actual problem sat somewhere else entirely.

We had a store manager who used our platform well in the beginning. Then went quiet. When we finally reached him, he told us the truth: selling surplus at cost price had pushed his monthly contribution margin negative — the number his bonus was calculated on. That triggered an approval requirement from his manager he hadn’t had before.

We fixed the system. We escalated, got the rules changed, did everything correctly.

He never became active again.

Because by then something else had happened. He had learned that our platform meant friction, risk, and an awkward conversation with his boss. No system fix removes that memory. Trust moves on a completely different timescale than software.

That sequence - understand the problem, design a fix, execute it well, nothing changes — happened not once. It happened across stores, across partners, across markets.

We were moving the whole time.

So look around.

At the companies raising right now. At the ones in your portfolio, on your team, or that you advise. At the ones where the founder is building fast and the numbers are going up and everything from the outside looks like it’s working.

Ask the questions that aren’t being asked.

Who has to change their behavior for this to work at scale? What do they gain from doing it? What do they risk? Who measures them, and on what?

If the answers are clean and specific, good. Build faster.

If the answers are vague - if the honest response is “users will see the value once they try it” or “adoption will come when we have more features” - that vagueness is the most important thing in that company right now.

More important than the next hire. More important than the next feature. More important than the next raise.

Because capital doesn’t fix incentive misalignment. It funds it.

And by the time the activity stops, the damage is already done.

I’m writing a book about this. It’s called -The avoidable startup failure. If you want to know when it’s ready: anjali.no/book

That story is not wrong. But it is incomplete.

Because while everyone has been watching startups accelerate, something else has been happening at the same time. Quietly, the startup model itself has started to strain. And that shift may end up changing the balance between startups and incumbents more than people currently expect.

Not because the threat from startups has disappeared. It has not. But because the economics of building new companies are evolving in ways that unexpectedly favor some of the assets large organizations already possess.

To see why, it helps to zoom out.

What is actually happening to startups

When you step back from the daily noise, three changes are happening simultaneously. Most people treat them as separate issues. In reality they reinforce each other.

The first is that building software has been dramatically commoditized. AI tools now make it faster and cheaper than ever to create products. On the surface this sounds like great news for startups.

But when everyone can build, everyone does, and everyone will.

The barrier and cost to creating a product is collapsing. The barrier to being noticed, chosen, and retained is not changing nearly as much. If anything, it is becoming significantly harder.

The second is more uncomfortable to say out loud.

Most of what is being built right now, especially using AI, are tools, not businesses. And there is a big difference.

Think of it this way. A builder gets paid to solve a specific problem for a specific customer. The tool is what he uses to do it. A hammer does not care who picks it up. It works for any builder, on any job. That is its strength — and its problem. Because if anyone can use it, anyone can sell it.

A business, when done right end to end, grows by itself. Software worked as a business because you could build it once and sell it a million times. The more customers you added, the more profitable you got. That is what made venture capital work — investors funded the early losses because the growth curve justified it.

Tools do not work that way. Someone builds a tool. Someone else copies it. Then ten more people copy it. The price drops. The margins disappear. You are back to competing on acquisition cost.

Most AI products being built today are tools. But they are being funded, priced, and measured like software businesses. That gap between what is being built and how it is being valued is something I am not sure enough people are talking about yet.

The third shift is something operators have been feeling for a while. Customer acquisition is not getting easier. In many cases it is becoming harder.

Sam Jacobs pointed out in his latest newsletter that Customer Acquisition Costs (CAC) payback periods in parts of the SaaS market have stretched to 35–36 months, while sales and marketing still consume more than a third of revenue.

More companies are competing for the same attention with increasingly similar products. Acquisition cost is eating into whatever efficiency gains AI was supposed to deliver.

Put these three together — commoditized building, tools replacing software businesses, and ever more expensive customer acquisition — and the picture becomes difficult to look at directly. Startups are building faster into more crowded markets, spending more to acquire customers they struggle to differentiate for, while chasing growth metrics that the underlying business model can no longer reliably deliver. All of this while investors are struggling to figure out and then see the implications of new venture math.

Capital is moving. Intentionally or unintentionally — not away from AI, but toward the infrastructure and foundation models that power it. Away from the application layer where most startups live. The funding environment for the average AI startup is not what the headlines suggest.

This is not a temporary correction. It is a structural shift. And it would create a vacuum that most people perhaps have not yet named correctly.

The hand corporates are holding

This is where I want to pause and say something that feels almost contrarian right now.

Large companies — corporates, established players, whatever you want to call them — are sitting on a better hand than most people realize. Not because they are smarter or more innovative. History and innovation case studies are pretty clear on that. But because the game has changed in ways that favor exactly what they have.

Three things specifically.

The first is cash. Corporates have revenue coming in. Not runway — revenue. That distinction matters enormously right now. A startup needs to prove its model, convince investors, and show growth metrics on a timeline that is rarely aligned with how markets actually develop. A corporate can fund experiments without a pitch deck. It can absorb failures that would kill a startup. It can wait. In a moment where finding the right business model requires running many tests, the ability to fund those tests without external pressure is not a small advantage. It is perhaps the decisive one.

The second is time. Closely related but distinct. The venture capital clock is a brutal forcing function. Eighteen months to show traction. Three years to prove the model. Five years to exit. That clock is misaligned with the pace at which genuinely new markets develop. Corporates don’t have that clock. They have a different kind of pressure — quarterly results, internal politics, shareholder expectations — but they might have more calendar time to let something develop before pulling the plug. In the current moment, that time is worth more than most corporate leaders appreciate.

The third is existing customer relationships. This one is underestimated almost everywhere I look. Startups focus on every new acquisition with a high CAC, working hard to make the business viable one customer at a time. Corporates already have them. They have trust, contracts, data, and access. Building something new on top of an existing customer relationship is categorically different from building something new and then having to convince a skeptical market to try it. The distribution problem — the hardest problem in any new venture — is already partially solved.

Cash. Time. Customer relationships. In the game that is emerging, these are the assets that matter most. And they sit overwhelmingly with the corporates.

But — and this is the part that bothers me and should bother corporates — having the best hand is not the same as playing it well.

The window

So what does this moment actually offer corporates?

Not a guarantee. Not an automatic advantage. A window. And windows close.

During these years of struggle and uncertainty, the pressure on startups to survive will consume energy that would otherwise go into disrupting corporates. That is the window. Not permanent relief. Breathing room. Time to move deliberately while the challengers are preoccupied with their own survival.

But breathing room is only useful if you see it for what it is. And I am not sure most corporates are looking in the right direction.

Most are competing harder and harder for the same customers with increasingly similar offerings, spending more to acquire and retain, and calling it growth. The map they are using is not wrong. It is just zoomed in too close to see the whole board.

The real strategic question

Every business plays on the same board. The intersection of supply and demand.

On one axis, demand. How many people want what you are offering. On the other, supply. How many others are offering something similar.

The goal is simple. You want to be where demand is high and supply is low. Where many want what you have and few can provide it. That is where margins hold, customers choose you without being convinced, and growth does not require outspending everyone else.

The problem is that competitive pressure always moves in one direction. Toward the crowded corner. High demand, high supply. More competitors, more noise, more acquisition cost. Everyone technically competing, nobody really winning.

That is precisely where the AI application layer is today. Thousands of tools, competing for the same buyers.

Corporates are not immune to this pull. But they have something startups increasingly do not. The time and resources to choose a different direction.

The hardest part

Real differentiation in an AI-driven world requires three things.

First, creativity that cannot easily be commoditized. Not the creativity of slogans and campaigns, but the ability to see a customer problem more completely than others do and build around that insight.

Second, the courage to specialize. That often means deliberately focusing on specific customers and letting go of others. Large organizations find this difficult because the instinct is always to broaden and capture more of the market. Yet breadth often leads straight into commoditization.

Third, genuine ownership of the customer journey. Not as a data project or CRM initiative, but as the strategic foundation of the company. If you do not understand how customers actually experience your product or service, every moment of friction and every moment of value, you cannot improve it deliberately.

And without that depth of understanding, differentiation rarely lasts once competitors arrive.

The one thing AI cannot commoditize

There is an interesting implication hidden inside all of this.

AI can commoditize building. It can accelerate experimentation. It can even commoditize parts of knowledge.

But it cannot replace judgment.

The judgment about where to play. The courage to commit to a position. The continuous human work of understanding customers better than anyone else.

Those capabilities remain stubbornly human.

Which means they may become the most valuable capabilities companies can develop in the years ahead.

The hand is there.

The window is open.

The real question is who will recognize the moment and choose to play differently.

I'm writing a book about the pattern that puts startups and new ventures in the valley of death, and the window before each capital raise where the direction can still be changed cheaply. The book is currently titled- The Physics of Startup Failures.
Early access as an ebook will be available before it's out. Sign up here.

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If you’re building something and want to follow that, you’ll find it here.

This piece is republished from the latest article in the Before You Scale series. My apologies if you subscribe in both places and have received it twice.

Every founder knows the feeling of closing a round.

The relief. The validation. The momentum.

Investors have looked at your company and decided to back it. Smart people. Experienced people.

It feels like proof.

But funding doesn’t prove that a business works.

It proves that a story works.

And the moment the money lands, something subtle starts happening inside the company.

The story starts making decisions.

Hiring plans form around it. Product priorities follow it. Teams align around it.

The company begins operating as if the story is already true.

In the book I am currently writing, I call this moment the Pre-Commitment Window.

It is the short period between when a founder starts telling investors what the business is - and when capital arrives and starts getting deployed- and makes that version expensive to question.

Most companies pass through it without noticing.

Why it matters

Before funding, assumptions are still cheap.

You can ask uncomfortable questions.

• Do customers actually value this the way we think?

• Will they keep paying once the novelty is gone?

• Does each new customer make the economics better - or just add more of the same cost?

• Are we building something repeatable, or just pushing hard?

After funding, the same questions become dangerous.

Because the company has already started acting on the answers.

Hiring depends on them. Product roadmaps depend on them. Investor expectations depend on them.

And reversing those decisions becomes expensive.

Not just financially. Psychologically.

Nobody wants to reopen questions that the last funding round seemed to settle.

The pattern I keep seeing

I now work with startups several years into building.

Often the pattern is the same.

Real product. Talented team. Millions invested.

But when you look closely, the company is still answering questions that should have been resolved earlier. Much earlier.

Who actually buys this. Why they buy it. Whether the economics work.

From the outside, the company looks like a scale-up.

From the inside, it is still searching for some basic answers.

The funding did not create clarity.

It created commitment.

Why this keeps happening

No one in the system is incentivised to stop.

Founders feel pressure to execute. Investors expect momentum. Accelerators celebrate the raise.

Everyone assumes the hard questions have already been answered.

But often they haven’t.

They’ve just become harder to ask.

The real job after funding

Most founders think funding is the signal to accelerate.

Sometimes it is.

But often the most valuable thing you can do right after funding is something else entirely.

Pause.

Examine what is actually working.

Not just revenue. Not just growth.

But the mechanics underneath it.

Because if the system works, scaling becomes easy.

If it doesn’t, scaling just makes the problem larger.

I wish someone had explained this to me when I raised capital.

It would have saved years of work.

And a company.

I’m writing a book about this pattern — the window before capital commits, when the questions that matter most can still be asked cheaply. More soon.

Before You Scale is a newsletter about why smart people scale the wrong things — and what it costs when the questions don’t get asked.

You can reach me at contact@anjali.no or www.anjali.no

I wanted to argue. But I nodded.

Because there’s a question hiding inside that sentiment that I’m not sure most of the people making these bets have fully answered:

Do you understand what kind of business you’re actually investing in?

The SaaS Playbook Is Quietly Breaking

For the past two decades, software investing has followed a reliable script. You find a painful workflow, you digitize it, you charge per seat, you scale. Gross margins sit somewhere between 50 and 85 percent. Net revenue retention compounds over time. The model is elegant, predictable, and very well understood by investors.

AI breaks almost every assumption in that script.

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To be fair, the shift away from per-seat pricing is something people are beginning to grasp. Usage-based models — where customers buy tokens or pay per interaction rather than per user — are increasingly the norm in AI products. Most sophisticated buyers understand this is where things are heading. But understanding the pricing alternatives is not the same as understanding the underlying economics.

Here is what is less discussed: when an AI agent does the work, your revenue is directly coupled to your compute costs in a way that traditional SaaS never was. Every query, every task, every resolved ticket has an infrastructure cost attached to it. And those costs are not stable. We are in the middle of a global energy crisis. Data center demand is exploding. The long-term price of compute is genuinely uncertain. No one knows where and when it settles.

This means the margin profile of an AI-native business is fundamentally harder to predict than a SaaS business. It’s not just that pricing has shifted from seats to usage. It’s that the cost side of the equation is now volatile in ways that traditional software investors have never had to model. A business that looks like it has 70 percent gross margins today might look very different in two years depending on energy prices, GPU availability, and how the hyperscalers choose to price their infrastructure.

If you’re writing checks into AI companies while mentally underwriting them as SaaS businesses, you may be building your thesis on a foundation that no longer exists.

The Tool That Won’t Become a Company

There’s a second problem, and it’s more uncomfortable.

Across industries, a new kind of operator is emerging: someone with domain expertise and just enough technical fluency to assemble powerful AI tools from the inside. They are not developers. They are not buying software in the traditional sense. They are building exactly what they need, when they need it, for close to nothing. A few days, a few tools, a working application. No engineering team. No procurement process. No vendor.

This matters enormously for startups whose entire premise is selling software to companies with complex legacy workflows.
The assumption has been: these organizations can’t build it themselves, so they’ll buy it from us. That assumption is eroding faster than most founders - and most investors - have registered.

The Customer Is Building Your Product

Nowhere is this more relevant than in Norway’s industrial heartland.

Right now there is significant energy - and significant capital- going into startups that promise to digitize heavy, manual workflows in sectors like maritime, energy, logistics, and construction. It’s a reasonable bet. These industries are genuinely behind. The pain is real. The willingness to pay has historically been there.

But here’s what I think is being underestimated: the most sophisticated operators inside these legacy companies are not waiting for a vendor to save them. They’re assembling tools internally. They’re automating from the inside out, quietly and without fanfare, because the technology now lets them do exactly that.

The startup that just raised a seed round to digitize offshore inspection workflows should be asking a harder question: not just “who else could build this?” but “could my customer build this themselves in six months?”
In 2024, the answer was usually no. In 2026, the answer is increasingly yes.

What Good AI Investing Actually Looks Like

None of this means AI is a bad bet. It means the bet requires more precision than “we only invest in AI.”

The questions worth asking are harder than they used to be.

What are the actual margins when you factor in compute costs - and what happens to those margins if energy prices keep climbing?
Is this a product or a workflow that a sufficiently motivated internal operator could replicate?
What happens to pricing power as foundation models get cheaper and more capable? Where exactly is the moat — in the model, the data, the distribution, or something else entirely?

These are not exotic questions. They are the basic questions of business model analysis, applied to a new context. But they require letting go of the SaaS mental model that has served the industry so well for so long.

AI is a capability. A genuinely transformative one. But capability is not a business model. And in the rush to not miss the wave, I worry that too many investors in the Norwegian ecosystem are funding the label rather than the logic.

The companies that will matter in five years are not the ones that added AI to a pitch deck. They are the ones that figured out a durable way to create and capture value in a world where the economics of software have fundamentally changed.

That is a much harder question. And it starts with asking it.

You can reach me by replying to this email or at contact@anjali.no.
Check out My website

I sat there feeling slightly out of place. I’ve been out of retail for the past nine months, and that distance has been unexpectedly clarifying. When you’re inside an industry, you move with its rhythms. You read the same newsletters, attend the same events, absorb the same anxieties. Stepping outside of it for a while gives you something rare: the ability to watch it from a distance and notice things you couldn’t see up close.

What I noticed is that the industry is just beginning to get desperate. Not visibly-the presentations were polished, the case studies were impressive. But underneath it all was a question the room was circling without quite landing on.

Alex M H Smith, a strategy consultant and writer whose thinking I follow closely, has been writing about exactly this — that what is hard and rare remains valuable, and AI is rapidly commoditizing everything that used to feel like an edge. I think he’s right, and I’ve been seeing the same thing play out in retail specifically.

The floor is rising. And the question isn’t how to be good anymore. It’s how to be irreplaceable. Retail is about to learn this lesson the hard way.

The seminar was full of predictions. We have a long history of being spectacularly wrong about how technology reshapes society, paired with an impressive ability to sound completely certain while doing it. So I won’t add to the pile.

But I will share one observation.

Most of the conversation at the seminar was about efficiency. AI reducing costs. AI streamlining logistics. AI optimizing pricing. And fine — I believe all of that. AI is genuinely good at making existing operations leaner and faster. But there was a nagging question I kept turning over in my mind that nobody seemed to be asking directly:

Where is the value going to come from?

Efficiency is not value. Efficiency is the absence of waste. Those are very different things. And in a world where every retailer has access to the same AI tools, the same optimization playbooks, the same data-driven personalization engines — efficiency just becomes the cost of being in the game. It stops being an advantage the moment everyone has it.

There were mentions of using AI for better customer experience and personalization. I’ll be honest: I roll my eyes at this. Not because personalization isn’t real, but because I’ve seen this movie before. It’s the same mistake startups make constantly — falling so in love with their own technology and solution that they forget the only thing that actually matters: providing something of genuine value to a real person, in a way they can’t find anywhere else.

AI-driven personalization, at scale, applied uniformly across an industry, is not differentiation. When everyone does it, it stops meaning anything

There were also examples from China — people shopping in a frenzy, led by AI influencers, dopamine loops engineered to perfection. I’ll be straightforward: that stuff makes me sick to my stomach. It might be impressive as a technological achievement. As a vision for what retail should become, it’s a dead end.

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Here’s the thing I keep coming back to, and it’s rooted in something very simple about human nature.

Humans value two kinds of things. Things that are rare — that produce the feeling of “wow, that’s something I’ve never seen before.” And things that are traditional — that carry history and familiarity, that produce that warm, fuzzy sense of belonging to something larger than a transaction. What falls into each category is always contextual, always shifting. But the underlying need is constant.

What’s also constant is the dynamic around rarity. People flock to something rare, and then they move on once it isn’t rare anymore. If the rare thing has genuine quality, it gets absorbed slowly into the culture, becomes trusted, becomes what we call brand value. That’s how lasting brands used to be built. Slowly. Through repeated proof of worth.

I’m not sure that process works the same way in a world of infinite acceleration and AI-generated everything. But rarity doesn’t stick the way it used to. The cycle is just too fast now.

My honest worry is overconsumption — a world of frictionless purchasing with nothing meaningful on the other end of it. But if I try to be genuinely optimistic, I can see another possibility: this could be the moment of mass extinction for all the middle-of-the-road brands and products that never really stood for anything in the first place. The ones that survived on convenience, on being good enough, on occupying shelf space and search results. AI levels that playing field overnight. If you don’t stand for something rare or something deeply rooted, why would anyone choose you?

Only a handful of brands will create lasting value at the top — genuine rarity, renewed frequently enough to stay relevant. Everyone else is going to feel the floor rising beneath them.

If I’m being honest about my own instincts — and I said I wouldn’t make predictions, but I’ll predict my own behavior — I find myself drawn in the opposite direction from the AI-optimized shopping experience. More offline. More human interaction. More things that feel like they were made by a person who gave a damn.

I don’t think I’m alone in that.

The industry is asking “what can we do with AI?” That’s the wrong question.

The right question is the one it’s been avoiding:
What do people actually value, and are we still providing it?

Before you scale — my series on why startups struggle to scale — has moved to LinkedIn, where it’s finding the right audience.

If you’re building something and want to follow that, you’ll find it here.

But this newsletter you are reading-The Clarity Lens -was always about something broader. The thinking behind the thinking. And I have too many thoughts that don’t fit a how to scale-startup newsletter.

So this is where they’ll live. I hope you continue to follow me here. Otherwise, just hit the unsubscribe button at the bottom. No hard feelings, whatsoever. :)

Starting with something that’s been bothering me for weeks.

Every week there’s a new prophecy. AI will change everything. Vibecoding will redefine work. Jobs will disappear. Jobs will reappear. We’ll all be faster, freer, more creative.

Nobody knows.

Nobody has ever known.

We have a long history of being wrong about how technology reshapes society, paired with an impressive ability to sound confident while doing it. At this point, the certainty is almost comical.

So let’s pause the theater. The future will happen whether we narrate it or not.

My LinkedIn feed has been full of it lately. Founders shipping products in a weekend. Developers building tools in hours that used to take weeks. The energy is real and I understand it — I’ve vibecoded myself, and the first time something just worked, I felt it too. The speed is genuinely remarkable.

But then I stopped and asked myself: what am I actually building? And more importantly — why?

That pause is what this article is about.

Vibecoding is speed, not progress

Vibecoding is a good example of where we are right now — a moment where the ability to execute has raced so far ahead of the ability to think that we’ve stopped noticing the gap.

What I mostly see is not a breakthrough in innovation. It’s a breakthrough in execution speed.

We can now build things extremely fast. Apps, tools, workflows, wrappers on top of wrappers. That’s impressive. It’s also largely beside the point.

Most vibecoded products help us do what we were already doing. Shop faster. Compare more options. Consume more efficiently. Produce more content.

This isn’t innovation. It’s acceleration inside the same frame. In a frame with high attention deficit.

We are getting very good at solving problems that probably shouldn’t exist in the first place.

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Judgment was always important. Now it’s everything

Even when building things was hard, judgment mattered.

Choosing the right problem. Knowing what not to build. Understanding second-order effects. Resisting the obvious solution.

Now building is cheap. Sometimes trivial.

Which means judgment is no longer a nice-to-have. It’s the scarce resource.

In a world where anyone can generate code, text, products, and ideas on demand, the differentiator is not capability. It’s discernment. Taste. Style. The ability to say no.

And yet this is the one skill we seem least interested in developing.

First principles have been replaced by vibes

I was trained in physics. You didn’t start by solving the problem. You started by interrogating it.

Why does this problem exist? What assumptions created it? What happens if those assumptions are wrong?

Only then did you touch the math.

Most modern tech discourse skips this entirely.

Instead, we ask how fast we can build, how cheap we can ship, how impressive the demo looks. Vibecoding is perfect for this mindset. It makes it easier than ever to move without thinking.

Motion is mistaken for progress. Output for insight.

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Save us for what, exactly?

I keep hearing about AI freeing up our time.

For what?

So a robot can do my laundry while I scroll more efficiently. So thousands lose their jobs while we celebrate frictionless consumption. So we can generate even more content that nobody asked for.

We talk about time saved as if time automatically turns into meaning. It doesn’t.

In a world already drowning in distraction, free time without judgment just gets filled with more noise.

The real divide isn’t technical

The future won’t be shaped by the fastest builders or the loudest futurists.

It will be shaped by a small minority of people who still have judgment.

People who can tell the difference between a real problem and a manufactured one. People who can ignore most options instead of celebrating infinite choice. People who can sit with uncertainty instead of filling it with output.

Everyone else will be busy vibecoding solutions to things that don’t matter.

I don’t want predictions. I want standards.

I don’t care how the world will look in ten years.

What I care about is whether we’re willing to develop judgment in a time that actively discourages it.

Less future cosplay. Less hype. Less speed for the sake of speed.

More first-principles thinking. More restraint. More courage to say, “This is pointless.”

That would be real progress.

Before you scale — my series on why startups struggle to scale — has moved to LinkedIn, where it’s finding the right audience.

If you’re building something and want to follow that, you’ll find it here.

“We just need more sales now.
But we don’t have enough money to hire more people or market properly.
Marketing has become insanely expensive.
That’s our problem right now.”

It sounds reasonable.
Most of the time, it is reasonable.

Then I ask a simple question.

If I gave you two experienced salespeople for free tomorrow.
You onboard them. They start next week.

What do you expect your growth to look like four months from now?

There’s usually a pause.

Some say pipeline would go up.
Some say “it depends.”
Very few can answer with confidence.

And that pause is the signal.

If adding proven sales capacity doesn’t give you a clear, predictable outcome, your real problem isn’t lack of salespeople.

It’s that what you’re selling, who you’re selling to, or how you’re selling isn’t ready to be repeated yet.

Many teams use hiring as a way to find out what works.
But hiring doesn’t create clarity. It locks in cost.

The same thing happens with marketing.

When customer acquisition starts to feel expensive, the instinct is to push harder. Spend more. Increase volume. Show momentum.

But spending doesn’t make demand clearer.
It often hides the signal you actually need to see.

What usually sits underneath these situations is not an execution problem.
It’s unresolved questions like:

• Which customers would buy this without being pushed?

• What do they value enough to come back for?

• What breaks when you try to scale what you’re doing today?

Until those questions are answered, more sales capacity or more marketing just turns uncertainty into permanent cost.

This is not about slowing down.
And it’s not about removing risk.

Startups are risky by nature.

It’s about keeping learning fast, while being careful with decisions that are hard to undo.

Move fast where learning is cheap.
Commit later where mistakes are expensive.

That’s when growth starts to become predictable.

You close the first deals yourself.
Customers respond. Revenue comes in.
It feels like sales is “working”.

So you make what looks like a rational decision:
to grow faster, you hire a sales executive.

You hire someone with a strong track record.
You onboard them carefully.
You explain which customer types to pursue.
You share the storyline that has worked for you.

Then you wait.

Three months pass.
Six months pass.

The pipeline is thin.
Deals don’t close.
Costs have doubled, but growth hasn’t.

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At this point, founders usually start questioning execution.

Maybe the salesperson isn’t the right one.
Maybe you need to join more meetings.
After all, when you show up, deals seem to move.

This is where most teams misdiagnose the problem.

What usually went wrong is not the hire.
And it’s not the effort.

The real issue is this:
you didn’t scale a PROVEN sales funnel. You tried to copy founder-led sales.

Early sales often work because of things that are hard to see and impossible to transfer: your credibility, your authority, your flexibility in conversations, your ability to adapt the story on the fly.

None of that is written down.
None of it is repeatable.
None of it survives when you remove yourself.

So when you hire a salesperson, they’re left with:
an unclear customer definition,
a generic value story,
and no solid reason why customers say yes without you in the room.

When deals stall, joining more meetings feels like the fix.
In reality, your presence is compensating for missing clarity.

That’s why costs go up while growth stays flat.

Hiring didn’t scale sales.
It scaled uncertainty.

This is one example of a broader pattern I see again and again:
Companies commit resources before they know what is safe to scale.

Hiring, building features, and spending on growth all become ways to act before the underlying questions are resolved.

The work that actually unlocks growth comes before the hire:
understanding which part of your value closes deals,
for whom,
and why it works even when you’re not there.

Until that’s clear, adding people doesn’t increase momentum.
It just makes the confusion more expensive.

Before funding: forced clarity

Before funding, founding teams are in exploration mode. They are trying to answer a small number of very concrete questions.

• Who sees the value in our solution?

• Which problem is urgent enough that someone will actually pay for it?

• What version of the product gets us there fastest?

Money is tight. Many teams are bootstrapped or working on the side. That makes them careful. Every decision costs something. Every wrong turn hurts.

Because of this, judgment is sharp. Teams test quickly. They stop when something does not work. Learning is fast because mistakes are cheap.

After funding: pressure to move

Then funding lands. Everyone is happy.

The goal quietly changes. Exploration gives way to momentum. There is pressure to hire, to spend, to show progress, and to look like a real company.

Plans harden. Roles get defined. Roadmaps get locked.

Money removes pain, but it also removes freedom.

When changing direction stops being easy

Before funding, changing direction is simple.
If a buyer does not respond, you stop.
If a feature does not matter, you drop it.

After funding, changing direction affects people.

If you hire someone to run a growth channel and it does not work, stopping now means questioning the hire. Someone’s work is suddenly on the line.

So the question changes.
Not “Is this working?”
But “How do we make this work?”

The same thing happens with roadmaps. Once a direction is announced and work is underway, changing course means admitting the plan was wrong. So teams wait. They keep going a bit longer.

Why it gets expensive fast

Hiring also makes learning slower.

Four engineers need alignment. Changes ripple through systems. Small tests turn into big projects.

What used to take a day now takes weeks.

The same goes for tools, agencies, and infrastructure. Even when something looks wrong, stopping feels like wasting money. So spending continues.

Burn goes up. Learning goes down.

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The real mistake

Before funding, mistakes are easy to undo.
After funding, mistakes turn into commitments.

By the time it is obvious something is wrong, changing direction feels harder than continuing. Even when continuing makes no sense.

This is why many startups fail while doing everything they were told to do.

This is not an execution problem.

It is a judgment problem.

Take the same 100 dollars. Spend it on five different things, and you will get five very different results.

One choice teaches you something useful.
Another just burns money.
A third locks you into the wrong direction.

The difference is not effort.
It is which bets you choose to make.

And most of those bets are placed right after funding, when decisions start to lock in.

That moment decides more than most people realize.

I published this article in Norwegian online startup publication Shifter on monday 12 january. Here I am sharing with you an English translation of the same.

When a startup closes its first funding round, things should get easier. More resources. More time. More opportunities.
But often, the opposite happens. Activity ramps up. Complexity grows. And the fundamental questions—who are we really here for, what problem are we solving, why are we the only ones who can do it—get pushed further away.

The Activity Trap

Ask a founder six months after funding: “What problem are you solving, and why are you the only ones who can solve it this way?”
The answer is often harder to articulate than before the money came in.

The team has grown from five to fifteen. Three new product features are in development. Marketing is testing two brand new channels. Sales is talking to anyone who will listen. Everyone is busy with work that feels important.

But the truth: Most of these initiatives won’t move the needle. Not because they’re bad ideas, but because they don’t address the problem customers actually care about.

In most startups, 90% of growth comes from 10% of the actions. But after funding, companies start doing more of everything—instead of figuring out which 10% actually delivers customer value.

42% Fail for One Reason

CB Insights analyzed over 100 failed startups:

• 42%: No market need

• 29%: Ran out of money (because they spent it on the wrong things)

• 23%: Not the right team

The biggest reason companies fail is not that they lack capital or technology, but that they don’t solve a problem customers care about.
And yet, after funding, it’s exactly this work—systematically understanding what customers care about—that gets pushed aside.

The Gap No One Fills

This is the founder’s responsibility. Not the investor’s.

Investors invest. They provide capital, open doors, share experience. But the day-to-day work of finding customer value? That’s the founder’s job.

The problem is, most founders haven’t done this before.

They’ve built products. Sold. Developed. Marketed. In organizations with established processes and customers. But the systematic work of testing what creates customer value—in a way that lets you know what to stop and what to double down on—they lack experience with that.

And the VC model doesn’t fill this gap. An investor with 15-20 companies has 2-3 hours per month per company. Enough to track metrics and give strategic advice. Not enough to sit close with the founder every week and help with the really hard part: Finding the few actions that create value, and having the courage to stop the rest.

So you get a gap: The founder has the responsibility, but not the tools. Investors may have the experience, but not the capacity.

The result? Activity without precision.

Testing vs. Hoping

Most startups replace testing with assumptions. They build first, measure later. They have opinions about what works, but no system for testing it.

Real hypothesis-driven testing looks like this:
“We believe that if we do A, then B will happen.”

Not vague hopes. Specific expectations:

• “If we change onboarding to three steps, 60% more users will complete it within 48 hours.”

• “If we solve X problem, churn will drop by 20% in a month.”

And then: How can we test this hypothesis in the shortest possible time?

Not “let’s build the whole solution.” But: What’s the smallest test that gives us a signal?

A landing page. A manual process. A meeting with five customers where you show wireframes and ask, “If this existed, would you pay for it?”

The point isn’t to build faster. The point is to learn faster—so that when you do build, you’re building what customers care about.

But this isn’t intuitive. It takes discipline, system, and something scary: Willingness to be wrong. Because 90% of the hypotheses you test won’t deliver the results you want. And that’s good, because you found out without wasting time and resources.

In reality, when the capital comes, it feels wrong to pause and test. It feels like slowing down. So instead of testing, founders build. And hope.

One Year Later

One year later: The company has burned through millions, hired dozens, built a lot. But they’ve moved further from customer value, not closer.

This isn’t a failure of effort. It’s a failure of focus.

The Choice

Most startups use funding to multiply activity.
The best use it to multiply their understanding of customer value.

Investors can provide capital, open doors, share experience. But they can’t do the daily work of keeping customer value at the center.

That work determines whether the capital builds something customers care about—or just multiplies what doesn’t work.

I took two weeks off over Christmas—first time in years. And I caught myself about to make the exact mistake I spend my time warning founders about.

A friend told me I should start a podcast. Another suggested short YouTube videos. They both like what I write, and hearing that felt good. My brain immediately started planning: format ideas, equipment I’d need, how to repurpose newsletter content.

Then I stopped. Wait. What problem am I actually solving here?

The real answer: I was avoiding the hard work.

There’s a law in physics called inertia.
Newton’s first law: An object in motion stays in motion, an object at rest stays at rest—unless acted upon by an external force.

We usually focus on the “stays at rest” part. That’s not the dangerous one.

The dangerous part is “stays in motion.” We keep moving in the same direction even when we should stop. We drift toward what feels comfortable, even when we convince ourselves we’re doing something new.

I’m a product person who loves writing. Building stuff comes naturally to me. Creating content comes naturally.
Podcasts and YouTube videos sound like strategic growth moves. But the work I actually need to be doing right now? Cold reaching potential clients. Having uncomfortable conversations. Finding out where they’re stuck and what’s keeping them there.

That work has friction. So I was about to solve a distribution problem by... creating more content.

Sound familiar?

I see this pattern everywhere:

Product people keep building features when they should be talking to customers. Communication experts keep polishing their messaging when they should be testing it in the market. Founders create elaborate content strategies when they should be doing uncomfortable outreach.

We all have our inertia zones—the work that feels productive but isn’t actually moving things forward.

The work that comes with less friction. The work we’re good at. The work that feels safe.

Mine is creating. Yours might be something else. But we all have one.

So here’s the question for 2026:

What’s your natural inertia zone?

Where are you keeping yourself busy with comfortable work instead of doing the necessary work?

Are you building when you should be selling? Creating when you should be testing? Polishing when you should be shipping?

I caught myself this time. The question is:

what are you about to convince yourself is “strategic” that’s actually just comfortable?

We are living in interesting times. Unsettling, fast-moving, very confusing. But also full of possibility. Over a long period of reflection, one idea has become clearer to me than ever.

I believe the purpose of life is to make the most of the particular bundle of consciousness each of us is. Not in isolation, but in collaboration with everything around us. Other people. Circumstances. Reality as it unfolds.

One can go very far philosophically here. What is real. What is subjective. How much is constructed by subjective observation. I find those questions fascinating, but they do not help much when you are trying to live a good everyday life.

What does help, at least for me, is something simpler.

First, to understand what you are made of. What lives inside you. Your strengths, limits, patterns, fears, values, curiosity, talent.

Second, to work with that material as honestly and fully as possible. To use it with care and for maximum leverage, for yourself and for the people and systems you are part of.

These two things are not sequential. They happen in parallel, throughout life.

You learn who you are by acting. You act differently as you learn.

I feel blessed because, both consciously and unconsciously, I have put myself in situations that forced this kind of growth. Not all of them were chosen freely. Many were hard. Some were painful. Some felt unfair at the time. But they all taught me something essential.

Struggle has been my most effective teacher. So has serendipity. Both belong in the same sentence.

I am grateful that I chose my partner wisely. That I have been surrounded by family and friends who care, even when life was or is messy. I chose to have one child, and that choice gave me the energy to be mentally present. That presence has shaped our relationship in ways I value deeply.

I am also aware that I live with privileges that matter.
I do not worry about food, shelter, or security. Time to read. Time to reflect. Time to think thoughts that are not immediately useful, but deeply important for my development as a human being.

I have no idea what the future will bring. What I do feel is that I am doing my best, at any given time, to stay curious and to understand both my own qualities and the circumstances I am in. That gives me a sense of preparedness, even in uncertainty.

To those of you who follow my writing. Those I know well, and those I do not know at all. Thank you. Your attention matters more than you might think.

My wish for all of us is simple.
A discovery mindset. Enough space to reflect. And the courage to choose wisely, again and again.

Some books have mattered more than others this year.

Searching for Rain in the Monsoon made me think deeply. So did Big Magic, for its insistence on creative living without fear, and on taking curiosity seriously without turning it into pressure.

After a long time, I also found my way back to fiction. Over the course of a few months, I read all seven of Elizabeth Strout’s books. I find her writing quiet and precise. She writes about ordinary lives in a way that feels deeply human.

Reading her reminded me why language and narrative matter. I aspire to write with that kind of honesty and precision over the course of my life.

I wish you all a merry Christmas and a very happy new year.

“We invest in the founder and the team. We trust them to figure it out. We don’t want to tell them what to do.”

At a principle level, this is right.
Founders live closest to the problem.
Context matters.
Advice given from the outside is often wrong.
And micromanagement destroys ownership.
So yes. Trust matters.

But there is something we talk far less about: what this kind of trust actually does to founder behaviour over time.

What trust produces in practice

When founders are trusted to “figure it out”, they usually do exactly what they are best at.

They solve.
They build.
They dive deeper.
They handle complexity.
They stay busy.

This often looks like competence. And often, it is.

But there is a risk embedded in this dynamic.

Founders who are trusted to figure things out rarely stop to ask whether they are still solving the right problem in the right way. Not because they don’t care. But because they are inside the problem every day, and momentum becomes hard to question from within.

This is how teams disappear into complexity without noticing.

The rabbit-hole trap

I’ve seen this pattern repeatedly, both in startups and in innovation initiatives inside larger organisations.

Progress looks real. Work is happening. Things are moving. Slowly.
Yet over time, fewer people can clearly explain why this is still the right direction.

At a detailed level, everything makes sense.
At a strategic level, clarity slowly disappears.

Why advice doesn’t fix this

The usual response is advice.
More ideas.
More suggestions.
More opinions from people who mean well.

Ironically, this often makes things worse.

Advice adds pressure.
It adds activity.
It increases noise.
It pushes founders to react instead of reflect.

There’s another reason advice rarely helps at this stage. Going back or reconsidering your entire approach is rarely seen as a real option. Once movement has started, both founders and advisors tend to assume the direction is broadly right. So the company keeps moving, even if the course is slightly off.

When things eventually get difficult, the response is rarely to rethink direction.
Instead, teams start cutting.
Cutting initiatives. Cutting scope. Cutting cost.

That’s often how companies optimise their way into a dead end.

I’ve lived this myself. Not in theory, but in practice.
Between advice and letting you work things out on your own, something important is missing.

What’s missing is not control. It’s judgment support.

Good support is not about telling founders what to do.
And it’s not about stepping away entirely.

It’s about helping them step out of the problem to question their own momentum.

The most valuable intervention is often a question, not a suggestion.

• What are we assuming to be true right now that we haven’t actually checked in a while?
• Which problem are we solving out of habit rather than conviction?
• What are we still working on mainly because we already invested time or money in it?
• If we were forced to simplify our strategy tomorrow, what would we immediately stop doing?

These questions don’t tell founders what to do.
They don’t remove founder autonomy.
They strengthen it.

Trust without challenge creates blind spots

There is a subtle tension here.

Trust is necessary for founders to operate.
Challenge is necessary for founders to course-correct.

When trust exists without structured challenge, blind spots grow quietly.
When challenge exists without trust, founders shut down.

The balance is fragile, and it’s rarely discussed explicitly. But this balance is exactly where drift either accelerates or slows.

I am in the process pf building my reader base and therefore all shares are very much appreciated.

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Previous posts

If you missed my previous posts in this series, here they are:

• Strategy is not a group exercise

• Founders don’t fail from lack of advice.

• Fix your roof while the sun is still shining

• Why your company needs one sentence of clarity