The result was 653 commits, ~144K lines of code across 8 projects published on GitHub, and a series of articles documenting each one. If you’ve been following along, you’ve already read the post-mortems. If you haven’t, here’s the index:

The articles

• Vibe Code: I built a small app 100% with GLM 4.7 (TV Clipboard)
• Vibe Code: Which LLM is the BEST?? Let’s get real
• Vibe Code: I built a Markdown editor from scratch with Claude Code (FrankMD) PART 1
• Vibe Code: I built a Markdown editor from scratch with Claude Code (FrankMD) PART 2
• RANT: Did AI kill programmers?
• Vibe Code: From Zero to Production in 6 DAYS - The M.Akita Chronicles
• From Zero to Post-Production in 1 Week - How to Use AI on Real Projects
• Vibe Code: I built a Mega clone in Rails in 1 day for my Home Server
• Vibe Code: I built an Intelligent Image Indexer with AI in 2 days - Frank Sherlock
• RANT: Did Akita open his legs to AI??
• ai-jail: Sandbox for AI Agents
• Software Is Never ‘Done’ - 4 Projects, the Life After Deploy
• I Built a Data Mining System for My Influencer Girlfriend
• My First Vibe Code Failure and How I Fixed It - Frank Yomik

The projects

All of this happened between January 27 and March 5, 2026.

I’m not going to repeat the technical details of every project. Each post-mortem above already covered that. What I want to discuss here is the consequence.

What these 37 days showed me

Projects that used to take weeks or months for an experienced developer now take days. A complete Markdown editor in 5 days. A Mega clone in 1 day. A data mining system with 40+ bot tools in 3 days. An image indexer with vision AI in 2 days.

And I’m not talking about throwaway prototypes. These projects are in production. They have tests. They have automated deployments. It’s real software built with real engineering practices, just at a speed that was unthinkable before.

This speed isn’t unique to me. Cloudflare just demonstrated something similar. In a recent post, they describe how an engineer reimplemented the Next.js API surface on top of Vite in a week, using Claude as the main tool. US$ 1,100 in API tokens, more than 800 sessions, 1,700 unit tests, 380 E2E tests, builds 4.4x faster than the original Next.js. Controversies aside about whether it’s a “complete” reimplementation or not, the central point is real: software that used to require teams and months can now be built by one person in days.

And that changes everything for anyone wanting to start a company.

The death of the easy startup

For years, the classic startup model worked like this: someone has an idea, puts together a small team, builds an MVP in 3-6 months, raises seed money, and tries to scale. The barrier to entry was development cost. Programmers are expensive, development is slow, and the first to market has the advantage.

That model is breaking.

If I can build a working Mega clone in 1 day, what’s a “cloud storage” startup worth? If Cloudflare reimplements the Next.js core in 1 week with one engineer and US$ 1,100 in tokens, what’s the real moat of a platform like Vercel? The “social listening” SaaS that charges R$ 500/month is competing with something I built in 3 days as a side project.

Every entrepreneur who used to show up describing their idea as “it’s like Uber, but for…” or “it’s like Airbnb, except…” or “another social network, but with…” — those people need to stop and rethink. When any competent developer with access to Claude Code or GPT Codex can replicate your MVP in a week, your idea isn’t worth anything anymore. Execution got too cheap.

I’m not exaggerating. In my 37 days, I built things I wouldn’t even attempt in 6 months before. Small CRMs, ecommerces, content managers, productivity tools, data mining apps, processing pipelines — all of that became commodity. The code itself is no longer the differentiator.

So what is the differentiator?

This is where most vibe coding enthusiasts miss the point. To illustrate, let me use my own project as an example.

Frank Yomik translates manga pages from Japanese to English in near real-time. The full pipeline (balloon detection, OCR, translation, rendering) works. But the most important component of the system isn’t any code I wrote. It’s the ogkalu/comic-text-and-bubble-detector model, an RT-DETR-v2 trained on ~11,000 labeled comic images.

I didn’t train that model. I couldn’t easily train that model. Collecting 11,000 diverse comic images, manually labeling the speech balloons in each one (or generating labels with some semi-automated pipeline, which isn’t trivial either), configuring the training, and running it on the necessary hardware — that’s work of a different nature. It’s work that vibe coding doesn’t solve.

And that’s the case of a relatively small model. An object detector can be trained with a few hundred to a few thousand labeled images on a single GPU in hours. Studies show useful results are possible with 100-350 images for specific domains, but robust real-world detectors usually need thousands. The cost is low, in the hundreds of dollars range.

Now look at what happens when we scale up to bigger models.

The numbers that matter

GPT-4 cost more than US$ 100 million to train, according to Sam Altman himself. Stanford estimated the compute cost of Google’s Gemini Ultra at US$ 191 million. Meta’s Llama 3 consumed 39.3 million GPU-hours on H100s, and Meta built two clusters of 24,576 GPUs each to make it possible — and by the end of 2024 it planned to have 350,000 H100s in its infrastructure.

These costs are accelerating. According to Epoch AI, the cost of hardware and energy to train frontier models grows by 2.4x per year since 2016. If that trend continues, the largest training runs will cost more than US$ 1 billion before the end of 2027. Dario Amodei, Anthropic’s CEO, has said frontier developers are probably spending close to a billion per training run now, with US$ 10 billion training runs expected within two years.

And the hardware? An H100 GPU costs US$ 25,000-40,000 per unit. A server with 8 GPUs runs between US$ 200,000 and US$ 400,000. The HBM memory those GPUs use is at capacity — SK Hynix, Samsung and Micron have already announced ~20% price increases for 2026. NVIDIA consumes more than 60% of the global HBM production. It’s a structural bottleneck, not a temporary one.

In terms of energy: global data centers consumed ~415 TWh of electricity in 2024, according to the IEA, about 1.5% of the world’s electricity. The projection is ~945 TWh by 2030. New data centers are being built with capacities of 100 MW to 1 GW each.

And the big tech investments reflect that. In 2025, the aggregate capex of Amazon ($125B), Google ($91B), Microsoft ($80B) and Meta ($71B) crossed US$ 400 billion, a 62% increase over 2024. Goldman Sachs projects more than US$ 500 billion in 2026.

These numbers aren’t meant to scare. They’re meant to put the real entry barrier in context.

The new barrier: exclusive data and training capacity

If software got cheap to produce, the competitive differentiator migrated. The question stopped being “who writes code the fastest?” and became “who has access to data nobody else has, and knows how to turn that data into useful models?”

DeepSeek-V3 announced that its training cost US$ 5.5 million in compute. The press celebrated the “cheap Chinese model.” But The Register reported that the acquisition cost of the 256 GPU servers used was over US$ 51 million — and that excludes R&D, data acquisition, data cleaning, and all the failed training runs before the final successful one. The real cost of developing the capability is one or two orders of magnitude above the marginal cost of the final successful training run.

That’s why we only see large companies producing frontier models. Meta, Alibaba, Google, Amazon, Microsoft, Anthropic — companies investing tens of billions in hardware and energy. A garage startup can’t compete on this dimension.

But the question goes beyond frontier models. Even smaller specialized models require something you can’t buy: high-quality proprietary data.

Llama 3 was trained on 15 trillion tokens. Epoch AI has documented that we’re approaching the limits of human-generated text data on the internet. Public data is being exhausted. Whoever has exclusive data — medical, financial, industrial, logistics, sensor, user behavior — has something that vibe coding can’t replicate.

And even those who train specialized models with proprietary data face a problem: the advantage is temporary. Another competitor can collect similar data and train a competing model in months. The differentiator needs to be continuously fed: more data, better curation, more efficient training pipelines, access to hardware that’s increasingly scarce and expensive.

The picture

If you’re thinking about starting a company, the question that matters has changed.

Before it was: “can I build this software?” Now the answer is almost always yes, fast and cheap.

The question now is: “do I have exclusive data nobody else has, and do I know how to turn that data into something useful that’s hard to replicate?”

If the answer is no, any competitor with Claude Code replicates your product in days. And then another one shows up. And another. The race to the bottom on price is immediate when the cost of building is close to zero.

If the answer is yes, you have a real moat — but a temporary one. Competing models trained on similar data can show up in months. Your differentiator needs to be continuously fed.

The era of easy startups is over. Not because building software got harder — it got way easier. But precisely because of that: when everyone can build the same thing in a week, the competitive advantage has to come from somewhere else. And that “somewhere else” requires capital and infrastructure that are orders of magnitude more expensive than writing code.

The garage still works. But what comes out of it can no longer be “an app.”

If you’ve been off traveling around Jupiter for the last few years, you may not have heard about a strand of production that has caused a lot of controversy and already established itself as viable: home 3D printing. 3D printing, or additive manufacturing instead of the subtractive production we use today, has existed for about 30 years. But the market stayed in the hands of giants like 3D Systems and Stratasys, and only for industrial printers that ran past 100 thousand dollars. They were the IBM of the 70s.

And just like the desktop revolution that Microsoft, Compaq, Apple, and Dell helped found, now it’s the turn of startups like MakerBot and Form Labs to step in. Form Labs was one of the most successful projects in its category on Kickstarter. They bring home 3D printers, under 2 thousand dollars, within reach of hobbyists and, down the road, the ordinary consumer.

“But 3D printing is just for nerds.” That’s exactly how “a personal computer in every home” sounded in the late 70s. That’s the premise of the documentary Print the Legend, produced and released by Netflix on September 26, 2014.

I’ll admit it makes me a little nervous that the “3D revolution” already gets a documentary without having reached the level an Apple II had by the mid-80s. Then again, the film doesn’t set out to explain the manufacturing process or the various 3D printing techniques, lasers, and so on. It explores what happens when the garage-startup idealism turns real and hits the level of an early-80s Apple.

The mess is obvious in the interviews with former MakerBot employees, about how they now hate their CEO and co-founder, Bre Pettis. The original garage vision, of a company built around open source and open hardware, suddenly takes on investment and leverage from the usual Brad Felds. And the company starts ballooning from a 12-person garage into a 200-, 600-, and more-person corporation.

Friends turn into enemies (and by the way, friends always turn into the worst enemies), people leave disillusioned, traumatized, disappointed, and cruelty and authoritarianism become routine. At least that’s what the ones who left always say.

How much of this is true? We’ll never know. The truth always has three versions: the one I tell, the one you tell, and the one that actually happened.

People start startups, usually, to be the anti-system, the rebels, the ones who don’t fit in, the ones who want to do things differently and change the game. This level of naive idealism is even “cute,” and it’s necessary: if you don’t believe the thing can happen, it really won’t. Thinking that way is a requirement, up to a point.

I call it “naive” for a reason. In the very rare cases like MakerBot’s (and maybe Form Labs’ down the road, since it’s walking the same path after landing its fat Series A), when you genuinely succeed at changing the system and flipping the game, from that moment on you become the new system, the new game, the new target. Now you’re the one to be fought and torn down.

Apple was the counter-movement to IBM in the 80s. It worked so well that Apple itself became the new system. In the 90s we figured Microsoft would be IBM’s successor, but in the 21st century we found out the one who took on that role was Apple.

It falls to a new garage startup to start another game from scratch. The most interesting part of “Print the Legend” is exactly how it shows that drama, from the beginning until now, of a startup walking that curse. How Bre Pettis went from leader of an open maker community to “traitor” of the movement, and how little MakerBot reached success: it was bought by Stratasys, the second largest in the market, and with that managed to grow the business.

Without giving away too much, someone near the end mentions that founders, entrepreneurs, and successful CEOs always talk about the “sacrifice” it took to get where they are. Most people picture sacrifice as working long hours, staying away from family for long stretches, or grinding through the complications of the process.

But the sacrifice they may be talking about is a different one: breaking your own identity, betraying your own principles, and crossing the lines you swore you’d never cross. And the rare big success stories, the Microsofts, the Apples, the IBMs, and now maybe the Stratasyses, demand that this happen.

The cycle will start over. Soon a new rebel garage startup shows up, plays the same game, and shortly after becomes the new system to be beaten. That’s the cycle of successful startups, and those are exactly the rules of the game of great “success.”

Opening photo: fb.com/printthelegend

I wrote this article in English right after the last episode of the series aired on TV, in October 2013. A few months have passed, so I imagine everyone has had the chance to watch the whole thing by now. For me, this was one of the best TV dramas of the last few decades. It comes along with The Sopranos.

I won’t review every detail of the series, since there are plenty of other blogs doing that with more competency than I would. I’ll assume you’ve watched the series, and I’m going to spoil parts of the finale, so go watch it before you keep reading.

People love the series, and they root for Heisenberg even knowing he commits plenty of crimes. Personally, I think what grabs people is the story the author is telling, far more than the crimes themselves.

This is the story of a very, very successful startup, literally the classic “garage startup”, except in this case inside a van. Walter and Jesse start with an idea, a few bucks, and a lot of work, cooking meth in the middle of the desert. Even with almost no money and no resources, Walt is adamant about the quality of the product, and that’s a mark of great entrepreneurs. Jesse is the metaphor for the wannabe entrepreneur, a dropout trying to hit the jackpot without experience and without thinking ahead.

For me, the whole idea of Breaking Bad revolves around entrepreneurship. Walt is not only a seasoned chemistry teacher, with real knowledge and talent; he’s also a great businessman, and he proved it many times. One example is understanding that, to score big, growing organically by selling on the streets Jesse’s way just isn’t enough.

Then come Gus Fring and Los Pollos Hermanos, with the explosion in distribution channels. That’s how you scale a business. Gus is Walt’s “angel investor”, and once the money is in, the pressure only goes up. Jesse quickly gets fed up with working so hard in the lab, like every young idealist who doesn’t yet understand what real hard work is. Walt, on the other hand, is focused on scoring big at any cost.

The show also demonstrates how to negotiate with partners you don’t particularly like or trust, in a very demanding game. Once you get the opportunity, you don’t have to do all the dirty work with your own hands: make big dog eat big dog, turn the Cartel against Gus. And if everything goes wrong, you can always blow up the nursing home.

In the process, what we see is Jesse growing up. Walt was a great mentor, and their adventures made him stronger. The finale is also about Jesse understanding what he really is and maybe becoming a better person, in terms of self-awareness. Now he’s ready to commit and sacrifice, instead of being just an idealist.

In the real world, you have to commit and make sacrifices. There will be collateral damage, because you can’t make an omelet without breaking some eggs. Nothing worthwhile is easy, and the process is never going to be pretty.

The finale is great because Walt finally admits it: when you’re building an enterprise, you do it for yourself. Not for your family, not for your friends, not for the good of mankind. It’s for you and you alone. If you’re not doing it for yourself, you’re doing it wrong, and that’s the most basic core concept of entrepreneurship.

Benefiting (or hurting) others is always a side effect of actions you take with the single goal of benefiting yourself. As long as you’re not doing it for yourself, you’ll always use others as the easy way out, the excuse. “I screwed up, but I did it with good intentions.” Good intentions don’t matter, results do. If you do everything for yourself, the responsibility is always your own. No excuses.

Being successful is much more than glory and fame. As Breaking Bad shows, when your business grows, the competition gets harsher, the attacks get more violent, and everybody wants a piece of your pie. Defending your own territory is up to you, and you can’t always do it alone.

Sometimes you need good mercenaries and always a good lawyer, like Mike Ehrmantraut and Saul Goodman, to cover your tracks. It’s the cold-blooded partners who handle the deals you can’t touch all the time.

Marie represents the worst and most degrading thing in the world: mediocre normality. People so entrenched in the status quo, so bored by their own existence, that they’re mortally jealous of anyone who won’t follow their tiny version of “truth”, the path of “being normal”. People full of prejudice and full of themselves, who judge everything and everyone all the time. The best thing to do is stay as far away from that rotten kind as possible.

Skyler starts out the same as Marie, but being so close to Walt, she fights against herself. She suffers to get out of the box, to get used to taking risks, to think differently. She goes through all the common stages of transition: denial, anger, bargaining, depression, and acceptance. In the end, we see that she finally understood.

Walt was not the villain, he was a man doing what he does best. Someone who values his own work so much that he won’t let anything or anyone stop him. That’s “drive”, and it’s the level of drive anyone who wants to be an entrepreneur needs to have. Reaching the goal, whatever it takes.

Walt is the ultimate entrepreneur role model, really a lot like Tony Soprano. The Mafia is the best MBA in the world.

Recently a blog article kicked up some buzz. Titled I wanted to work at Apple really bad, and now not so much, it’s a vent from the author himself. The summary is simple: in his opinion, his boss treated him and his team badly, to the point where he dropped everything and walked out.

The more generic discussions ran along the lines of how Apple must really be a horrible place to work, and that the upper ranks still practice the legendary “Steve Jobs style” of kicking people to squeeze out results. Some even went so far as to say “the only way out is to start your own thing, chase your own dreams without a boss like that stepping on you.”

And that’s the point of this article. With the current frenzy around startups, this is an attitude I see more and more often.

Let me put the common complaint about bosses in perspective. No boss you’ve ever run into, even the worst of the worst, comes close to Henry Clay Frick, who ran the operations of legendary Andrew Carnegie’s steel mills. Working conditions in the late 19th century were terrible, and maybe not even the worst conditions today match the worst of that era.

Several of the great industrial magnates of the period, including Carnegie, Rockefeller, Vanderbilt, and many others, exploited workers to the edge of misery. One example of how far it went was the famous Homestead Strike. The result? Seven workers killed and eleven wounded.

Believe me, you would not want someone like Frick as your boss.

That was an extreme example, and it doesn’t mean there aren’t bad bosses today. I’ll keep the context to the world of tech startups we’re part of, and leave out public service, the military, and other areas outside that frame.

The big difference between today and Carnegie’s time is that today there are options. Back then, either you put up with terrible conditions and terrible pay, or you lived in misery with no job at all. Today any good professional has plenty of alternatives. People come and go from companies hundreds of times a day, across hundreds of companies, and you only have to look at the proliferation of job and recruiting sites to see it.

If you’re a student or a fresh graduate, understand a hard truth: you are just like the hundreds of people who graduated alongside you and enter the market every single day. The first job is always hard. And not just the first: the second, the third, and probably the ones after that too. What you “think” you’re capable of is worth nothing until you have a run of concrete results to prove it. That’s what we call a résumé.

I’ve heard plenty of young people say things like “I need to change jobs, I’m not learning anything here anymore.” If you’ve been at the same company for ten years, it’s probably past time. In the first or second year? That’s nonsense. The company has plenty to teach you; the problem is you don’t want to learn.

A programmer, for instance, doesn’t have “programming” as their only job. In August 2013 I wrote that the hardest thing for a Software Engineer is to grasp that software problems often have no solution in software. Learning to negotiate, communicating so others actually understand, managing expectations, working in teams, convincing others that your ideas are good: all of that is part of the job.

In other words, a lot of things that have nothing to do with code. And this holds for any profession, whether you’re a designer, a writer, a cook, or a race car driver. Everyone has to learn and practice these skills to grow.

There are catchphrases repeated thoughtlessly, like “it’s not worth living someone else’s dream as a company employee.” If that’s the thinking, better to resign. A company isn’t a charity: it exists to turn a profit, not to babysit employees. And unless we’re talking about a non-profit, no employee is there as an unpaid volunteer.

Between company and employee there’s a work contract. Both agreed to the terms. If you don’t agree, don’t accept it; if you accepted, honor it; if you think the situation has changed, renegotiate. Renegotiating is an option, and the company can say no. If you’re not satisfied, resign, honor the terms to the end, and leave like any good professional. Walking off the job, like in the blog account, is a unilateral breach of contract. It’s wrong.

You have several reasons to hold a job. There’s the salary to pay the bills at the end of the month, assuming you’ve grown a spine and stopped sponging off mom and dad. And there’s the learning: you’re paid not only to do your job, but to explore everything established companies have already figured out, which you soak up “for free.” Every criticism you get, every complaint, is a chance to sharpen something you didn’t even know you were missing. “No pain, no gain.”

The very fact that you struggle to find another company willing to hire you already shows you’re still short on skills. Another common line is “I’d do more, but nobody gives me a chance (or pays me more).” If you’ve caught yourself saying that, you still have a lot to learn. And even to be an entrepreneur, this is the most basic lesson: nobody gives you anything for free, everything is a voluntary trade for mutual benefit. No benefit, no deal.

And I’ll tell you the worst place in the world to learn all of this: your own first company. The most common outcome when someone completely inexperienced decides to open their own shop? Becoming exactly the kind of boss described by the blog author who worked at Apple.

PS: there were plenty of ways the blog author could have solved his internal problem. A company the size of Apple, with more than 80 thousand employees, surely has several paths to solving a problem like that. Not knowing how to find them only shows there's still a lot to learn. After all, the squeaky wheel gets the grease.

"Everyone's doing B2C startups, almost no one is solving the 'Enterprise' problem, the billion-dollar B2B market."

Let me simplify. I’m treating “B2C,” business to consumer, as all the common sites we see today: social networks, instant messaging, content management, everything whose final target audience is the mass of individual consumers. And “B2B,” business to business, as the software solutions that solve both a corporation’s internal problems and problems that connect multiple corporations, where the target audience is legal entities. It’s a simplification, but it serves my purpose.

I’ll repeat something I tweeted recently: “entrepreneur” is a state, not a career or a profession. Any person, individual or legal entity, by definition, is entrepreneuring. Even a student is, building their own knowledge to solve some problem in the future. A house cleaner is an entrepreneur, and today some even earn at scale by subcontracting others and distributing services.

So it’s not only software developers who, by chance, won this “privilege.” In practice, there’s nothing special about being an entrepreneur, you just have to not be a procrastinator.

Many young people, many not even in college yet, are dazzled by the false “glamour” of this short period, which could well be a bubble, or at least a temporary market anomaly. If you’re in this group, I recommend my previous article, the translation of Alex Payne’s post, Letter to a Young Programmer Considering a Startup.

The exercise here is simple. Why do you think the overwhelming majority of tech startups invest in B2C web applications? And why are almost all of them so similar to each other? Basically, if you swap the logo, the name, and a few colors, many of them come out practically identical. Ecommerces are obvious. Vertical social networks. Mix a network-of-acquaintances component with verticals like jobs, classifieds, transportation (taxi), exercise and health.

The answer is frighteningly simple: it’s all an inexperienced person knows. Their day-to-day boils down to using Facebook, Instagram, Medium, and Tumblr. To taking the bus and the subway. To going to an emergency room or getting some exams. To going to the gym. To attending a university. And all of it from the consumer’s point of view, never the provider’s or producer’s. That’s why everything comes out more or less the same.

The Corporate World Is Very Boring

The most frightening side effect is that “tech startups” and the pseudo-career of “entrepreneur” come as the salvation of whoever read blogs, tweets, and Facebook posts about how ‘horrendous’ the life of a worker at an agency, at a big company, at a corporation is. The bureaucracy, the politicking, the hierarchical structure. All of it painted as if getting a job were walking down death row, and as if being employed at a corporation were being tortured daily in cruel ways.

And worst of all: most young, inexperienced people believe it. TL;DR: it isn’t entirely true.

To make it worse, Black Swans really do show up along the way. Facebook, Tumblr, Snapchat, Twitter. That gives the impression the feat can be repeated. Not understanding the Law of Large Numbers can be fatal.

In short: given millions of people trying to win the lottery, one eventually wins. But there’s no repeatable process that gets you there. It’s a dead-end of randomness. Thank Bernoulli and Poisson for warning us about it, even though few know it today.

I’m not saying there’s no value in B2C. Of course there is, just far more limited than people imagine. The other side of the coin, the corporate world, is almost immune to startups. We know the big names: SAP, Oracle, Microsoft, Totvs. On the purely technical side, this is very low-quality software that, ‘magically’ for some, moves billions of dollars. And it’s a market that has seen little or almost no disruption in decades.

The reason is simple: few have stopped to understand how this world works. Think about someone trying to break into ecommerce. The shallow understanding is that an ecommerce is a “virtual store.” I see it differently: I understand ecommerce as one more distribution channel.

Behind it there are countless consolidated processes that anyone who has worked in retail knows well. Distribution centers, Supply Chain, pricing strategies, taxation and material transport, purchase approval, inventory and warehouse management. Familiar territory for anyone who has worked with Sales and Distribution. Alien to everyone else.

Job sites. Few grasp what that means, but it’s a small leg of the area known as HR, Human Resources. It means understanding labor law, labor liability, benefits, recruitment and selection, training, payroll, timesheets, travel.

Understand this: you have no chance of offering anything to the corporate market without having actively taken part in it. To someone who has never been there, a corporation is a black box. And most immediatist people tend to back away from what they don’t understand instead of exploring it. A “hacker” does the opposite: cracks black boxes open. Whoever just consumes stays a script kid thinking they’re more than they are.

When you pass through several companies, several contexts and situations, different processes at different stages, only then do you start to understand the problem domain. Do this a few times and maybe you start to see how to improve or, better yet, “innovate” in this segment.

Innovation in the corporate market starts with simple process optimization, and can end in the complete replacement of an old process or the creation of an entirely new vertical. But innovation, on its own, is a process, with stages that have to be cleared one by one. And the first stage is invariably acquiring knowledge.

There are no shortcuts. Even in B2C it amazes me to see someone try to build a product for the masses without understanding the persuasion techniques accumulated in the body of knowledge called “marketing.”

The shortcut of building copy-cat tech startups, blindly believing in a nonexistent promise, is raising a generation that’s ignorant of the processes that govern this enormous market. And some things are time-dependent. I took advantage of that by entering the market early, aiming to figure out how its gears work.

When you’re the youngest, mistakes weigh less and wins are overvalued. Once you’re past that age, mistakes become intolerable and wins are treated as the expected norm. And the later it gets, the less chance you have of understanding how the world works, with more and more doors closed.

Obviously I’m generalizing. There are exceptional cases where this works differently, but if you don’t yet know whether you’re an exceptional case, the odds are that you aren’t.

Serendipity only happens when you expose yourself to the widest possible variety of situations, creating opportunities. In a single startup, a single product, a single unproven idea, the chances of serendipity collapse.

The advantage of an SAP, over its several decades of existence, was accumulating the knowledge of every process, of every industry, sweeping through nearly everything important in the corporate world. And even so there are areas it still can’t quite touch, which opens room for a Salesforce.com to stand out. Now picture whoever is artificially limiting themselves.

More than that: with no knowledge at all and the illusion that “mistakes” are good because they turn into learning, we forget the obvious. Erring is human. Erring at what is already notoriously wrong is stupidity, pure and simple.

Charging a client without having signed a contract first, then calling them dishonest for not paying in full, shows the stupidity of whoever didn’t sign the contract. Spending the money up front as “investment” and then running into payroll trouble is amateurism from someone who ignores the basics of cash flow.

Rewriting entire systems without knowing what it will cost in development hours, user training, integrations, data migration, and opportunity cost is another huge blunder from someone who can’t do basic cost analysis. All of this is plain stupidity, you don’t need to err to learn it. Seeing it happen once was enough: every company does this, for decades, long before you were born.

This is inexperience, which is normal, nobody is born knowing everything. That’s why acquiring experience matters so much. Without it you’re always at a disadvantage, because you wanted a shortcut you thought would save 5 years and it’ll leave you 10 years behind.

The B2C world is over-saturated. The B2B world will stay free of important startups for a few more years, since this generation is also wasting time and effort in inefficient ways, throwing away everything we’ve known for years. And remember: avoiding waste, as I recall, is the pillar of “Lean.”

Alex Payne was one of the earliest engineers at Twitter. I know him from Scala and his posts on NoSQL and other tech topics. Beyond being a programmer and a book author, he’s a seasoned startup investor.

His view on startups lines up with mine. I recommend watching the talk, which grew out of a post on his blog with the same title as this article. I decided to translate that post into Portuguese because Brazilians need to hear more of the other side of the coin.

From here on, these are Alex’s words:

I regularly receive emails from young people, usually those interested in programming, who are trying to make decisions about school and/or their professional futures. This post is for those young people.

If you’re in your late teens or early 20s, you’ve grown up in a world that idealized startups, their founders, and the people who work at them.

If you’re in school, you may have felt pressure or have been encouraged to drop out and join or start your own company. If you’re already out in the working world, you may feel that your non-startup job is somehow inadequate, or that you’re missing out on valuable experience and potential wealth.

The generation you grew up in has, in recent years, teetered on the brink of becoming “lost.” Jobs are scarce, entering a university offers no guarantee of employment. Big, old corporations are no longer a guarantee of safe harbor for building a career. Startups appear, through the lens of the media, as the only sign of life in a dying world. I understand the appeal.

Everyone’s background is different, and your choices are only yours. That said, you’re not making decisions in a vacuum. Here are some things to consider that, in my experience, you’re less likely to hear about if you’re working in startups.

A startup is only a means to an end.

I recently interviewed a young guy. I asked him where he saw himself in four years. “Running my own company,” he said without hesitation. I asked him why. “Because entrepreneurship is in my blood,” he answered. There was no mention of what his hypothetical company would do, what problems he would solve for people. His goal was a company just for the sake of having a company. That’s what he studied for, after all.

People are satisfied in their jobs when they operate with a sense of purpose. So much of our understanding of the psychology of success revolves around goals and keeping those goals top of mind: visualizing the moment of achievement, tracking progress, having others hold us accountable to reach them. Goals shape our individual futures.

Maybe a startup is the best way to reach that goal, and maybe it isn’t. If the goal of the young guy described above is to own a business — any business! — then maybe a startup really is the best path. For others, however, I always wonder if they’re adapting their goals into the shape of a startup because that’s the most applauded, admired, and easily understood (if not easily achieved) approach.

Maybe the best way to reach your goal is starting a non-profit organization or going into politics. Maybe it’s doing research at a university or making art. Maybe the answer is joining a large, stable company with formidable resources you can leverage to reach your goal. Maybe your goal is best reached by building a stable, pressure-free career that leaves enough time for your family, friends, community, and self-improvement.

A startup is only a means to an end. Consider the end, and try not to celebrate the means. What do you care about? Who do you want to help? Does a startup make it easier or harder to reach this goal? Where will this leave you when your goal is reached? Where will it leave you if it isn’t?

A job at a startup is the new office job. Startup culture is the new corporate culture.

Startups are portrayed as being exciting, risky, and even subversive alternatives to traditional corporate employment. Startups are seen as freer, more open, more flexible. Some companies really do start like that, but some interviews at late-stage startups make it clear how fast they ossify into structures that resemble the organizations that came before them.

Just as in the first dot-com bubble, there’s currently a proliferation of startups, incubators, accelerators, angel investors, and so on. In order for the “startup community” to replicate itself, nanobot-style, the mechanics of “doing a startup” have been reduced to an easily transportable sequence of actions accompanied by a shared set of values, norms, and language. As a result, the culture of most startups is uniform, even in style of dress and accessories that help “startup guys” — and they’re mostly “the” guys — stay with their herd (so they’re not preyed on by cougars).

Business school graduates like the young guy I interviewed are going straight from university to startups, and that’s if they even finish school. Business graduates, traditionally risk-averse, now say they don’t want to work for big companies. But startups are the new big companies. They are, as I’ll describe below, the office cubicles of a distributed workforce aggregated by venture capitalists and their associated institutions.

There’s nothing inherently wrong with an office job. Just understand what you’re joining. When the company-supplied beer kegs run dry, when the free snacks are making you fat, and playing Xbox in the chill room isn’t as fun anymore, what then? When you find out you now report to a politicking middle manager and not the inspiring CEO who interviewed you, will you still want to be there? Is it an environment with enough toys and novelties to sustain you? When every place you consider working looks more or less the same, how long does the novelty last?

Startups have been systematized, mythologized, culturally and socially de-risked; reduced to formulas and recipes. And yet, there is no sustainable formula for creativity and rebellion. When we try to industrialize innovation, we tear out exactly what we’re trying to cultivate: the creative destruction that keeps the fire of capitalism burning.

Startups are part of the system, not a rebel wrench in the gears.

Funding for startups — that is, the money that pays your salaries — comes from somewhere. Wealthy individuals and institutions invest in startups like any other asset class. The futurist Bruce Sterling recently joked that “startups are full of young people working hard to make other people rich — Baby Boomer financiers, mostly.” Even though this may be a generalist and cynical statement, it’s by no means untrue.

In broad strokes, and excluding areas like biotech, venture-backed startups are a machine where relatively small amounts of capital are inserted on one side and, ideally, a lot comes out the other side. (In reality this machine seems to not work anymore, although the effectiveness of VC as an asset class and the VCs themselves is open to discussion). The salient point: what’s in the middle of the machine is you. You make it run.

The machine isn’t interested in you. In fact, the machine is designed with the understanding that most startups will fail, or at most offer mediocre returns to investors. Most companies in many VC portfolios are recognized as straw men. One or two “10x” companies are what give value to the portfolio. In the best case, founders of failing startups get another push at the slot machine. In the worst case, their failures lead them to despair.

There’s nothing inherently disruptive about a venture-backed startup. The startup system is just another system; an alternative to the corporate ladder but with as many rungs. Some startups may end up dramatically reshaping the market, but so can any other operator already in the game or active regulator.

The now perennial celebration of startup-driven disruption raises the question: if we accept that disruption is indeed happening, are we better off in the resulting disrupted market? Did we solve a problem, or did we just move the problem around? Are we creating value while increasing fairness and equality, creating positive change that will last? Or did we just make one group of rich people a little richer at the cost of another group of rich people? Are we creating a better future, or just reshuffling the present?

Startups have an ongoing interpersonal cost.

No startup story is complete without a scene or two of macho heroes: nights spent programming to exhaustion, weeks away from home trying to raise money in humiliating pitch after humiliating pitch. Startups appeal to a desire for daring that is lost in many forms of modern work, and we hear stories of the rewards waiting when personal lives are sacrificed on the altar of the launch schedule.

Less often we hear about the damage startups do to people’s lives. In extreme cases, like with the entrepreneur whose story of failure and suicide is linked above, the “community” may take a day or two to reflect and lament in blogs and tweets. Then they’re back to “the grind,” and more importantly, making a public show of how hard you’re working to satisfy the investors and the intimidating competition.

I’ve seen firsthand the damage startups can do to relationships. I’ve seen marriages and friendships destroyed, I’ve seen children and partners being sidelined, and I’ve failed those in my life in every way when work came first. I would listen as people who are the picture of a successful startup — visible in the press and social media, leading conferences, eternally founding and exiting — confided their total loneliness despite seemingly being the social center of the entrepreneurial community.

When you’re young, relationships seem like a renewable resource. Friendships exist in abundance and come easily. Just leaving home and into the world, you’re eager to escape the constant presence of family. Being pulled into work makes you feel important, independent, an adult. The work itself provides a new community and new friendships, and the bonds formed during intense collaborative work are strong.

I made many friends through work at early-stage companies. Ironically, these relationships are easier to maintain and enjoy when I’m not working at a startup.

Parting Thoughts.

I’ve worked in startups for half my life now. This work has brought me financial freedom, and I’ve put money I earned at a startup into other startups. If there is, as I’ve argued above, a modern “startup system,” I’m part of it.

I won’t mince words: I am deeply skeptical of this system. I’m skeptical of this system’s slavery, self-congratulatory fetishization of “disruption,” while at the same time becoming so obviously the kind of impassive institution it wants to replace. I’m skeptical of the short-term vision of the startup community. And I’m particularly skeptical of its disregard for the lives of the people who participate in it and the lives of those who live in the world that startups seek to reshape. Let’s not even start to discuss the collusion, cartelization, and other market corruption activities that are so common in the VC world. The point being: it’s a bad game, and a fraudulent game.

And yet. There are startups I wouldn’t want to see disappear. There are people working at and founding these startups who are good, kind, with balanced personal and professional lives, concerned about the impact of their work. Just as we throw slander and accusations of corruption at other systems like politics, mass media, entertainment, and professional sports, we must also admire those who operate ethically and effectively in them. We should celebrate even more those who pioneer new and alternative systems, because they work in the shadows of the community that has a constant hand on the crank of the publicity machine.

Now, you could say that I’m laying too much responsibility at the feet of the startup world. Although this system spreads every day over itself as the savior of everything, from capitalism to culture, of course we can accept that business is business and ideals are better left at home. As a VC from a top firm on Sand Hill Road told me during a pitch many years ago when I was describing a conceptual feature in Simple that would make it easier for users to more easily and regularly donate a portion of their savings to charity, “let’s not waste time on that stuff, we’re here to make money.”

You may be able to stomach that conduct, but I hope your idealism hasn’t been worn down while still so young. I hope you want your work to have meaning, purpose, and value no matter what form that work takes. More than that, I hope you want your life to be defined by more than your work.

Young programmer, I urge you to consider both sides of the startup coin. There are so many ways to leave a mark on the world.

A Note about Feedback

If you are part of the audience of this post, I’d love to hear your feedback and answer your questions, preferably by email. My address is easy to find on this site.

If you are not part of the audience of this post and are really, really angry that a stranger on the Internet has a different opinion from yours, I encourage you to direct your energy into an alternative argument that someone young (or, really, anyone at a career transition point) could benefit from reading. They are your future employees, coworkers, or founders. They are the ones you need to convince, not me.

— May 23, 2013

Taking to the streets isn’t the only solution.

"Never in the history of the world has anyone ever achieved anything good and valuable by means of prayers and supplications" – J.P. Morgan

I don’t want to judge or analyze the #vemprarua (“come to the streets”) movements that took over the country’s streets in the recent past. It’s a tangle I’ll leave for political scientists and historians to untangle. What I want to elaborate on is a mindset that comes out of this kind of movement and shows up in our day-to-day: “claiming,” the act of “complaining, demanding.”

It’s very common for this new generation to fall into the trap of thinking that demanding is the best solution to problems. They’re wrong. Barring extreme cases, that’s always the worst possible solution. In the daily life of the common man, demanding is just a declaration of your own incompetence.

Let’s consider our tech market in general:

• Demanding better working conditions: nobody works anymore in dirty, smoky factories, alongside rats and sewage. Come on, nobody even works 8 hours a day nonstop, at most 4 hours stretched over 8.
• Demanding better salaries: it’s a free market, with dozens of tech companies of all sizes and categories. Mobility is easy. Of course, only someone with the ability to do it manages to move from one company to another for more money. Whoever stays put, unhappy, and only knows how to “demand” a raise is already showing their low character.
• Demanding investments: it seems startup ’entrepreneurs’ today are turning into ‘professional beggars,’ convinced they can only move forward once an investor hands them money.

The “demanding” mindset leads to another one, the “cheap complainer,” the person who blames everyone but themselves.

• “What they’re asking is impossible to do in this time and cost.” The thinking behind it: “I can’t picture a way, so it must be impossible.”
• “The product’s users are stupid, the problem isn’t the product.” The thinking: “if I made it, it can only be good; if they’re complaining, they’re the stupid ones.”
• “The market is unfair: I know more and earn less than I should.” The thinking: “I know I’m really good, so why don’t they pay me what I want?”
• “They only criticize me, and what about the other guy who also didn’t do it?” Nobody likes being criticized, but without criticism there’s no progress. Worse still when the first reaction to criticism is to compare it with someone else’s mistake or to justify it by blaming others. That profile will never go far. Praise doesn’t help anyone evolve, cheap praise least of all.

The “Me me me” Generation is the most sensitive I’ve ever seen. It should be called the “Porcelain Generation,” because it breaks way too easily.

In the Industrial Revolution people were literally hard as iron. There was no option: many died in the factories, and the concept of “working conditions” didn’t even exist. In the agricultural era, people worked from sunrise to sunset, earning very little and carrying tons on their backs.

Now this digital era has a stereotypically Emo resilience (nothing to do with the origins of hardcore punk): scratch a fingernail and they panic. Adolescence is being stretched, and adulthood only shows up after 30 (back in the day, 16 was a good age to take on an adult role).

That should actually be a good thing, because it means we’ve raised comfort to a level never seen in millennia of human history. But there’s a side effect: the new generation grew up without understanding how hard it was to get here.

All of this can lead to a question: “so I’m supposed to swallow everything I don’t like?” Not at all. And here’s a hook back to my previous article “Constraints are Liberating: less is more”.

Always assume this premise: nobody is ever going to give you what you want or need, much less anything beyond that. If you haven’t earned it, you don’t deserve what you’re asking for, and nobody has any obligation even to listen to what you have to say. It’s on you, and only you, to solve your own problem, with your own sweat and your own tears.

To me, the difference between a child and an adult is simple: an adult solves their own problems with their own hands and never expects them to be solved for free. And “solving” means actually solving, without blaming others, without demanding, without sweeping the problem under the rug.

And when the problem looks “impossible” is exactly when you get the best chance to innovate. Innovation comes precisely out of an impossible situation. A thing is impossible when you can’t pull it off with what we know today. You can only solve it down a different path, one nobody knows yet.

The teenagers graduating from colleges today see this trendy “Startup” wave and want to be “entrepreneurs.” All they learn to do is put together PowerPoints for Demo Days. They believe their “education” (which is thin, no matter the MBA or PhD) and their “idea” are enough to crown themselves “entrepreneurs.” That’s little, extremely little.

An “entrepreneur” who takes low risk and makes low sacrifice is just an average employee with a fancy title. An “idea” and a possible investment solve very little.

First, go work in a real industry to learn how it works and, who knows, find a solution nobody has tried yet. Because here’s another truth: whatever idea you have, someone has probably had it before and already tried it in all sorts of ways. The odds of you having a truly original idea are low.

Only when you land in an impossible situation, where everything has already been tried, does the chance to try something new and maybe innovative show up. As you try to solve it, you might end up finding a solution that already existed and discover that your “impossible” was just not knowing what was already known. Then you move on to the next problem.

I was watching the History Channel series “The Men Who Built America”, which shows, in a romanticized way, part of the story of how the United States conquered and earned its place as the biggest economic power in the world. The story starts like ours: nobody gave them anything, everything had to be earned. It has some good examples I like to cite.

• It was impossible to transport goods across the entire country by horse or even by ship; it became more and more necessary to find ways to shorten that time. It was the railroads of Vanderbilt that connected all the states of the country.
• It was impossible to have a corporation as large and massive as Standard Oil once was, but Rockefeller innovated what we know today as corporate structures, many of his practices later deemed illegal. If you’ve ever filled your tank at an Esso station here in Brazil, it’s worth remembering where it all started.
• It was impossible to cross the great Mississippi River with an iron bridge. Connecting the East and West of the country seemed impossible. It took an Andrew Carnegie to execute the idea of an affordable steel industry at large scale to solve this problem. Carnegie Steel was formed, which would later become US Steel.
• It was impossible to have electricity distributed to every home in the country. It literally took the “blood” of geniuses like Edison, Tesla, Westinghouse, and Morgan to reach this goal. Today we don’t even think about it, because everyone assumes electricity is something “natural.” It wasn’t.
• It was impossible to improve the brutal working conditions in factories and have productivity at the same time. Henry Ford changed that with the refinement of his production line. By the way, remember the model that made him famous was the Ford Model T; to get to “T” he started at model “A.”

These and other “self-made men” changed the world one way only: by solving one problem at a time, without claiming, complaining, or demanding. And the more “impossible” the problem was, the more “revolutionary” the solution turned out to be. That’s how great entrepreneurs are made: solving their own problems with their own hands.

The opening quote of the article sums up its content, and the next one defines it:

"Vision without execution is hallucination" – Thomas Edison

“We’re putting together an excellent new product that will solve your problems, would you use it?” says the validation survey of a new startup. Result: 70% of the 1,000 people who answered said yes. So the conclusion is clear: the product is valid and can’t go wrong, right?

Wrong. Those numbers don’t mean a thing. On their own they carry no validity, and they support no conclusion at all. “But it’s 1,000 people! How can you say that?” This article isn’t trying to be statistically rigorous, just to point out a few of the many places where almost everyone gets it wrong when running a survey these days.

First of all, what’s your product’s target audience? Let’s say it’s the population of the interior of the southern states, classes C and D, ages 50 to 60, with little experience using computers. Now imagine the question above was part of a survey done online, shared on Facebook and Twitter.

Who answered it? Plenty of people from classes A through C for sure, concentrated in the southeastern capitals, ages 16 to 25, on a computer every day. You asked the wrong question to the wrong people.

For the sake of the example, let’s say you took care to pick the right population and dodged what’s known as “Biased Sampling.” Even so, the question is still bad, and it should be obvious why. It’s what we call a “Loaded Question”: the wording already nudges the respondent toward a certain answer.

For starters, it takes for granted that the product is “excellent” and that it “will solve” the person’s problems. A less loaded form would be: “We’re building a product with features X; assuming you have problems Y, do you think this would help solve them?”

There are plenty of techniques for steering clear of baseless premises, like actually explaining the value proposition instead of stuffing the question with rhetoric. It’s very easy to build a fallacious question that pulls a false answer out of people.

It gets worse when you take those 1,000 people, single out the 700 who said “yes” to the rigged question asked of the wrong audience, and start drawing conclusions from it. “Oh, we noticed that of these 700, half have a credit card, shop online at least once a month, and say they’d share the service with at least 2 friends on social media.” And it gets worse still when the ones who said “no” happen to be the audience closest to the target you want to reach.

I also consulted Ricardo Couto* who explained the issue. “Knowing the respondent, their habits and motivations is much more valuable for the business than having a high percentage of favorable responses about the product or service in an online questionnaire. By the way, calling a form put together in 5 minutes on Google Docs or SurveyMonkey a ‘survey’ is, at best, naïve. What you have there is a questionnaire. Questionnaires can be useful if used well. But in general, they’re just sets of questions around a subject. A survey can even make use of that tool, but not every questionnaire is a survey.”

Statistics, probability, and research in general are the work of professionals who master this field. It’s no trivial matter, and it’s not something to handle carelessly. This example is just one of the many ways to fool yourself with numbers.

Mark Twain popularized the phrase “There are three kinds of lies: lies, damned lies, and statistics.” The subject has been discussed and rebutted so widely that it produced a famous 1954 book by Darrell Huff, “How to Lie with Statistics,” which catalogs the intentional and unintentional errors in interpreting statistics.

Ricardo also added: “If we think of an online questionnaire as a serious research tool, first you have to know how research is done. I really doubt that the people who say they ‘are doing’ a survey and send you a link to a questionnaire took into account the order effect, the observer effect, or avoided leading questions – factors well known to anyone who does real research. And I’m not even getting into statistical validity, which you only reach by applying statistical methods (a simple percentage isn’t descriptive statistics, okay? you have to know what a p-value is), or into selecting respondents suited to the target audience you intend to reach. Or do I only want, as users, customers, or consumers, professionals in my age bracket, my income range, and my online shopping and social media behavior?”

So the next time you go to create an account on one of those dozens of online survey services, check whether the tool meets the bare minimum of a well-done survey and walks you through the right steps: defining the audience, collecting, processing, and analyzing the data rigorously. Without that, all you’re left holding is a pile of opaque numbers, with no meaning and no conclusion to draw from them.

*Ricardo Couto is a Consultant in User Experience and Research, Mentor at Aceleratech, President of the Interaction Designers Association SP (IxDA SP), and Member of the Brazilian Information Design Society. He studied Cognitive Psychology (master's) at the Federal University of Pernambuco and specializations in Information Design, Higher Education Teaching, and Distance Education Technology. He was a university professor at undergraduate and graduate level for 7 years.

I wrote about my journey in 6 articles, originally in Brazilian Portuguese. You can use Google Translate that’s available in all of them, I’m curious to see if they work well enough. The journey starts in September 2012 and ends in October 2012. Here are the articles:

• Trip to San Francisco - Part 1 - Techcrunch Disrupt

• Trip to San Francisco - Part 2 - Visiting Companies

• Trip to San Francisco - Part 3 - People and Tourism

• Trip to Europe - Part 1 - Amsterdam, Netherlands

• Trip to Europe - Part 2 - Berlin, Germany

• Trip to Europe - Part 3 - Tel-Aviv, Israel

PS: I was in doubt about considering Israel in “Europe”, seems like it’s actually Asia but it’s considered part of Europe for sports :-)

I also posted hundreds of photos organized in Facebook Albums that you can access here:

• San Francisco
• Amsterdam
• Berlin
• Tel-Aviv/Jerusalem

Finally, I’ve documented my every move while there through Instagram, you can see them all here

Enjoy!