Open Source and Profit

I have written extensively about free, open source software as a way of life, and now reading back my own articles of the past 7 years, I realize that I was wrong on some of the ideas, or in the state of the open source culture within business and around companies.

I’ll make a bold statement to start, trying to get you interested in reading past the introduction, and I hope to give you enough arguments to prove I’m right. Feel free to disagree on the comments section.

The future of business and profit, in years to come, can only come if surrounded by free thoughts.

By free thoughts I mean free/open source software, open hardware, open standards, free knowledge (both free as in beer and as in speech), etc.

Past Ideas

I began my quest to understand the open source business model back in 2006, when I wrote that open source was not just software, but also speech. Having open source (free) software is not enough when the reasons why the software is free are not clear. The reason why this is so is that the synergy, that is greater than the sum of the individual parts, can only be achieved if people have the rights (and incentives) to reach out on every possible level, not just the source, or the hardware. I make that clear later on, in 2009, when I expose the problems of writing closed source software: there is no ecosystem in which to rely, so progress is limited and the end result is always less efficient, since the costs to make it as efficient are too great and would drive the prices of the software too high up to be profitable.

In 2008 I saw both sides of the story, pro and against Richard Stallman, on the views of the legitimacy of propriety control, being it via copyright licenses or proprietary software. I may have come a long way, but I was never against his idea of the perfect society, Richard Stallman’s utopia, or as some friends put it: The Star Trek Universe. The main difference between me and Stallman is that he believes we should fight to the last man to protect ourselves from the evil corporations towards software abuse, while I still believe that it’s impossible for them to sustain this empire for too long. His utopia will come, whether they like it or not.

Finally, in 2011 I wrote about how copying (and even stealing) is the only business model that makes sense (Microsoft, Apple, Oracle etc are all thieves, in that sense) and the number of patent disputes and copyright infringement should serve to prove me right. Last year I think I had finally hit the epiphany, when I discussed all these ideas with a friend and came to the conclusion that I don’t want to live in a world where it’s not possible to copy, share, derive or distribute freely. Without the freedom to share, our hands will be tied to defend against oppression, and it might just be a coincidence, but in the last decade we’ve seen the biggest growth of both disproportionate propriety protection and disproportional governmental oppression that the free world has ever seen.

Can it be different?

Stallman’s argument is that we should fiercely protect ourselves against oppression, and I agree, but after being around business and free software for nearly 20 years, I so far failed to see a business model in which starting everything from scratch, in a secret lab, and releasing the product ready for consumption makes any sense. My view is that society does partake in an evolutionary process that is ubiquitous and compulsory, in which it strives to reduce the cost of the whole process, towards stability (even if local), as much as any other biological, chemical or physical system we know.

So, to prove my argument that an open society is not just desirable, but the only final solution, all I need to do is to show that this is the least energy state of the social system. Open source software, open hardware and all systems where sharing is at the core should be, then, the least costly business models, so to force virtually all companies in the world to follow suit, and create the Stallman’s utopia as a result of the natural stability, not a forced state.

This is crucial, because every forced state is non-natural by definition, and every non-natural state has to be maintained by using resources that could be used otherwise, to enhance the quality of the lives of the individuals of the system (being them human or not, let’s not block our point of view this early). To achieve balance on a social system we have to let things go awry for a while, so that the arguments against such a state are perfectly clear to everyone involved, and there remains no argument that the current state is non-optimal. If there isn’t discomfort, there isn’t the need for change. Without death, there is no life.


Of all the bad ideas us humans had on how to build a social system, capitalism is probably one of the worst, but it’s also one of the most stable, and that’s because it’s the closest to the jungle rule, survival of the fittest and all that. Regulations and governments never came to actually protect the people, but as to protect capitalism from itself, and continue increasing the profit of the profitable. Socialism and anarchy rely too much on forced states, in which individuals have to be devoid of selfishness, a state that doesn’t exist on the current form of human beings. So, while they’re the product of amazing analysis of the social structure, they still need heavy genetic changes in the constituents of the system to work properly, on a stable, least-energy state.

Having less angry people on the streets is more profitable for the government (less costs with security, more international trust in the local currency, more investments, etc), so panis et circenses will always be more profitable than any real change. However, with more educated societies, result from the increase in profits of the middle class, more real changes will have to be made by governments, even if wrapped in complete populist crap. One step at a time, the population will get more educated, and you’ll end up with more substance and less wrapping.

So, in the end, it’s all about profit. If not using open source/hardware means things will cost more, the tendency will be to use it. And the more everyone uses it, the less valuable will be the products that are not using it, because the ecosystem in which applications and devices are immersed in, becomes the biggest selling point of any product. Would you buy a Blackberry Application, or an Android Application? Today, the answer is close to 80% on the latter, and that’s only because they don’t use the former at all.

It’s not just more expensive to build Blackberry applications, because the system is less open, the tools less advanced, but also the profit margins are smaller, and the return on investment will never justify. This is why Nokia died with their own App store, Symbian was not free, and there was a better, free and open ecosystem already in place. The battle had already been lost, even before it started.

But none of that was really due to moral standards, or Stallman’s bickering. It was only about profit. Microsoft dominated the desktop for a few years, long enough to make a stand and still be dominant after 15 years of irrelevance, but that was only because there was nothing better when they started, not by a long distance. However, when they tried to flood the server market, Linux was not only already relevant, but it was better, cheaper and freer. The LAMP stack was already good enough, and the ecosystem was so open, that it was impossible for anyone with a closed development cycle to even begin to compete on the same level.

Linux became so powerful that, when Apple re-defined the concept of smartphones with the iPhone (beating Nokia’s earlier attempts by light-years of quality), the Android system was created, evolved and dominated in less than a decade. The power to share made possible for Google, a non-device, non-mobile company, to completely outperform a hardware manufacturer in a matter of years. If Google had invented a new OS, not based on anything existent, or if they had closed the source, like Apple did with FreeBSD, they wouldn’t be able to compete, and Apple would still be dominant.

Do we need profit?

So, the question is: is this really necessary? Do we really depend on Google (specifically) to free us from the hands of tyrant companies? Not really. If it wasn’t Google, it’d be someone else. Apple, for a long time, was the odd guy in the room, and they have created an immense value for society: they gave us something to look for, they have educated the world on what we should strive for mobile devices. But once that’s done, the shareable ecosystem learns, evolves and dominate. That’s not because Google is less evil than Apple, but because Android is more profitable than iOS.

Profit here is not just the return on investment that you plan on having on a specific number of years, but adding to that, the potential that the evolving ecosystem will allow people to do when you’ve long lost the control over it. Shareable systems, including open hardware and software, allow people far down in the planing, manufacturing and distributing process to still have profit, regardless of what were your original intentions. One such case is Maddog’s Project Cauã.

By using inexpensive RaspberryPis, by fostering local development and production and by enabling the local community to use all that as a way of living, Maddog’s project is using the power of the open source initiative by completely unrelated people, to empower the people of a country that much needs empowering. That new class of people, from this and other projects, is what is educating the population of the world, and what is allowing the people to fight for their rights, and is the reason why so many civil uprisings are happening in Brazil, Turkey, Egypt.


All that creates instability, social unrest, whistle-blowing gone wrong (Assange, Snowden), and this is a good thing. We need more of it.

It’s only when people feel uncomfortable with how the governments treat them that they’ll get up their chairs and demand for a change. It’s only when people are educated that they realise that oppression is happening (since there is a force driving us away from the least-energy state, towards enriching the rich), and it’s only when these states are reached that real changes happen.

The more educated society is, the quicker people will rise to arms against oppression, and the closer we’ll be to Stallman’s utopia. So, whether governments and the billionaire minority likes or not, society will go towards stability, and that stability will migrate to local minima. People will rest, and oppression will grow in an oscillatory manner until unrest happens again, and will throw us into yet another minimum state.

Since we don’t want to stay in a local minima, we want to find the best solution not just a solution, having it close to perfect in the first attempt is not optimal, but whether we get it close in the first time or not, the oscillatory nature of social unrest will not change, and nature will always find a way to get us closer to the global minimum.


Is it possible to stay in this unstable state for too long? I don’t think so. But it’s not going to be a quick transition, nor is it going to be easy, nor we’ll get it on the first attempt.

But more importantly, reaching stability is not a matter of forcing us to move towards a better society, it’s a matter of how dynamic systems behave when there are clear energetic state functions. In physical and chemical systems, this is just energy, in biological systems this is the propagation ability, and in social systems, this is profit. As sad as it sounds…

Computer Science vs Software Engineering

The difference between science and engineering is pretty obvious. Physics is science, mechanics is engineering. Mathematics is (ahem) science, and building bridges is engineering. Right?

Well, after several years in science and far too much time in software engineering that I was hoping to tell my kids when they grow up, it seems that people’s beliefs are much more exacerbated about the difference, if there’s any, than their own logic seems to imply.


General beliefs that science is more abstract fall apart really quickly when you compare maths to physics. There are many areas of maths (statistics, for example) that are much more realistic and real world than many parts of physics (like string theory and a good part of cosmology). Nevertheless, most scientists will turn their noses up at or anything that resembles engineering.

From different points of view (biology, chemistry, physics and maths), I could see that there isn’t a consensus on what people really consider a less elaborate task, not even among the same groups of scientists. But when faced with a rejection by one of their colleagues, the rest usually agree on it. I came to the conclusion that the psychology of belonging to a group was more important than personal beliefs or preferences. One would expect that from young schoolgirls, not from professors and graduate students. But regardless of the group behaviour, there still is that feeling that tasks such as engineering (whatever that is) are mundane, mechanical and more detrimental to the greater good than science.

Real World

On the other side of the table, the real world, there are people doing real work. It generally consists of less thinking, more acting and getting things done. You tend to use tables and calculators rather than white boards and dialogue, your decisions are much more based on gut feelings and experience than over-zealously examining every single corner case and the result of your work is generally more compact and useful to the every-day person.

From that perspective, (what we’re calling) engineers have a good deal of prejudice towards (what we called) scientists. For instance, the book Real World Haskell is a great pun from people that have one foot on each side of this battle (but are leaning towards the more abstract end of it). In the commercial world, you don’t have time to analyse every single detail, you have a deadline, do what you can with that and buy insurance for the rest.

Engineers also produce better results than scientists. Their programs are better structured, more robust and efficient. Their bridges, rockets, gadgets and medicines are far more tested, bullet-proofed and safe than any scientist could ever hope to do. It is a misconception that software engineers have the same experience than an academic with the same time coding, as is a misconception that engineers could as easily develop prototypes that would revolutionise their industry.

But even on engineering, there are tasks and tasks. Even loathing scientists, those engineers that perform a more elaborate task (such as massive bridges, ultra-resistant synthetic materials, operating systems) consider themselves above the mundane crowd of lesser engineers (building 2-bed flats in the outskirts of Slough). So, even here, the more abstract, less fundamental jobs are taken at a higher level than the more essential and critical to society.

Is it true, then, that the more abstract and less mundane a task is, the better?


Since the first thoughts on general purpose computing, there is this separation of the intangible generic abstraction and the mundane mechanical real world machine. Leibniz developed the binary numeral system, compared the human brain to a machine and even had some ideas on how to develop one, someday, but he ended up creating some general-purpose multipliers (following Pascal’s design for the adder).

Leibniz would have thrilled in the 21th century. Lots of people in the 20th with the same mindset (such as Alan Turin) did so much more, mainly because of the availability of modern building techniques (perfected for centuries by engineers). Babbage is another example: he developed his differential machine for years and when he failed (more by arrogance than anything else), his analytical engine (far more elegant and abstract) has taken his entire soul for another decade. When he realised he couldn’t build it in that century, he perfected his first design (reduced the size 3 times) and made a great specialist machine… for engineers.

Mathematicians and physicists had to do horrible things (such as astrology and alchemy) to keep their pockets full and, in their spare time, do a bit of real science. But in this century this is less important. Nowadays, even if you’re not a climate scientist, you can get a good budget for very little real applicability (check NASA’s funded projects, for example). The number of people working in string theory or trying to prove the Riemann hypothesis is a clear demonstration of that.

But computing is still not there yet. We’re still doing astrology and alchemy for a living and hoping to learn the more profound implications of computing on our spare time. Well, some of us at least. And that comes to my point…

There is no computer science… yet

The beginning of science was marked by philosophy and dialogue. 2000 years later, man kind was still doing alchemy, trying to prove the Sun was the centre of the solar system (and failing). Only 200 years after that that people really started doing real science, cleansing themselves from private funding and focusing on real science. But computer science is far from it…

Most computer science courses I’ve seen teach a few algorithms, an object oriented language (such as Java) and a few courses on current technologies (such as databases, web development and concurrency). Very few of them really teach about Turin machines, group theory, complex systems, other forms of formal logic and alternatives to the current models. Moreover, the number of people doing real science on computing (given what appears on arXiv or news aggregation sites such as Ars Technica or Slashdot) is probably less than the number of people working with string theory or wanting a one-way trip to Mars.

So, what do PHDs do in computer science? Well, novel techniques on some old school algorithms are always a good choice, but the recent favourite has been breaking the security of the banking system or re-writing the same application we all already have, but for the cloud. Even the more interesting dissertations like memory models in concurrent systems, energy efficient gate designs are all commercial applications at most.

After all, PHDs can get a lot more money in the industry than remaining at the universities, and doing your PHD towards some commercial application can guarantee you a more senior position as a start in such companies than something completely abstract. So, now, to be honestly blunt, we are all doing alchemy.

Interesting engineering

Still, that’s not to say that there aren’t interesting jobs in software engineering. I’m lucky to be able to work with compilers (especially because it also involves the amazing LLVM), and there are other jobs in the industry that are as interesting as mine. But all of them are just the higher engineering, the less mundane rocket science (that has nothing of science). But all in all, software engineering is a very boring job.

You cannot code freely, ignore the temporary bugs, ask the user to be nice and have a controlled input pattern. You need a massive test infrastructure, quality control, standards (which are always tedious), and well documented interfaces. All that gets in the way of real innovation, it makes any attempt of doing innovation in a real company a mere exercise of futility and a mild source of fun.

This is not exclusive of the software industry, of course. In the pharmaceutical industry there is very little innovation. They do develop new drugs, but using the same old methods. They do need to get new medicines, more powerful out of the door quickly, but the massive amount of tests and regulation they have to follow is overwhelming (this is why they avoid as much as possible doing it right, so don’t trust them!). Nevertheless, there are very interesting positions in that industry as well.

When, then?

Good question. People are afraid of going out of their area of expertise, they feel exposed and ridiculed, and quickly retract to their comfort area. The best thing that can happen to a scientist, in my opinion, is to be proven wrong. For me, there is nothing worse than being wrong and not knowing. Not many people are like that, and the fear of failure is what keeps the industry (all of them) in the real world, with real concerns (this is good, actually).

So, as far as the industry drives innovation in computing, there will be no computer science. As long as the most gifted software engineers are mere employees in the big corporations, they won’t try, to avoid failure, as that could cost them their jobs. I’ve been to a few companies and heard about many others that have a real innovation centre, computer laboratory or research department, and there isn’t a single one of them that actually is bold enough to change computing at its core.

Something that IBM, Lucent and Bell labs did in the past, but probably don’t do it any more these days. It is a good twist of irony, but the company that gets closer to software science today is Microsoft, in its campus in Cambridge. What happened to those great software teams of the 70’s? Could those companies really afford real science, or were them just betting their petty cash in case someone got lucky?

I can’t answer those questions, nor if it’ll ever be possible to have real science in the software industry. But I do plea to all software people to think about this when they teach at university. Please, teach those kids how to think, defy the current models, challenge the universality of the Turin machine, create a new mathematics and prove Gödel wrong. I know you won’t try (by hubris and self-respect), but they will, and they will fail and after so many failures, something new can come up and make the difference.

There is nothing worse than being wrong and not knowing it…