About me

Why everything is so complicated

First of all, I think we all feel that the world is super fucking complicated.

As I worked for different organizations of different sizes and with different people and cultures, the true size of the complexity at hand showed itself. And, since I’ve worked on both the big picture(Project Management) and details(Engineering), I can assure you that it’s even more complicated than you imagine.

The details are nearly infinite, and the big picture is also nearly infinite, as it’s harder to ignore the 4th dimension(time) when doing business plans as it is when writing code(in fact, the best engineers also take time seriously into account, but they don’t have as much skin in the game, so if something goes wrong they can just leave).

But the thing is, every organization also varies drastically. I couldn’t apply the same tools working for a company with 5 people in Portugal as I could working for a company with 1400 people in Germany.

The variability between each organization is, in itself, also nearly infinite.

If you ask more questions, you’ll find that there is a near infinite number of aspects, and that each of them is, in itself, also nearly infinite. And all this happens in a nearly infinite timeline.

I say nearly infinite because our perception doesn’t require knowing whether the universe is truly infinite or not, we’re too small for that.

Since we’re talking about near-infinite sizes, and that no matter how big your perception is, it’s still nothing compared to what’s out there, the only way to increase the perception of an organization is by working together and sharing perceptions. But the human aspect gets in the way of this.

The hardest part is knowing where to draw the line. When do leaders stop trying to get closer to +∞, and when do engineers stop trying to get closer to -∞? The answer will transform your business as it will help you understand what to do, and when, much more clearly.

You can achieve this by starting with very different tests and slowly making them more granular. Choosing the right tests is more important that the tests themselves and is where most go wrong.

A little about my history:

During my career as an engineer, I found myself either with incredibly different thoughts than my peers, or working between upper management and engineering. This forced me to juggle completely different points-of-view, goals, problems, and ideas. I had to conciliate both sides and make it possible for both sides to communicate more clearly and avoid misunderstandings. All for the sake of the project and the business.

Upper-management was always incredibly big picture oriented, naturally. And engineers were mostly detail oriented.

Where this goes wrong in organizations

The funny phenomenon that will now seem very obvious, is that upper-management tended to assume the details would sort themselves out(or else). And engineers tended to assume the big picture would also sort itself out. Both sides assumed and hoped the other side knew better, failing to realize that the failure to communicate these assumptions would be the cause of all the problems every organization will always have. Nearly every single tool your business uses internally is an attempt at making similar knowledge transfer processes easier(either between upper management and engineers, or upper-management and finance, upper-management and sales, etc). Unless you’re in the top 1% of businesses(think google, amazon, facebook, etc), bad tools will lead to worse work comparatively to others with slightly better tools. This makes you less competitive.

This lead me on a search for how to better understand humans to improve collaboration, and is arguably my favourite thing to do.

But, since I also understand machines fairly well, and that most businesses nowadays are complex cybernetic systems(computers and humans working together), I’m able to make sense of a lot of extremely different information and simplify it to make chasing a goal easier and faster for everyone involved.

I like to get the right people and the right tools working together to transform sub-par systems into highly effective machines, but taking into account personal and technological limitations.

I won’t expect people to work like machines, and I won’t expect machines to work like people.

I don’t associate with a single job title or label, which makes it incredibly hard to explain what I do, the idea of this site is to showcase a little of how I think in order to not have to explain myself with spoken words as often as I feel forced to.

A lot of people find me incredibly pretentious due to my idiosyncrasies. I’m aware that I might come off like that sometimes. The thing is, I just don’t care that much about it(but definitely enough to write all this, so make up your own mind about how you feel about this).

My motivation to write

Ever since I was young, I discovered that I’m good at picking up patterns. So, I spent a lot of time trying to pick up more patterns, and even patterns of the patterns, and patterns of the patterns of the patterns. If I figure out how something works, I proceed to document my findings, and move onto something else.

I look at everything as a system: https://searchcio.techtarget.com/definition/systems-thinking

When I pick up some patterns, I like to make a rough outline of them and systematically apply them to systems other than where I discovered them(eg: sports, business, art, music, etc). Sometimes the results are insanely dumb, other times insanely precise. I’m aware of this, and diligently test the theoretical results against the real world(by looking at the past, and the present, and extrapolating the future).(if you catch me in a test phase, I’m actively thinking out loud, and you will think I’m an asshole).

I will share some patterns I see in the world in this site as a reference for myself and others.

Who I write for

My only expectation from readers is that they’re reasonable according to the standard of the culture we share. My favourite method of persuasion for most people is the Ethos. As I find Logos to get too complicated very quickly in complex systems, and I find Pathos to be manipulative.

However, Ethos requires hard evidence, and, as a high school drop out, I don’t have much proof besides a long CV.

My biggest weakness is failing to provide sources that validate my opinions a bit better, but to be fair, sometimes the sources don’t exist(yet).

I used to suffer a lot from paralysis by analysis, but for topics I know well, it’s not as present as before anymore.

My one goal is:

To improve communication and collaboration worldwide(human->machine and human->human, I don’t like machine->human yet(ask me why)).

About the author

Amando Abreu likes to create automatable solutions to problems.

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