Crazy Hami

Vanar is usually explained in terms: it is a blockchain that people can actually use, made by a team that knows about games, movies and products, with popular brands and it has a system that includes games, virtual worlds, artificial intelligence tools and brand support. When people talk about Vanar they usually focus on how big it's many different areas a lot of users and the goal of getting billions of people to use Web3. Vanar is a blockchain that wants to be used by everyone. Vanar has a lot of parts, including games and virtual worlds, which is what makes Vanar interesting.
I think that way of looking at it makes sense. It makes it hard to see what the actual problem is with the framing. The framing is what gets in the way. We need to look at the framing and figure out where the real issue is, with the framing itself.
When we actually use systems, in the world they tend to fail because they cannot handle the daily work not because they are missing some things. When you have a lot of people using the system you start to worry about whether it will keep working whether you can make changes to it without problems and whether you can keep it running over time.
The real question is not whether a system can handle things like games or websites for people but whether it can do all these things reliably over time even when a lot of people are using it at the same time or when people are using it in different ways or when things outside of the system are changing.
When we think about how systemsre engineered platforms that people use every day are really tough on blockchain technology. These platforms cannot handle responses, unpredictable costs and obvious failures. If a new financial system on blockchain is down for a while it is not the end of the world.. If a game or a website that people use for fun is down it is a big problem. The same thing is true for websites that companies use to connect with customers. People who use these platforms do not think about the bad things about blockchain. They just want the platform to work quickly and consistently and they want to trust it. Blockchain technology has to work in these situations like, in games and entertainment platforms because people will stop using them if they do not work well. Blockchain has to be responsive, consistent and trustworthy for people to use it.
When we are designing infrastructure we need to think about how it will handle the things people expect from it. This is a different issue than just trying to make it work as fast, as possible or making sure it does well on tests that do not really show how it will work in the real world. We have to make sure our infrastructure can absorb the expectations that people have of it.
Systems that last a long time teach us something. The decisions we make about how they work at the beginning become a part of how they are built over time. This includes things like how they run how they keep track of information how we update them and how people get paid. As the system gets bigger these decisions add up. When other programs, tools and outside companies start to use these systems it becomes very hard to make changes to them. It is expensive. It can be dangerous.
If we design a system from the start to work with a lot of people it will be different from one that we try to change to work with a lot of people. One way is not better than the other. They have different problems. Systems that are designed for a lot of people from the beginning have issues than systems that are changed later to work with a lot of people, like consumer-scale systems.
Vanar is an example of this. They really focus on gaming and entertainment. This means that they think people want a few things. They want to know what to expect when they use the system. They want to know how much it will cost. They also want it to work with the tools they already use. These things are just as important as making sure the system is totally decentralized.
When you start with these ideas it affects a lot of things. For example it affects how much people pay for transactions. It affects how people get information from the system. It even affects how the system is updated and how problems are fixed. Some of these choices might limit what people can do in some ways.
They also make other things easier, for Vanar and its users. The main thing to think about is not whether these choices are good or bad but that they decide how the system will work over a time. The system will be shaped by these tradeoffs. That is what matters. The system and its performance will depend on these choices.
Systems that cover areas like gaming, metaverse environments services that use Artificial Intelligence and tools for brands also have to deal with a lot of coordination problems. Each of these areas is changing at its speed and this puts stress on the system in different ways. What works well for a game may not work perfectly for making sure a brand is doing things right or, for work that is driven by Artificial Intelligence.
Over time the system has to either find a way to work with the rules or pay the price for supporting different needs.The systems have to do one of these things. Both ways are going to make it harder to maintain the system. This will cause tension in the way it is built.
This is the point where second-order effects start to take over. The things we do to help the ecosystem grow at first can later cause problems with how resourcesre used. The shortcuts we use to make it easy for developers to get started can become obstacles to performance. The connections we make to help people use the system can become rigid and hard to change. These are not mistakes, in the design.
Rather what happens when we pick a path and stick to it as we actually use the system. We have to think about the ecosystem and how it will grow over time and consider how our decisions will affect the ecosystem and the people who use it. The second-order effects of our decisions can be significant. They can impact the ecosystem in ways we do not expect so we need to be careful and think about the long term effects of what we do.
Markets and the stories people tell about them usually take a while to catch up with what's really happening. People tend to focus on goals like getting a lot of users creating a big ecosystem and making popular products such as metaverse platforms or game networks. The hard work that goes into keeping these systems running over time, like handling updates without causing problems making sure old systems still work dealing with unexpected demands and managing when things go wrong is often not considered when people first decide how much something is worth. By the time people start to notice these things the main structure of the system is already set in motion. It is hard to change.
When I look at Vanar through this lens I am less interested in the list of supported verticals or the promise of scale and interested in how the Vanar system is expected to age over time. How does the Vanar system handle failure when things do not go as planned? How costly is it to evolve core assumptions in Vanar once applications, like Virtua Metaverse or the VGN games network are deeply embedded in Vanar?How much operational complexity is pushed onto developers and partners who use Vanar and how much of this complexity is absorbed by the Vanar base layer itself?
These questions do not have answers and they are not the kind of things you can sum up in a few words. The Bitcoin system and other systems like it are very complex. They are the kinds of questions that only become clearer as the Bitcoin system accumulates history of being used.. They are also the questions that determine whether the Bitcoin infrastructure can remain coherent be maintained and be trustworthy, over time. The Bitcoin system has to be able to answer these questions if it wants to be adopted by a lot of people.
In the end the long-term viability of any such system comes down to a single foundational issue: when the environment changes and it always does—does the architecture allow the system to adapt without breaking the assumptions that made it useful in the first place?
@Vanarchain
#vanar
$XPL

Când vorbim despre tokenomics, de obicei începem cu idei. Oamenii spun că stimulentele ajută la aducerea tuturor pe aceeași pagină, mențin rețeaua în siguranță și o fac să crească. Facem ilustrații care arată cum se mișcă valoarea și responsabilitatea. Dacă totul pare echilibrat și are sens, credem că planul este bun. Există o idee că, dacă ceva arată bine pe hârtie, va funcționa bine în viață. Tokenomics se referă la modul în care aceste stimulente și rețelele funcționează împreună și tokenomics este ceea ce încercăm să înțelegem. Tokenomics este un subiect, dar adesea credem că, dacă putem să ne concentrăm pe elementele de bază, restul tokenomics se va așeza la locul său.

It started with a question that bothered every single engineer and every regulator who saw blockchain become popular. The question was this.Can we really have privacy and follow real world rules on a ledger like blockchain? This is a deal, for blockchain.
In a world where financial markets move trillions daily, where institutions must balance confidentiality and transparency, the answer seemed elusive
When we are not paying attention to the numbers and all the ups and downs of the stock market that is where the real work of systems takes place. Most of the time people talk about Dusk and the bigger group of finance systems they focus on ideas. People talk about Dusk.
Things like being able to control your privacy or following the rules that big institutions have to follow. They make it sound like these are things that you can just turn on or off but that is not the case, with Dusk and decentralized finance systems. Dusk and decentralized finance systems are not that easy to understand.
When you look at things from the point of view of a systems engineer these things are not features. They are decisions about how the system is built. When we look at technical systems over a long period of time we see that the ideas that seem the best at first often do not work well in the long run because of the problems that come up when they are actually being used.
Most of the talk, about adoption is missing a big problem. The traditional finance system just cannot use a ledger where everyone can see all the information. Imagine a bank having to broadcast every client's sensitive trade data to the entire world just to settle a transaction. It’s a non-starter. But that’s where Dusk gets interesting. They are not just building another fast L1—they are building a professional-grade environment where privacy and compliance actually coexists.
@Dusk
#dusk
$DUSK

Oamenii de obicei cred că personalizarea este un lucru. Când vorbim despre asta, spunem că este ca și cum am fi liberi. Putem muta lucrurile în jur, schimba părți, schimba modul în care facem lucrurile și face să pară că este al nostru. Unele sisteme, cum ar fi Plasma XPL, duc această idee mai departe. Ei cred că a putea schimba multe lucruri și a le face în felul nostru este ceea ce face să fie bun. Cu cât avem mai multe moduri de a personaliza Plasma XPL, cu atât este mai bine. Această idee sună bine când ne gândim la ea.
Lucrurile nu sunt întotdeauna atât de simple pe cât par. Conceputurile pot face ca lucrurile să pară plate, știi, ca și cum nu ar fi cu adevărat reale. Când trebuie să faci ceva să funcționeze în fiecare zi și apoi în fiecare an devine cu adevărat complicat. Imaginea lucrurilor nu este atât de ușor de înțeles când trebuie să te ocupi de un sistem care trebuie să funcționeze zi de zi, an după an.

Când oamenii discută despre blockchain în public, de obicei, vorbesc despre imagine. Discutăm despre lucruri precum descentralizarea și transparența. Acestea sunt idei, dar nu spun întreaga poveste. Blockchain-ul este destinat să fie un mod, dar nu este întotdeauna așa cum funcționează atunci când este folosit efectiv. Ce se întâmplă când blockchain-ul este folosit pentru o perioadă și oamenii încearcă să-l repare sau să-l folosească în mod greșit? Din perspectiva oamenilor care construiesc aceste sisteme, acesta este un acord. Blockchain-ul este discutat în termeni de lucruri precum încrederea și programabilitatea. Realitatea modului în care funcționează blockchain-ul este mai complicată decât atât.

People usually talk about privacy from a distance. They do not really think about how things work. The conversation about privacy is often about ideas. Like the basics of cryptography what protocols can promise and what people claim in their papers. It is also about the things that could happen but only the bad things that people think about. In this world privacy is simple. A system. Has privacy or it does not. When the right math is used the problem of privacy seems to be solved. Privacy is, like that. People think about it in a way. The system has privacy. It does not have privacy.
I have worked with systems that need to run all the time for years. The way people think about this is not totally wrong. It is just missing some points. When it comes to privacy it usually does not fail because of some theory. It fails when it is actually being used. Privacy fails when the system is really busy. It fails when people are moving data from one system to another. It fails when people are doing maintenance work.. It fails where the technical parts of the system meet the reasons why people use it and the real world. Privacy fails at these points because of the way people use the system and the way things really work.
What people often do not think about is how tough the real world is for systems. Systems do not just run one time. Then stop. They keep going. They get bigger. The things they rely on change. The people working on them. Go. Rules and laws change too. People who try to attack systems get smarter. After a while the question is not just "is this system private when we first make it?. Something even harder: does this system stay private after many years of making changes dealing with problems finding ways, around things and making compromises?
From a systems engineering point of view longevity is not really about how something works at its best. It is, about how a system works when it is not working perfectly. The thing that makes infrastructure a long time is not how it works when everything is going well but how it works when things are not going well. A privacy mechanism that only works when every part of the system is working perfectly is not very strong. As systems get older people start taking shortcuts they only monitor some things.
They start to assume things without writing them down which can cause problems that are hard to see. The privacy mechanism of a system is what matters and the privacy mechanism of a system should be able to handle problems. The system should be able to handle things when they're not ideal and the system should be able to handle things when the system is not working perfectly.
One thing we learn over and over is how the decisions we make about a systems architecture at the beginning can have an impact later on. When a system is still small we make choices about things like who we trust what data people can see, how we will upgrade the system and what we are willing to sacrifice in terms of performance. These choices become very expensive to change on. We can try to add privacy to a system that was not originally designed with privacy in mind. It is not usually a simple process.
When we add layers to the system we often introduce small problems that can cause big issues, such as people being able to see information they should not or the system giving away secrets through the way it operates. Architectural decisions like these can also lead to problems, with the way the system is run. The rules we put in place to govern it can sometimes get around the technical safeguards we have set up.
That does not mean that systems that are retrofitted will always fail. Many systems are able to adapt. The ability to adapt is often a thing.. Adapting systems is not something that can be done without any cost. The systems become more complicated. It takes work to keep them running. The people, in charge of the systems have to pay attention to them all the time.
They have to make sure that the systems are working correctly. Over time people have to make an effort to protect their privacy. The system does not protect privacy by itself. People have to take care of privacy. Systems that are retrofitted do not always protect privacy by default. People have to work to defend their privacy.
When we build systems with privacy in mind from the beginning we have to think about things. These systems are often more complicated from the start. We have to be more careful about how flexible they're we have to limit what the people running them can see. This has effects. It makes it harder to find problems when things go wrong.
It slows down how quickly we can make changes. It even changes how teams work together and get things done. The people building these systems usually have to give up some ways of doing things at the beginning so that the whole system is safer in the long run. Systems with privacy, in mind like these are just built that way.
The big difference is not which way is really better. It is about knowing what you are giving up when you make a choice. Privacy always has effects that happen later. Having rules can make it harder to get information make it tough to follow the rules or make it slower to respond.
Having rules can make things happen faster but it can also cause problems that are hard to deal with and even harder to fix later. Every decision you make will stop some things from happening. It will also make other things possible. Privacy is like that it has these effects that happen later. When you make a choice, about privacy you have to think about what might happen because of that choice.
Markets and stories about what's happening often take time to catch up with what is really going on. It is easier to talk about the features of something than the limitations of Markets and narratives. It is also easier to show people how something works than to show them how long it will last.. The systems that Markets and narratives are talking about that last, for a long time are usually the ones that still make sense in the world they are being used in even after many years have passed and the people who created them are no longer involved and things have changed.
After watching enough complex systems age, the discussion inevitably comes back to a single foundational question: what does this system require to remain faithful to its core guarantees as everything around it changes? Privacy that actually works is not the version that sounds most compelling at inception but the version that can survive maintenance, pressure, and time without quietly eroding.
@Dusk
#dusk
$DUSK

When people talk about blockchain projects they usually focus on what the projects can do how fast they work or the new kinds of security they use. They say things like transactions regulatory compliance and high-performance finality like these are easy to do and running blockchain projects on a big scale is not a big deal. Blockchain projects are often discussed in the news at meetings or even among experts and people usually talk about the features of blockchain projects. The real challenges of using blockchain projects, in the world are not always considered. Blockchain projects are complex. Running them at scale can be very difficult.
Usually people talk about the idea of something in a general way. They discuss the things about it the theory behind it and sometimes they show how it works in a very controlled environment. This is what happens most of the time when we discuss the concept. The concept is usually explained in terms of advantages and theoretical guarantees. Occasionally there are demonstrations of the concept, under controlled conditions that're almost ideal. The concept is what we are focusing on.
When you look at systems for a long time you can see why people think this way.. It is not the whole story. The real world is a messy place. Networks are always changing. The amount of work to be done can suddenly get very high without warning. Software has to work with other systems that do things differently and have different limits.
Some things seem easy to understand when you read about them. Private ledgers, succinct attestation and multiple transaction models.. When you really use the system a lot you find out that these things can affect each other in complicated and sometimes surprising ways. Complex systems are like this because they are made up of parts that interact with each other in complex ways and this is especially true when complex systems, like private ledgers and multiple transaction models are used together.
The clever cryptography is not usually what fails first. It is the assumptions people make about timing and communication and coordination that start to fall. People make mistakes when they think about how these things work. The cryptography itself is usually pretty strong. The assumptions about how it is used are what really matter. The assumptions, about timing and communication and coordination of the cryptography are what start to cause problems.
I have learned something from my experience. It is that the decisions we make at the beginning, about how we build something have an impact. For example how the different parts of the system talk to each other how we make sure everyone agrees on things and how we keep peoples information private when they make transactions. These are all important choices.
Once the system gets big and a lot of people are using it it is very hard to change these things. The way we format our data the rules we use to communicate and what we expect from the network all get tangled up together. This makes it expensive and risky to try to make changes later on. When we are talking about systems that handle peoples money and are supposed to keep their information private the stakes are even higher.
The privacy-focused financial systems are an example of this. Regulatory compliance and auditability and confidentiality are really important. They are not things that are nice to have. They are things that we have to do. If we do not think about compliance and auditability and confidentiality when we start something they can really get in the way and limit what we can do with it. Regulatory compliance and auditability and confidentiality can make it hard to make changes or do things differently if we did not plan for them from the start.
I want to make it clear that I am not saying we should not try things or take risks. This is about thinking about the choices we make. If we build a system from the beginning with the idea of following rules, in mind it might seem like it is moving slowly at first. On the hand if we focus on making the system fast or using new types of cryptography and then try to add in the rules later we will have a lot of problems to deal with.
It is very hard. Takes a lot of time to add accountability to a system that was not designed for it. This usually ends up being more expensive than if we had just included it from the start when we were building the system. When you think about it neither way is really good or bad. What is important is how these choices play out over time as the system gets older. The system is what matters and how the system works is what we should be looking at. The system will change as it ages.
When a system runs for a time you start to think about other things that can go wrong. Things like maintenance. What happens when the system fails. You also think about how the system can handle stress. Problems like network issues and small mistakes in cryptography are not rare. They are just what happens when a complex system has to deal with things it cannot control. The system might be able to do a lot of things fast but that does not mean much if it cannot handle things like nodes leaving the network, new software or changes in rules. The ability of a system to last is not about what it can do. Durability is what matters and durability is rarely, about how powerful the system is.
The thing that really matters is being able to handle shocks and keep going. This means the system can adapt to things that happen and still work properly. The system has to keep doing what it is supposed to do without changing the things that it is based on. The system has to keep these things safe so it can continue to function in a good way. This is really, about the ability of the system to absorb shocks.
There is also a side to this the difference between what people say the market is doing and what the engineers are actually doing. People get really excited about what a system can do when it is used by itself.. People do not think about all the work it takes to keep the system running how hard it is to monitor and how much it costs to make sure everything is okay.
These things are not obvious until the system has been running for a time. The people who use the system the people who invest in it and even the people who regulate it often think that it will always be private and fast.. That is not true. There are limits to how much the system can handle. If you push the system hard it will start to break down and people will not trust it anymore. The system and the trust people have, in it will both be affected.
I keep looking at how things change over time. It always brings me back, to one basic question: can a system really balance privacy guarantees and regulatory obligations and performance targets in a way that will work for years not just a few months? The blockchain system is what I am talking about. This question and how hard it is to answer is what really determines if a blockchain system can really last in the world of finance. You do not figure this out by looking at benchmarks or reading whitepapers or looking at how neat the protocolsre.
This is figured out when you look at how things work over time. You have to put in a lot of effort to make upgrades and see if the ideas you had, at the start actually work out in the run with your software or system or whatever it is. The thing is, you have to see if what you thought would happen with your early architectural assumptions actually happens in life.
When I think about privacy-centric financial blockchains, I care less about what is theoretically possible and more about the interplay between design, context, and longevity. Innovation is necessary, but it is resilience that endures. The conversation that too often gets overlooked the hard, sometimes tedious work of aligning cryptography, network architecture, and compliance under messy, real-world constraints is exactly what separates a passing demonstration from infrastructure that can survive and evolve over a decade.
@Dusk
#dusk
$DUSK

Voi scrie asta într-un mod care sună ca o persoană. Vreau să păstrez părțile și să fac să sune serios, dar nu prea formal. Ideile principale vor rămâne la fel. Voi folosi un ritm și un mod de a vorbi mai natural. Acest lucru va face să sune ca un inginer care vorbește și se gândește la lucruri în timp. Ideile inginerului vor rămâne intacte. Inginerul va folosi un mod de a vorbi mai natural și reflexiv.
Când oamenii vorbesc despre Vanar, de obicei o fac într-un mod general. Ei spun lucruri precum Vanar ajută la conectarea lucrurilor din lume cu lumi digitale. Asta înseamnă să iei lucruri și să faci versiuni digitale ale acestora, astfel încât să fie mai ușor să le deții și să le tranzacționezi. Ideea de Vanar este simplă. Sună bine. Este ușor de înțeles și de explicat altora. Oamenii le place ideea pentru că se potrivește cu ideea de blockchain, care este o nouă modalitate pentru oameni de a avea încredere și de a colabora. Vanar este o parte din asta și oamenii apreciază că face mai ușor să mutăm valoare între diferite sisteme.

When we talk about blockchain technology people often discuss payment systems for merchants. These systems are built using things like Plasma XPL. The talk around these systems is often about how they can handle a lot of transactions do things quickly and save money. These are things to consider when making a payment system.. Sometimes people do not think about the hard work that goes into making a system that people can trust and that works well over time. Blockchain technology and payment systems, like the ones built on Plasma XPL need to be reliable. We need to think about how blockchain technology and payment systems can work for merchants.
When we think about how merchant payment systemsre designed they usually focus on a few key things. They need to be fast so people do not have to wait a time for their payments to go through. They also need to be able to work without being controlled by one point and the fees need to be low. These things are important to businesses and people who buy things in places where payments need to happen quickly and easily.
Plasma XPL is a system that is built on top of Ethereum. It is interesting because it tries to move some of the work of processing payments to chains, which helps take some of the pressure, off the main Ethereum chain. This makes it easier and less expensive to use Ethereum.
Plasma XPL is a layer-2 scalability solution, which means it is a way to make Ethereum work better and faster. But it’s easy to overlook the deeper, long-term engineering issues that arise when systems of this nature are deployed at scale, particularly in dynamic, real-world environments where failure modes are difficult to predict.
In systems engineering there is a truth that really matters: the big decisions you make at the start of a project can have lasting consequences that you cannot change.The Plasma XPL design is an example of this.The people who made Plasma XPL thought that Plasma XPL sidechains could handle transactions on their own without needing help, from the main Ethereum chain.This was an idea when they were building Plasma XPL.
The Plasma XPL system was built with this idea in mind. This idea was good at the beginning when the system was not used a lot the number of merchants and users was small. Everything was still being tested. The system was new then.. As the system gets bigger the ideas we had, at the beginning do not always work. The system idea worked early on. The system had users and merchants early on. As the system grows we find problems we did not expect with the system.
We have a problem with Plasma XPL. This is an example of how important decisions about the systems design can cause problems later on. Plasma XPL started with sidechains, which seemed like an idea at the time. They were supposed to help the Ethereum chain by taking some of the work off of it and letting more things happen outside of the main chain.. Then more people started using Plasma XPL and more stores began to accept payments, with it. As all these transactions started happening at the time Plasma XPL started to have trouble working properly. Plasma XPL is still having these problems because of the way it was designed. The assumptions that worked well at low scale like sidechains being able to independently handle transaction processing begin to show cracks.
It’s an important reminder when designing complex systems, we need to think beyond the immediate needs and consider how the system will adapt over time. The challenge is not in creating a system that works today it’s in creating one that will continue to work as it grows. This is why long-term planning, adaptability, and foresight are critical in systems engineering. Because once a system reaches a certain size, it becomes harder to fix, harder to adapt and harder to maintain.
In the end, the real question is: will this system remain stable and resilient as it scales? That’s the key factor that will determine whether it thrives or falls apart under the weight of its own growth.
@Plasma
#Plasma
$XPL

When we talk about ways of sharing information over computers the conversation usually begins with the basic idea. We look at what the system's supposed to do. For example how does it store information how do people get to use it how do people get rewarded for helping out. How fast is it compared to the old way of doing things. The papers that explain these systems and the posts that announce their launch often talk about ideas like storing information in many places or making information that can be used in different ways or keeping information safe, with money. At this level these ideas usually make sense. Are even nice to think about.
What usually gets overlooked is what happens after the plans are done and the system is actually being used every day in a real world setting with real people running it. Things do not always work perfectly. The internet connection is not always great things break sometimes. People use the system in different ways.
From what I have seen as a systems engineer the difference, between how thingsre supposed to work and how they really work is where a lot of problems come from. The system is where most problems start because it is used by operators and it has to deal with imperfect networks and changing usage patterns of the system.
Things do not go wrong with technical systems because the main ideas behind them are bad. Complex technical systems fail because the assumptions that are built into them from the start do not work well when they are used for a time or when a lot of people use them or when people actually use complex technical systems. This is what happens with technical systems when the assumptions, in their architecture are not very flexible.
In software systems that have been around for a time time is the main thing that causes problems. The requirements of the software system change over time. The way the system is used also changes. Sometimes people try to do things to the system when they were not expected to. When the system is first put in place people may take shortcuts to get things done quickly. After a few years these shortcuts become the normal way of doing things.
A part of the system that was only meant to be used for a time can become a crucial part of the system because other parts of the system have been built around it. You do not usually see these things happening when you first try out the system. They make a big difference in the end. Software systems, like these have to deal with time and its effects. Time is what really tests the software system.
I often notice that people do not think enough about maintenance and recovery. It is easy to create a system that works well when everything is working fine.. It is really tough to create a system that still works okay when things start to go wrong.. It is even tougher to make it so that fixing the system is easy and always the same. When we talk about systems they are usually not working perfectly. Some parts of the system are not working right. Some nodes are slower than others. The data is not evenly spread out. Peoples motivations change.. Sometimes humans have to step in and fix things at bad times.
Maintenance and recovery are really important, in distributed systems. When we build systems we have to think about the architecture, from the start. If we do not do this our systems will have a lot of problems that will be hard to fix on. This is what we call debt. Architectures that do not think about this from the beginning will accumulate debt very quickly. We have to consider the architecture of our systems to avoid this kind of debt.
When we first design something we make a lot of decisions about how it should work. We decide how to organize the data, who to trust and how to make updates. At the time these choices seem like no deal. The thing is, these early architectural assumptions can really add up over time.
They can affect the system in ways. For example the way we lay out the data can make it hard to make changes later on. The same thing happens with trust boundaries, upgrade mechanisms and economic coupling. These choices might seem small when we make them. Years later they can limit what we can do.
It is really hard to go and add new features to a system that was not designed with them in mind. For instance trying to add observability to a system that was not planned to have it can be very painful. It is also difficult to introduce rules to a network that was designed to be static. This can cause a lot of problems with how the different parts of the network workIt is also hard to separate things that have become closely linked over time. When concerns have become economically or logically entangled it is rarely easy to pull them.
This is why systems that are changed after they are made feel different from systems that are made with a way of working in mind. Neither way is better than the other. Systems that are changed after they are made are often more flexible. We can learn from what happened before. Systems that are made for a purpose are often better because they have clear rules and limits. The problem is that we have to choose between making something that can be used for things and making something that is easy to understand.
Systems that can be used for things are good because we can use them again but they can also be used in the wrong way. Systems that are made for a purpose can be more predictable but they might not work well if our understanding of the problem changes. Systems that are made for a purpose like the ones we are talking about can be too closely tied to what we thought the problem was, at the beginning.
When we think about systems from an engineering point of view the things that are really interesting are not about what the systems can do. About what happens when things do not go as planned. For example how does the system work when it is not growing fast as it used to? What makes people want to take care of the system of just adding new things to it? Who has to pay for it when the system needs to be changed or updated because things did not work out as expected?
It is also important to think about how easy it's to notice when something is going wrong slowly compared to when something goes wrong all of a sudden. These are not the kinds of things that you can see when you are testing the system. They are the things that the people who use the system and take care of it have to deal with every day. The system and its effects on people are what matter, in the run.
Alternative design approaches normally come from starting points not from some big idea. When you think that data can be changed you make a plan for how to control and work together. If you think data should never change you make a plan for having copies and dealing with the cost. If you think the people running the system are experts you make the system more complicated on the outside.
If you think they are not experts you make the system handle the parts on its own. Each of these starting points has its costs and just because you do not see these costs does not mean they are not there. Alternative design approaches, like these have costs that you have to think about when you're designing a system.
Markets and the stories people tell about them are usually behind the times. When these stories are first being told it is the people who're clear and confident about what is going on that get rewarded.. When it comes to actually making things work it is the people who are humble and able to adapt that do well.
The thing is by the time we really understand how something works people have already made up their minds about what it's. So it becomes very hard to change what people think about it just like it is hard to change the way it was built. Markets and the stories people tell about them are, like this.
After watching many systems mature, stagnate, or quietly fail, I find myself returning to the same foundational question when evaluating any new protocol or platform when this system is no longer new, no longer growing, and no longer forgiving of mistakes, who will carry the ongoing cost of keeping it correct?
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