What make Social Networks addictive (and what we can learn for software development )

Social Networks have become a social norm today. Almost everyone tends to have at least one profile on one of platforms such as Facebook, X, Tiktok, and a few others. I was on Facebook when i was a student and honestly I did not get what actually Facebook was and why people use it. I wrote something on my wall, then I got a notification saying a friend liked my post. I also saw my friends posted something funny on their walls, but I did not hit the like button, not because it was not funny, it was because I did not aware that I should press like button if I found it funny. I left Facebook because playing games is much more engaging than this thing. Until when I came to university, my friends too, but we live in different districts and study in different universities. We lived far away and it was really hard to meet frequently like when in school. Call & SMS is costly for long conversations, and it is not fun too. Then I back to Facebook because most of friends was using it too. We got free messaging & video calls. We can share thoughts, opinions, discussions via comments and showing support via the like button. We share moments by uploading photos and videos. We did not meet in person frequently like before, but we feel that we know what others are doing. Until I saw first news about Social Network Addiction! And I did not understand. How does a tool that simply informs its users about someone about something, become addictive ?

At first glance, Facebook, X, Tiktok or any Social Networks, looks simple: “someone posted something, then you see it.” But the addictiveness doesn’t come from the information itself — it comes from how that information is delivered, timed, and socially framed. This post will reveal the real mechanism behind it, or at least the core part.

Before understand the whole mechanism, it is important to understand some artifacts that build up the mechanism: The Slot Machine Effect, Social Validation Need, FOMO, Stopping Cues, Personalization, Triggers and Social Obligation Pressure.

1. The slot machine effect

The slot machine effect is a nickname for a behavioral psychology: Variable-ratio reinforcement. Simply put, “you repeat an action because the reward is unpredictable but sometimes great.” It is likely what happens inside gamblers’s psychology. When using Social Networks, each time we open it, what we get is random. Sometimes, there is nothing interesting. Sometimes, there is a funny post, a like, or a message. Sometimes, there is something emotionally strong such as a drama, a praise or a surprise – and we feel good. This unpredictability trains human brain to try again because “maybe the next scroll will be good.” . That’s what keeps users opening the application and keep scrolling, like a hunt for emotions. And human loves go hunting, this activity is deep rooted in brain since very first day of human kind. But what we hunt is not simply food anymore.

2. Social Validation Need

Humans, as a nature, care deeply about how others see them. This is a survival factor, evolved and deeps rooted in human brain for thousand years, since Tribal Age when there is no law and what tribal members perceive you determine you alive, or die. Our brain is wired to care about Being accepted, Being noticed and Not being rejected. Social Networks do not reinvent this, it measured and amplified it. In real life, validation is subtle. It is a feeling via daily interaction between people. Each person even has their own way showing validation. Each culture has its own custom to visualize validation. Here on Social Networks, validation is visualized by number of likes, comments & shares. 1 like vs 100 likes! 0 comments vs 20 comments! 0 shares vs 10 shares! Comparison is triggered. This turns Social Validation into something closer to a score system than an natural feeling. Social Validation now becomes Social Comparison – when we evaluate our opinions, abilities, and worth by comparing us to others.

As a blending of Social Validation and Social Comparison, human brain tends to translate Likes into Approval, Comments into Attention, and Shares into Influence. It is a translation from numbers to a feeling. It is a false translation because these numbers can be manipulated by many ways: psychology tricks, ads campaign, payment or from clone accounts. But it does not easy to escape that false translation. Because of Cognitive Ease – human brain loves simple things – and here interpreting Likes as Approval is easier than real life approval which can be complex: tone, facial expression, context. This triggers dopamine (reward signaling) as well, making us want to check reactions, post again, stay engaged.

3. Stopping Cues

Social Networks, at some extents, is likely a TV shows, or books, when it also provides content. The diffs are, Social Network content is made by anyone without necessary knowledge, skills and permissions. People on Social Network can be not directors, not scholars, not professor but nothing stop them to tell stories, teaching or bragging. TV shows or books have endpoints. We know when it is end and take time to relax. Social Networks removes that, on purpose.

A common design pattern often used in Social Networks is Infinite Scroll. This design keeps users in a continuous loop with no friction to stop. Human brain relies on boundaries to end activities. End of a chapter, End of a page, End of an episode is cues for brain to stop. Infinite scroll deletes those cues. Without a clear “end,” human brain defaults to keep going on. It pairs perfectly with the Slot Machine Effect when Unpredictable rewards keep behavior going longer than predictable ones. This also exploit the Completion Bias – the psychological tendency to prioritize easy, quick tasks over more important, complex ones to gain a fleeting sense of accomplishment and a dopamine boost. This bias tricks the brain into valuing the “done” feeling, often leading to wasted time on trivial tasks rather than high-impact. And here, keep scrolling feels easier than close the app.

4. Fear of missing out (FOMO)

Fear of Missing Out (FOMO) is a psychological concept describing anxiety when other people is having rewarding experiences without their participation. Simply put, it says that: you can feel anxiety when you see others are winning. This feeling is exploited strongly on Social Networks, where people frequently & easily compare their lives to others profiles, via New Feeds, number of Like, Comments & Shares, eventually leading to feelings of inadequacy or exclusion. FOMO reflects the human need for Social Validation, and also stemming from Social Comparison – when a person must know, must do, or must have something to be belong to a group. FOMO people often experience greater dissatisfaction and impulsive decision-making.

Social Networks amplify FOMO by providing constant updates about others’ activities, achievements, and lifestyles. This can create a loop of checking, posting, and comparing to other. Users can feel anxiety when comparing to other. And then the brain want some relief when it feel anxiety. Turns out the most relieved action for this anxiety is to check if they are what they are. Checking via Social Networks app is faster, easier, even anonymous so it is the best choice for brain – Cognitive Ease again. Although feel anxiety, users do not flee away. This is classic Negative Reinforcement: a behavior sticks because it removes an unpleasant feeling. The Social Networks apps, one hand bring anxiety to users, on another hand, become a fasted way for user to relieve that anxiety. And it become addictive because it is a fasted way for user to get relief.

5. Personalization

Naturally, people don’t like people that have different opinions. If a Social Networks only shows content that contradicts user’s perspectives, they won’t use the app. To keep people using Social Network, it needs to show what users like to see. And to a human, there is nothing better than seeing what they already believe. This is Confirmation Bias – when human brain automatically filters out what not support the existing belief and only focus on what support that belief. Exploiting this bias, Social Networks analyze users’s behaviors and only show what a users tend to like. Time spent on certain post, likes, comments, shares, or even demographic info, or even avatars, is inputs to an algorithm that predicts what a user might like. For a long time watching people interacting on Internet, these algorithm seem know what its users like. And when that algorithm only show only user what they like, it makes users feel that the whole Social Network is people just like them – this is Halo Effect when humans use a small cue to judge the whole thing. Because users like something posted on a Social Network, they might like that Social Network as well. This illusion keeps user returning because no one can resist seeing what they like.

6. Triggers

Above artifacts function based on many psychological instincts of human being. Because it is instincts, it is hard to resist. But instinct does not function all the time. It needs external triggers.

Human has language, in written format. Human brain can translate symbols into meaning. Depends on what meaning is translated to, it can trigger instincts just like a deer hears sounds in a bush. Simply put, human instinct can be triggered via text. We all may have a friend that is triggered when hearing or seeing certain words. It can be any word, but depend on their experiences in the past, words can bring different feelings. Social Networks exploit these well via Notification. Notification sent to user does not simply informing some events. It’s message is designed to trigger human instincts. Example:

“You were mentioned in a comment” → triggers Social Validation (“someone is talking about me”)
“Someone liked your post” → triggers Social Validation (“people value what I shared”)
“You have 5 new notifications” → triggers FOMO (“what did I miss?”)
“Your friend just posted after a long time” → triggers FOMO (“this might matter”)
“This is getting a lot of attention” → triggers Social Validation (“this could be important or trending”)

Each message is short, but it is not neutral. It is designed to activate specific psychological responses such as curiosity, belonging, urgency, or FOMO. Over time, the brain begins to associate these phrases with emotional outcomes. This is why people feel an urge to check immediately, even when they were not planning to.

In this way, notifications function less like messages and more like triggers. They convert language into instinctive reactions, turning attention into a reflex rather than a deliberate choice.

7. Social Obligation Pressure

Social Obligation Pressure is the feeling that you owe a response, attention, or presence because of social expectations—even if you don’t actually want to engage at that moment. This obligation come from Fear of Negative Judgment. This fear is amplified by features such as: Read receipts or Typing indicators, which is commonly used in Chat Box. This is natural feeling in human when it helps to forming social. But on Social Networks, people do not see each other face, so by visualizing via indicators, Social Network ensure that Fear exists and push user engaging because no one want to be seen as impolite. It’s not just “I should reply” — it’s more like “If I don’t, people will think something bad about me.”

Social Obligation Pressure, or Fear of Negative Judgment, targets identity, not just curiosity. Humans constantly assume they are being evaluated. We predict how others might interpret our behavior. We try to avoid being seen as: rude, ignoring, ungrateful or socially incompetent. This fear is not about the action itself —it’s about your brain anticipates the meaning others might assign to your action – which may not true. Many times, when we reply to someone on Social Networks, Not because we want to — but because we want to avoid negative judgment. Read receipts removes plausible deniability, Typing indicators creates expectation of response, Online status signals availability, Notification creates urgency. All features are designed around Social Obligation Pressure.

Put It All Together

Social Networks profit from advertisement, where the more users addicted, the more revenue it earns. By combining all above artifacts, Social Network applications train human brain a behavior loops by exploiting human biases and instincts to keep users spending at much time as possible on its app, by following steps:

From a free tool that solves real life problems: Communication – such as Messenger, Chat, Video Calls, etc…
Triggers – the Notifications – is added to trigger anxiety, or FOMO
Social Obligation Pressure pushes users to engage: reply messages, check information, etc
Users Open the Social Network app (e.g. Facebook / TikTok)
Personalization algorithm shows highly relevant, easy-to-consume content to users
Slot Machine Effect: users get unpredictable rewards while scrolling
Social Validation Need: users eventually get likes/comments that give dopamine hits
No Stopping Cues: no natural point to exit leads to doom scrolling
After leaving / pausing using Social Network: anxiety, curiosity, or social pressure still lingering in brain
Social Networks introduce new trigger forms to make user urge to check again, then back to Step 2 !

And we already all heard and knew about real life harms caused by social network addictiveness — from wasted time and reduced productivity, to anxiety, low self-esteem, and constant comparison. Over time, it can lead to irritability, anger, and strained relationships, as attention is pulled away from real-world interactions. In more serious cases, the cycle of validation and comparison can deepen emotional distress, contributing to isolation and even self-harm. What makes this especially concerning is that these outcomes are not caused by a single feature, but by a system of reinforcing loops that continuously pull users back in, often without them realizing it.

Be aware about the mechanism behind Social Networks can be the first steps of escaping the addictiveness loop. If you have someone that is addicting to Social Networks, let share this post to them!

Lessons for Software Design

Although bad side effects of Social Networks is undeniable, but the high user engaging ratio of Social Networks app is also a dream to any software company. As a software creators, we all want our applications are used daily, especially when competition is getting high every day. We still have a way of applying mechanism observed in Social Networks for good purpose. It is long post here already and I will continue this part on next parts. To not be missing out, please subscribe so you can get a notification when next parts is available:

9 Reasons Why You Never Hit Your Goals (and what actually works)

Everyone loves setting goals. New year, new plans. New week, new habits. New project, new ambitions, etc. But if looking honestly, most goals fail, isn’t it! Ironically, they don’t fail because they’re too hard, they fail because they’re vague, emotional, or just unrealistic. If you find yourself missed your goals too many times, this post is for you. But this post will not provide you motivation, this post will expose your misperceptions, and knowing these misperceptions is the first step toward your goals.

1. You are making wishes, not goals

This is the most common misperceptions can be seen when looking into people’s todo list, or new year resolutions. People usually write their wishes instead of goals and completely not aware about the diff. For example, it is easy to see these lines in someone’s todo list: “to be better at something”, “build a great app”, “be rich”, “be happy”, “be confident”, etc. These lines won’t make any outcome, they are just wishes in a world without genie. A goal must be Specific & Measurable. And because it is Measurable, it will be Achievable.

To be Specific & Measurable, each goal must be written in a simple sentence using 1 number, 1 noun & 1 verb and a deadline. Example:

deliver 1 feature every 3 days
publish 10 blog posts in quarter 1
run total 15km each week
save 50% of salary each month
read 1 page of any book each day
…

If you can’t measure your actions, you can’t achieve the outcome. Focus on number, be familiar with scoring yourself. Be a project manager of your life, avoid saying vague words, be specific! Writing todo in this format will be the first step of realizing any goal. When all metrics are met, you goal! When metric is not met, at least you will know why.

2. You expect outcome happen over night

Good things take time. It is one rule for any goal. Outcome comes from concentrate, commitment and consistency, not from your commands. Outcome is compounded from tiny results each day.

Setting goals make illusions of fast results. When you set a goal, your brain immediately imagines the outcome, especially if you have an imaginative brain, you might lock yourself in your imaginary world without notice the boundary with your reality. Although the outcome is imaginary, it somehow triggers dopamine in your brain and you “feel” success. That mental picture feels real but you skips the process entirely. You likely borrow dopamine from your future but any borrowing need to be paid. And when life pull you back to its reality, when someone or something reminds you about your goals, which are not completed yet, a crack appears inside your world and that crack hurts a lot. It triggers other toxic hormones as well. And this might explain symptoms that many people avoid to mention again their goals, or go outrage if someone mentions it.

Expecting fast outcomes creates a dangerous loop: You start strong, You don’t see results quickly, You feel discouraged then You quit or switch goals. This loop waste your time, energy and mind a lot and it is harmful than you think. Not because the goal was wrong, but because your timeline was unrealistic. Treat your goals as seeds. It will grow slowly but for sure. Most meaningful outcomes come lates because it requires many many suitable conditions. They usually come after weeks or months of invisible effort. So, when making goals, at the deadline part, give it time, count in month is a good starting point.

3. You depend on emotions, not habits

Motivation! yeah it is the emotion everyone love. People even pay significantly to just attend some meetings that “sell” motivation. But then that motivation expired right after you left the meeting. It’s expensive, and smell like scam. Your brain don’t need that external motivation. You don’t need fake motivation.

Motivation is unreliable. At the beginning of any goal, motivation feels strong. You’re excited, focused, ready to act. But motivation is temporary. Some days you’ll feel tired, distracted or simply won’t feel like doing anything. You can burn out. No one gonna compliment you every time, everywhere. Not everyone understand your goals evenly. If your actions depend on how you feel, your progress will always be dependent on external conditions, aka you lose the control of your life.

Habits solve this problem by removing the need to decide what to do every day. Build a daily routine that make you harder to fail than succeed. No debate. No negotiation. You don’t rely on energy—you rely on structure of a day you will spend. Remember sleepy days, rainy days, hot as hell days but you still have to complete 5 classes before go to bed. That is a sample of how to complete a goal. Structure your timeline and turn it into habit. Sciences proved that any your actions can turn into habits after 3 weeks. After that threshold, you will act unconsciously toward your goal.

Habits are not just actions—they shape your identity. You don’t “try to work out”, you just run every morning at 5AM. You don’t “try to learn” , you just studies every night at 8PM, etc. Be specific about when you do what and repeat it daily. You can spend 1 month to test this theory and see (not feel) the result.

4. You review other too much instead of yourself

Comparison! It is not easy feeling but everyone unconsciously does that, at least for a while when they were younger. This is normal behavior and is a source of motivation. But because we learn to not depend on motivation here, comparison is unnecessary too. Comparison slows you down more than you think.

It’s easy to spend time analyzing others on what they’re doing, how fast they’re growing, what strategies they use. It feels like learning, even productive when you absorb new information. At some extent, this gives you hints on how to do a stuff and keep you moving, but if too much, it counter attack you by wasting your time. Your progress stands still while you make comparison with other. In the worst part, when you focus too much on others, two things may happen: You feel behind too far – then you feel discouraged, or You copy blindly – then you lack of direction. You might give up or try doing too many things, all at once, which is a fail-for-sure strategy. You end up reacting instead of building. You’re measuring your progress against someone else’s timeline, resources, and starting point—which you don’t fully see.

Progress doesn’t come from observing others. It comes from observing yourself. If you don’t review your own actions, you miss: what worked, what didn’t, where you wasted time, where you improved. Without this loop, you are doomed to repeat the same mistakes. Never expect that same methods would produce different results. Ignore others, focus on yourself. Track your progress toward your goals. Update the progress daily. Do not care about what other post on their social profiles such as LinkedIn or Facebook, many times they lies, or just exaggerate about themself. Real professional shows their result, not lines on their CV.

5. You work hard, but not deep

Given that you already have Specific & Measurable goals, with right habits that serve the goals, and completely ignore other people on social networks. Now you are going to be busy: each day, you answering messages, switching tasks, reacting to notifications, reading a few articles, check some news, write some code, draw something, and repeat that routine for 10 days already. You got busy all the time but your none of metric you set are met. What is wrong ? Is the right goal not just enough ? This busy seems not productive. It is distraction actually. It is not “deep” enough. Deep work is something like: You spend 7 continuous days to make a first version of your app then you spend 8 hours to complete a drawing, then you spend 8 hours to collect relevant information from articles and news, then you spend 2 hours to reply and react to messages and notifications. Same 10 days spent, but the result will be different.

Deep work is to focus in one goal in a long timespan, long enough to deliver a meaningful result. Don’t switch tasks too much because your brain is a single-threaded machine, not a multi-threaded one. Switching tasks can make you feel busy, productive, and do more but in fact, it creates movement, not meaningful progress. You waste time and energy when switching tasks because your brain has to switch the context, and lose the short-term-memory that is important for resolving difficult issues.

People has tendency to choose working hard instead of deep working. Working hard is easy to see, has small wins and human brain loves that feel. Deep work requires patience, honesty and creativity. Deep work does not gives instant satisfaction by small wins like hard work, but it forces you to confront what you don’t know, where you struggle and accept that how slow a progress can be – which is not an easy feel to most of people. And human brain has a default mode to choose the easy one. Working hard is good, but it is not enough to complete goals, meaningful ones!

6. You sense, but not score

How do you know you are doing a good work?

Let say you already spent 1 months focusing on one goal such as making a simple software, or building a website, or learning a new language. You barely switch tasks in 1 month. You focused on one goal. Good job, you are very close. Now it is the time to scoring yourself. And score is a number. For example for above sample goals, let gather data about: how many users want to use your new software, or, how many people go to your website, or, can you take an official language test yet, etc. Does that number met the metric you set ? If yes, wonderful, if no, lets find out!

It is completely okay to not be 10/10 per goal. It is not even matter. The honesty to yourself is matter and it will adjust your strategy when it sees that scores. Those scores act as feedbacks from reality. It measures the gap between your assumption and reality and can tell you whether you are on the right track. If the goal is not met even you escaped above 5 misperceptions, the wrong part is in your method, your approach, aka, in how you work on specific tasks. There must be some missing steps, or overdo steps, or wrong assumptions, or underrated steps.

This scoring habit is to calculate effectiveness. If it is not effective yet, let experiment other methods and again gather scores. After a few try, scores can tell you what works, what do not, and what you feel it work. Focus on what actually work only!

Scoring yourself has another psychological effects. It can train your brain to be open minded, flexible when you willing to adapt multiple methods for same goal, and get rid of some cognitive biases. Human brain has many cognitive biases, the common ones that can be fixed by scoring yourself are:

Confirmation bias: You notice only evidence that supports what you already believe and ignore what contradicts it.
Self-serving bias: You naturally credit yourself for what works and blame external factors for what do not work.
Effort justification: You assume that because you put in effort, you’re making progress.
Recency bias: You overvalue what happened recently.
Optimism bias: You overestimate how well things are going, or will go.
Availability bias: You judge based on what’s easiest to remember.
Consistency bias: You resist admitting that your current approach isn’t working because you’ve already committed to it.

Escaping those biases, you can be stronger than ever!

7. You put yourself in wrong environment

Now your are strong, the goal is right, but progress is slow. What’s wrong now ?

Goals are like seeds. Good seeds can grow slowly due to wrong environment. Your progress is also, it speeds up or slows down depend a lot on where you are sitting, what you eat and who you collaborate with. Place, Food and Supporters is the environment that effect your goals the most.

Place – where you actually do the work. It can be an office, at home, or at certain kind of coffee shop. If your space is full of distractions, noise, or easy escapes, your focus will always be fragile. You’ll need constant willpower just to do basic work. Know yourself, measure yourself to understand where is the place gives you most productive work. Some people love work at office, some people love work at home, some love work at a coffee shop, some want to be near the sea, etc. Each person has different soul that decide where is their productive places. Some person has unique fear that decide where is not an easy escape environment. This is likely give you no retreat option so the only choice is moving forward.

Food — your hidden performance system. What you eat doesn’t just affect your health, it affects your energy, clarity, and consistency. Low-quality fuel brain can leads to: energy crashes, brain fog, inconsistent output. You might think you lack discipline, but sometimes you’re just under-fueled. You don’t need a perfect diet, but if your goal requires focus and long term effort, your body needs stable energy supply. So, always feed yourself well, then work.

Supporters — who shapes your standards. You don’t gonna need a big network but you do need the right people. The people around you influence: what you consider “normal”, how high you should aim and how you respond to feedbacks. If your environment tolerates excuses, you’ll make them. If it values growth, you’ll feel pressure to improve. Support doesn’t always mean encouragement or compliments. Most of time they don’t understand what you are doing. It is just their personality. It can be accountability, it can be honesty. Sometimes it’s just being around people who take things seriously. And the best person will be the one already make it, the one already achieve whatever goals you set. Learn from them is the best.

8. You have too many goals

Now you are super strong, your mind can focus, your body is full of energy, your environment is fit. The goal is close than ever. But not just too many goals!

Now here some other cognitive biases emerge! You need to fix them too:

Shiny Object Syndrome: You’re attracted to new ideas simply because they’re new then you back to switching tasks.
Opportunity Cost Neglect: You focus on what you gain from a new goal—but ignore what it costs then You overload yourself without realizing what you sacrificed.
Overconfidence Bias: Because things are going well, you assume you can handle more. But you underestimate the cognitive load and split your attention.
Planning Fallacy: You underestimate how long things actually take then you stack multiple goals on unrealistic timelines.
FOMO (Fear of Missing Out): You get more excitement from starting than finishing, so you have a bunch of half-completed goals rather than completed goals.
Identity Expansion Bias: You want to become multiple versions of yourself at once, but then no one can identify who you really are, and eventually you lose opportunities because people don’t remember complex things.

Less is more! At this level, what you need to notice is not about adding goals, but about filtering goals. When everything is working, your biggest risk is not failure, it’s dilution. Time and energy is limited resources, and most of time, life provide you just enough to complete one goal – the one that give you identity

9. You don’t collaborate

Teamwork ? . No, it is not mandatory here.

People often use collaboration and teamwork as if they’re the same. They overlap—but they solve different problems.

Teamwork is about shared execution. Teamwork is about working as a unit toward a shared outcome. Roles are defined, responsibility is distributed, success or failure is collective. No single person owns everything. The team does, and team members might be changed.

Collaboration is combining strengths. Collaboration is about bringing different people with different skills together to have solve a problem. You still stay responsible for your goal. You only involve others when it adds value, aka solve what you can’t. It’s flexible method and often temporary. You can hire, or consult, many experts in short term to help you overcome somethings out of your expertise. For example, when building a software, you can hire a designer in a few months for a final UI design instead of draw yourself. Or when you’re writing, you can have some friends reviews and challenges your ideas. You’re still the owner. Others enhance your work. And don’t forget to pay them, or help them back!

If you’ve already chosen one goal, you don’t necessarily need a full team. What you likely need is targeted collaboration. Jumping straight into teamwork can actually slow you down because teamwork might require more coordination, more dependencies, less flexibility. Stay owner, but don’t stay isolated.

What is Smart Contract ? – explained in plain English

Smart Contract is a contract but instead of written in human language, it is written in a programing language. Like a contract, a Smart Contract defines conditions and financial obligations among participants. Unlike a contract, with a Smart Contract, financial obligations can be executed automatically if conditions are met, without underwriters, lawyers or law enforcement entities.

A contract can protect financial rights of participants only if there is a government enforce and operate. Financial obligations in contracts is money. Money is managed and operated by banks. A Smart Contract is a program and only execute on Blockchain. Blockchain is a network of computers, obey to a protocol that provide services similar to a bank such as : holding balances, transferring value, recording ownership, enforcing rules automatically, and keeping an immutable transaction history.

What Conditions can be added to a Smart Contract ?

Not every statement in contract can be converted to Smart Contract. Smart Contract is a program so it works well with precise numbers and clearly defined if-else conditions such as: money amount, date time, vote counting, temperature.

For example that a company is using Smart Contract to pay employees salary. The Smart Contract can easily implement the agreement that, at every 1st of each month, a fixed amount of money is automatically transferred from the company’s wallet to each employee’s wallets, provided that sufficient funds have been deposited in advance.

Once deployed, the smart contract does not rely on the company’s willingness to pay or on any manual action from accountants or banks. If the date condition is met, the payment is executed exactly as written. If the funds are not available, the payment simply does not occur, making the failure transparent and verifiable to all parties.

In this way, the smart contract replaces trust in the employer or intermediaries with trust in predefined rules and automated execution, ensuring predictable and timely salary payments without human discretion.

However, the smart contract cannot determine whether the employee actually worked, worked well, or should be fired. Those human decisions must be made outside the system. The smart contract only enforces what was clearly defined in advance: who gets paid, how much, and when.

What Conditions can NOT be added to a Smart Contract ?

Smart Contract can not work with Emotions, Quality Judgements, Real Life Events.

For example that a company hires a developer under this agreement:

“The developer will build a high-quality mobile app that meets business needs.
Payment will be made if the work is satisfactory.”

This is where Smart Contract can not replace contract. A smart contract, as a program, can not decide:

Whether the app is “high-quality”
Whether it “meets business needs”
Whether the work is “satisfactory”

These require:

Human judgment
Discussion
Interpretation
Sometimes negotiation or compromise

Smart contracts are excellent at enforcing clear rules, but they cannot replace contracts that rely on human judgment, quality assessment, or trust.

How to save $99/year when build app on iOS

If $99 per year is dust to you then this post is not for you 🙂

If it is not, then please take a look !

A fact is that it will cost $99 per year to be able to publish mobile applications to AppStore. For any indie developers that is at the first step of publishing their app, this cost might cause some hesitation.

In case that your application is simple, which is not depends system level APIs such as GPS, File System, Bluetooth, Background Activities or Push Notification, it is possible to make use of PWA feature that is supported by Safari browser which always available on iOS and MacOS.

PWA stands for Progressive Web App. It is a web app, but can be installed into smart phones like a mobile app. Simply put, instead of accessing via a web browser like Safari or Chrome, users can find an icon on their phone, tap it and open the app. This experience makes it feel like it is a mobile app, but under beneath, it opens a browser session and render HTML, JS, CSS code. Although the feel when using PWA app is not as smooth and optimized as when on mobile app, it is acceptable for simple tools, content-first applications, or admin dashboards.

I will take one of my favorite PWA application, Meme Express, as an example. Meme Express is a meme editor that I am using on my Macbook and iPhone whenever I want to make a meme. This meme editor is built with Flutter framework. It has a native app on PlayStore for Android, and a PWA version for the rest of OS including: iOS, MacOS, Window and Linux, essentially, any device can run a browser.

How is PWA version of Meme Express made ?

Framework

Align with mobile first design, Flutter is in used. For simple tools, Flutter is a perfect cross-platform solution, when we can write code once then port to iOS, Android, WebApp, Window and Linux application.

Deploy

For Android version, it is published via Playstore normally, at here: https://play.google.com/store/apps/details?id=com.ease_studio.meme. Unlike other cross-platform framework that utilize in-app web view to mimic mobile app, Flutter ports application to a native Android app.

For iOS version, Flutter can port app to native iOS code as well. But because 99$/year is not an option here, PWA version comes as a rescue.

To publish a PWA version, a hosting server is required. A hosting server requires monthly cost. Luckily, Github Page allow us to deploy a web app from a repository for free and it can be accessed via URL username.github.io/app-name , for example with Meme Express, it is https://ease-studio.github.io/meme-pwa/ . Github Page also allows to map a domain name to it. For example here, https://meme-express.io.vn/ actually points to https://ease-studio.github.io/meme-pwa/ .

Make it Installable

To make a web app installable, aka make it a PWA app, a file manifest.json is added. manifest.json structured is defined at: https://developer.mozilla.org/en-US/docs/Web/Progressive_web_apps/Manifest.

Install PWA app

Below is a demonstration of installing an PWA app to an iPhone, taking Meme Express as an example. Simply put:

Open Safari go to https://meme-express.io.vn/
tap “Share” icon
tap “Add to Home Screen”

How to compete with generative AI as a software engineer ?

Before the decade of AI bursting, software engineering is mostly about writing code that realize requirements. Software Engineers, at some extent, act like a translators between human languages and computer language. This translation today can be accomplished by many generative AI products in seconds and from my observation, generated code has pattern even better than code written by most of developers. It is understandable when companies begin laying off employees that does not match existing AI. It is just a cost optimization – vital part of every business – and also a coldest truth of this life, might be !

What is generative AI good and not good at ?

Recall the flow that each software engineer has to do daily is:

Receive requirements -> Review current state of source code -> Define a target state of source code -> Retrieve information from documents of related tools, libraries and solutions -> Pick solutions -> Actually write code -> Aligning new code to existing code -> Deploy -> Testing -> Measuring results -> Read error messages -> Debugging.

Some steps of this flow is done better by generative AI, and some is better by human:

Steps	Description	Winner and Why
Receive requirements	to capture goals, constraints, acceptance criteria, performance, security needs, and stakeholders’ expectations.	Human Reason: human are better at eliciting ambiguous needs, negotiating trade-offs, and asking the right follow-ups with stakeholders. AI can help by summarizing long requirement documents and suggesting missing or inconsistent points.
Review current state of source code	to read codebase, architecture, tests, docs, build scripts, dependencies, and CI config.	Human + AI Reason: AI can quickly index, summarize files, find patterns, risky hotspots, and generate dependency graphs. But humans provide domain knowledge, historical context, and recognize subtle intent (business logic, quirks, trade-offs).
Define a target state of source code	to design the desired architecture, interfaces, data flows, APIs, and acceptance criteria for the new state.	Human + AI Reason: AI can propose multiple concrete design options, highlight trade-offs. Humans must pick the option that fits non-technical constraints (policy, team skill, product strategy).
Retrieve information from documents of related tools, libraries and solutions	to find API docs, migration guides, best practices, configuration notes.	AI Reason: AI can extract key steps, call signatures, breaking changes, and produce concise examples from long docs much faster than manual reading. Humans validate and interpret edge cases.
Pick solutions	to select libraries, patterns, and implementation approaches considering performance, security, license, team skills.	Human Reason: human decision-makers must weigh organizational constraints, long-term maintenance, licensing, and political factors.
Actually write code	implement features, refactor, add tests, update docs.	AI Reason: AI excels at generating boilerplate, test stubs, consistent code patterns, and translations across languages.
Aligning new code to existing code	ensure style, APIs, error-handling, logging, and patterns match the codebase; maintain backward compatibility.	Human + AI Reason: AI can automatically reformat, rename for consistency, and propose refactors to match patterns; humans confirm that changes don’t break conventions tied to tests or runtime behaviors.
Deploy	push to staging/production, run migration scripts, coordinate releases, rollback plans.	Human Reason: Humans must coordinate cross-team tasks, business windows, and incident response. AI/automation is excellent at packaging, CI/CD scripts, and repeatable deployment steps.
Testing	Run the application locally and manually verify that new changes behave as expected.	Human Reason: Manual testing relies heavily on intuition, product knowledge, and human perception (e.g., UX feel, layout issues, unexpected delays, weird state transitions).
Measuring results	monitor metrics, logs, user feedback, testing results, and define success signals.	Human + AI Reason: AI can detect anomalies, summarize metrics, and surface correlations. Humans decide what metrics matter, interpret business impact, and choose next actions.
Read error messages	analyze stack traces, logs, exceptions, and failure contexts.	Human + AI Reason: AI quickly maps errors to likely root causes and suggests reproducible steps. Humans provide context (recent changes, infra issues) and confirm fixes.
Debugging	reproduce issues, step through code, identify root cause, fix and validate.	Human Reason: AI speeds discovery (identifying suspicious diffs, suggesting breakpoints, generating reproducer scripts), but complex debugging often needs human insight into domain rules, race conditions, and stateful behaviors.

How to compete with generative AI to secure the career as a software engineer ?

Similar to the Industrial Revolution and Digital Revolution, where labors is replaced by machines, some jobs disappeared but new jobs got created. And at some extent, AI, is just another machine, huge one, so, essentially, we are still in the Revolution of Machine era.

The answer for this question is that we need to work on where this huge machine cannot. So far, at the moment of this post, what we can do to compete with AI in software development are:

Transit to Solution Architect

As AI becomes strong at writing code, humans can shift upward into architectural thinking. A Solution Architect focuses on shaping systems, not just lines of code. This involves interpreting ambiguous requirements, negotiating constraints across teams, balancing trade-offs between cost, performance, security, and future growth. AI can propose patterns, but only a human understands organizational politics, legacy constraints, domain history, and long-term impact. By moving into architecture, you operate at a layer where human judgment, experience, and foresight remain irreplaceable.

Become Reviewer / Validator

AI can produce solutions quickly, but it still needs someone to verify correctness, safety, and alignment with real-world constraints. A human reviewer checks assumptions, identifies risks, ensures compliance with business rules, and validates that AI-generated code or plans actually make sense in context. Humans excel at spotting hidden inconsistencies, ethical issues, and practical pitfalls that AI may overlook. Becoming a Validator means owning the final approval — the role of the responsible adult in the loop.

Become Orchestrator

Future engineers will spend less time typing code and more time coordinating AI agents, tools, workflows, and automation. An Orchestrator knows how to decompose problems, feed the right information to the right AI tool, evaluate outputs, and blend them into a coherent product. This role requires systems thinking, communication, and the ability to see the entire workflow end-to-end. AI is powerful but narrow; an Orchestrator provides the glue, strategy, and oversight that turns multiple AI capabilities into a real solution.

Study Broader knowledge

AI is good at depth — consuming a specific library or framework instantly — but humans win by having breadth. Understanding multiple domains (networking, security, product design, compliance, UX, devops, data, hardware) allows you to make decisions AI cannot contextualize. Breadth lets you spot cross-domain interactions, anticipate downstream consequences, and design better holistic systems. The more wide your knowledge, the more you can see risks, opportunities, and real-world constraints that AI cannot infer from text alone.

Expertise in task description

In an AI-driven era, the most valuable skill is the ability to turn a messy idea into a clear, precise, constraints-rich task. This includes defining scope, edge cases, success criteria, and architectural boundaries. AI is only as good as the instructions it receives — so those who excel at describing tasks will control the quality of AI output. Humans who master problem framing, prompt engineering, and requirement decomposition gain leverage: they make AI more accurate, faster, and more predictable than others can.

Business Analyst

The heart of value creation lies in understanding the business, not writing the code. AI cannot replace someone who knows market dynamics, user behavior, budget constraints, prioritization logic, risk tolerance, stakeholder psychology, and regulatory boundaries. A Business Analyst bridges the gap between technology and real-world value. They decide why a feature matters, who it serves, how it impacts revenue or cost, and what risk it introduces — areas where AI can help, but not replace the human nuance needed.

Pentester

Security is one of the hardest domains for AI to master fully because it requires creativity, unpredictability, street knowledge, and adversarial thinking. A pentester does more than run scanners — they exploit human behavior, spot surprising vulnerabilities, and think like an attacker. Humans who understand security fundamentals, threat modeling, social engineering, and advanced exploitation techniques will stay in demand. AI helps automate scanning and code analysis, but a creative pentester stays ahead by understanding motives, tactics, and real-world constraints.

Essentially, it is to use AI as a super-assistant
that can write code very well
to realize our intentions.

What is Refactor and why it is matter ?

For someone with no programming experience, the word “refactor” can be confusing at first, because it’s mostly used in coding. For a simple explaining, refactor is Making something better or clearer without changing what it does.

Why Refactoring when there is nothing change ?

“If it works, don’t touch it” is a principle that is still valid in real world. It’s truth, pragmatic and is recommended at some extent when we do not have enough understanding about system we are working on. From business perspective, Refactoring feels unproductive when there is no new features added to system, but, just like a business, sometime we need to restructure processes, reorganize people and rearrange tasks to maximize outcomes, programing process also need refactoring to optimize coding experience which help source code more readable, maintainable, and scalable. These benefits, in turns, accelerate developers when adding new features or fixing bugs later on.

What is Readable code ?

Readable code is code written clearly so another developer, or future you, can read it quickly and know what’s going on, sometime just by guessing via variable names and function names. Some tactics can be applied to ensure readable code are:

Clear naming: Variables, functions, and classes have names that explain their purpose.
Short, focused functions: Each function does one thing, not many things.
Consistent formatting: Proper indentation, spacing, and line breaks.
Avoids unnecessary complexity: No overly clever tricks, Straightforward logic.
Helpful comments: Explain why, not what.
Use of standard patterns: Code follows common conventions so others instantly recognize the structure.

What is Maintainable code ?

Readable: as explained as above
Well-organized: Code is structured logically into modules, functions, or classes
Consistent: Follows the same style, naming, and patterns everywhere.
Well-tested: Covered by tests to catch bugs early and safely.
Documented: Has comments or docs explaining why and how things work.
Flexible: Easy to modify, extend, or adapt without breaking existing code.

What is Scalable code ?

Efficient: Uses memory and CPU wisely, Avoids unnecessary heavy operations.
Modular: Pieces of code can be separated or duplicated easily
Asynchronous / non-blocking when needed: Doesn’t freeze the whole system while waiting for one slow task.
Uses good architecture: Clear layers, Can split into microservices or separate components if needed.
Uses proper data structures: For example, using a Map instead of a List for fast lookups.
Database scalability: Indexes, caching, batching queries, sharding, etc.

Refactor safety

Because the goal is to keep system working as the same while rewriting codes, there must be a metric indicate sameness, or early detect differences in system behaviors. This is where Test Driven Development shines.

Writing Test is mistakenly overlooked by inexperience developers. Beginners usually think programing job is just to write code, see it run then move on writing another code. Writing tests looks like an extra work or an annoying requirement. This is okay just as a young men does not understand “karma”. And karma for this overlooking usually are:

Bugs keep coming back
Bugs evolve when there is more code added
Take so much time for debugging
Source code become a mess and a small change can take months to add

When bugs bring enough pain, developers begin more experience.

Test Driven Development (aka TDD)

Test-Driven Development (TDD) is a software development process where you write tests before writing the actual code.

TDD follows a repeating 3-step loop:

Write a failing test ( yes, always fail first ! )
- The test describes what the code should do.
- It fails because the feature doesn’t exist yet, or the bug is not fixed yet.
Write the minimum code needed to make the test pass
- Not perfect code, just enough to pass the test.
Refactor – Clean up the code
- Improve readability, maintainability, scalability
- Keep the tests passing.

Then repeat the cycle for the next feature and bug fixing.

Tests ideally can simulate the UX that users will engage on real product. This can not be 100% achieved but keep this principle in mind will help a lot to write good tests. Depends on how closely a test to real world UX, tests can be classified to 3 levels: Unit Test, Integration Test, and E2E Test.

Unit Test

Unit Test is ideal to test behaviors of a function or a class. In each unit test, we can test output of a function given a particular input. We can anticipate what inputs can be, even unrealistic ones (hackers usually input unrealistic ones) , to ensure our functions keep functioning regardless what input is. Unit tests can be used as a debugging tool when we can test directly a part of system without try reproducing via UI/UX. For functions that is well guarded by unit tests, developers can feel more confident to add changes or refactor it because bugs can be caught early.

Integration Test

Integration tests are tests that check how multiple parts of system work together. Functions, Classes and Flows can be tested on how they are interacting together inside a system. It ensures that every “pieces” of the system are integrating properly. Similar to Unit Test, we can anticipate and simulates Flows to can catch bugs soon.

E2E Test

E2E (End-to-End) tests are the tests that simulate a real user using the real app, by actually click buttons and typing text.

This is ultimate form of Test that can catch bugs that unit or integration tests cannot. E2E Tests test the app in an environment closest to production. They validate the entire system from UI/UX to data storage. But it is the hardest tests to make when a real system need to be deployed for E2E tests can execute. Simulating user behaviors by coding requires more effort. This is why many teams usually stop at Integrating Tests and it is totally ok when majority of bugs can be catch at level of Integration Test. Writing E2E Tests is time consuming so we should only write it for bugs that un-produceable at Integration Test level. These bugs are high-level bugs and it should be addressed by high-level tests, and they mostly about concurrency, timing and resources:

Race Condition: A situation where the correct behavior of a program depends on the relative timing or interleaving of multiple threads or processes. It’s about uncontrolled timing causing wrong results.
DeadLock: Two or more threads/processes are waiting on each other indefinitely, preventing progress. As the result, system freezes because resources are locked in a circular wait.
Livelock: Threads or processes keep changing state in response to each other but make no actual progress. As the result, CPU or threads are active, but nothing gets done.
Starvation: A thread never gets access to a needed resource or CPU because other threads dominate it. As the result, resource exists, but some threads never get a chance to execute.
Atomicity violation: A set of operations that should be executed as a single, indivisible unit is interrupted, causing incorrect results.
Order violation: Correct behavior depends on operations happening in a specific order, but the order is not guaranteed that eventually leads to incorrect results.
Heisenbug: A bug that disappears or changes when you try to observe it (e.g., by debugging, logging, or adding print statements). This sounds like quantum computing but yes, it does exists. These bugs often caused by concurrency, timing, or memory issues.
Data corruption: Shared data is modified concurrently without proper synchronization, resulting in invalid or inconsistent values.
Lost update: Two concurrent operations overwrite each other’s results, causing data loss.
Dirty read / inconsistent read: A thread reads a partially updated or uncommitted value from another thread or transaction and then produce wrong results.
Priority inversion: A low-priority thread holds a resource needed by a high-priority thread, causing the high-priority thread to wait unnecessarily.

In conclusion, to Refactor code safely, we need a lot of tests, good tests one !

How to avoid Merge Conflicts in software development

Beside Ambiguous Requirements, Tight Deadline and Unstable Legacy Codebase, Merge Conflict is another light fear that annoys and disrupts developers the most while making software.

From a fact of how Merge Conflict might appear in this post that long-live branches should be avoid as much as possible to mitigate chance of conflict, here are some guidelines to help any software teams deal with this fear.

User Story based Task Description

Human brain is designed to consume story, not ambiguity. In software development, User Story is short, simple description of a feature or requirement told from the perspective of the end user. It’s a fundamental element of Agile and Scrum methods — meant to capture what the user wants and why, without prescribing how developers should implement it. A user story usually follows this format: As a [type of user], when [something happen], user want [some goal] so that [some reason] . For example: As a registered user, I want to reset my password so that I can access my account if I forget it. This helps teams understand who needs something, what they need, and why it matters.

Depends on how big the goal user want is, a User Story can be splitted into simpler stories. We don’t have to write an essay in task description because we are not at school. Clarity is the top priority when writing tasks descriptions, so don’t think, just tell stories.

When a User Story is simple enough, a task stemmed from it can have a small scope of change with limited effect of codebase, and in predictable way. Small scope of change in a task helps to mitigate chance of conflicts. Even conflicts happen, resolving them can be easier because it happens in fewer places.

Merge/Rebase daily, resolve early

When tasks are defined well and scope of change is limited, the branch now can be short-live which is okay for Rebase tactic. Depend on preference of history commit tree, Merge or Rebase both is okay. The recommended practice here is to do it daily: merge main branch into new branches, or rebase new branches onto main branch. This practice helps to early aware of possible places might cause conflicts so that we can adjust coding tactic or sync up with other developers about what changes are made.

FIFO Merging

It is obviously right when prioritize tasks but do not apply priority to the order of merging code because it can turn some branches into long-live one when higher priority tasks keep being merge first. When a task is put on progress, your Kanban board for example, and when it is in Done column for example, it should be merged asap regardless priority of its task. What is completed first should be merged first, (First-In-First-Out order) . To achieve this state, utilize any tool to automatically do so is highly recommended. Of course, completion of a task here includes testing phase as well.

When a task is well defined with limited scope in User Story format, and somehow it gets stuck and turn into long-live branch, we need to review its necessity:

If we don’t need this feature anymore, so discard the task and close the branch.
If we still need this feature, but it contains risky changes, and it is why no one dare to merge it to main branch, so it is time to make simplier stories from the risky parts. Don’t let task being stuck. Keep feature branches short-live.

Commit with Task ID

Commit message is encouraged to describe what changes are but there is nothing to force or ensure that consistency. This depends on how good a developer can explain things. So to make it simple and scalable, it is recommended to begin a commit message with Task ID, for example: #1234 fix things , so whenever anyone wonders why a commit is added, they can trace back to related task description and let the User Story explains.

Long-live branches as Microservices

For any reason that a branch is planned to be long-live, such as when making a challenging feature that inevitable requires long time of development, consider to turn this big part into Microservices. Microservices architecture can keep new code in separated repository, which in turn, can mitigate risk of conflicts with existing main branch. Main system can communicate to this new Microservices in any kind to get things done without worrying about large changes from new features. The new Microservices can have its own tasks board with its own User Stories, and User here, is the Main system.

Time is money, so Don’t waste development time for resolving merge conflicts !

Merge vs Rebase: which is better ?

I usually prefer using Merge to Rebase for safety first.

Merge and Rebase is 2 ways of combining changes from different branches when using Github as chosen source code management platform. Since Merge seems to be enough to get things done in every cases, why does Github includes Rebase method ?

The answer seems related to team’s preference on the commit history. Github maintains a tree of commits per repository and each commit is a snapshot of all files. It is important to notice that Github stores project snapshots, not the diffs that we see with command git diff . Diffs are calculated on the fly when we compare 2 commits. This nature of Github affects to how actually Merge and Rebase behaves under the hood:

How does Merge actually work ?

When using git merge, for example, to merge branch A into branch B and given branch B is created from branch A, Github performs below steps:

Finds the common ancestor snapshot, aka the commit where branch B is created from.
Compares the latest snapshots of branch A to ancestor snapshot, get the diffs D1 (aka MERGE_HEAD)
Compares the latest snapshot of branch B to ancestor snapshot, get the diffs D2 (aka HEAD)
Applies diffs D1 & D2 on the ancestor snapshot then output a new merged snapshot, stored in a new commit of branch B

Because commits are snapshots:

Git doesn’t need to replay all intermediate diffs.
It just looks at 3 snapshots: ancestor , HEAD and MERGE_HEAD.

That’s why merging large histories is fast and doesn’t rewrite old commits — the snapshots are stable and immutable. When using Merge, if Conflicts happen, because there are always 3 snapshots is taken into account and the output is always 1 new snapshot, resolving Conflicts when using Merge likely happens only once.

How does Rebase actually work ?

When using git rebase, for example, to rebase branch B onto branch A, given that branch B is created from branch A, Github performs below steps:

Calculate the diff between each commit (aka snapshot) of branch B to its parent commit. This is likely to create a “patch” telling step-by-step how changes are already made on branch B,
Reapplies those diffs (patches) on top of latest snapshot of branch A
Creates new commits with new IDs (aka new snapshots).

So when each time when we rebase a branch B onto branch A, new commits (or snapshots) are added as if we have just made those changes on the snapshots of branch A. Because diffs are reapplied every time when we rebase, if there are Conflicts, it is likely we have to resolve same conflicts again and again. And this is why I prefer Merge to Rebase.

So, why does Rebase exists ?

Rebase is mostly used when we have a reason to control how the commit history looks like on a branch. This can be useful when a team prefer a linear commit history that is easier to read and do not care what actually happen such as when a branch is created and what is merged. Because it rewrites commit history on a branch, Rebase is not recommended to use on main branch due to the risk of losing commits and resolving conflicts multiple time. Rebase is safer only on a feature branch, which is created from main branch, and most important, this feature branch should have short-time development. On a feature branch that long-live enough, re-resolving conflicts might happen frequently and this can slow down development speed and even frustrate developers.

Conclusion

In summary, my suggestion on Merge vs Rebase is :

Always using Merge for safety first
If we are working on a feature branch (NOT the main or master one), and want to have a nicer commit history on this branch, and development time for this branch is short, then can use Rebase

Story behind ads you see on your Facebook

TO PROTECT YOUR PRIVACY !!

Have you ever wonder why powerful tools like Google Search, Gmail, Facebook, X, Tiktok, etc are all free to use ?

When you see they sell nothing, then you are what to be sold !

Advertisement is the main profit source that keep most of online tools free nowadays. Advertisement is not bad when it brings information to us in proactive way so we don’t have to spend time investigating market options. But due to this indirect method of advertising, we can’t know who actually behind it. And in fact, this has become an ideal channel for scammers to lure users via social networks. A lot of students, elders were victims because they has least knowledge and experience online. And when many companies systems were infiltrated, hacked, stolen data, personal data of users is leaked globally. These problems, when combine together, harms our privacy !

This post reveals some methods around online advertising industry found on Facebook and the same also can be applied in every social networks as well.

How anyone can make you read something while using Facebook ?

Given that we are all using some banking or non-banking applications, and on the news we hear about companies behind those application are hacked, and data is leaked on some dark web. Dark webs are websites operated outside the laws and are the ideal places for criminal activities which selling hacked data is the most popular. Today anyone can buy leaked data using Bitcoin or Ethereum to hide their identity completely. When someone has our name, phone numbers, emails or even addresses, they can search for and start stalking us on social networks such as Facebook, Instagram, X, etc, then after that they pay to run a targeted ads campaign with information they know about us, and let Facebook algorithm handle presenting that ads to our mobile phone.

How can advertisers control who will see their ads:

1. Custom Audiences

Facebook allows anyone to use phone numbers, emails, or names to directly target a specific user:

Advertisers upload a list of customer data (CSV) to Facebook Ads Manager.
Facebook matches the data (phone/email/name) with existing user accounts.
Once matched, only those users in the list will see the ads.

This is the most direct method of delivering ads to a known individual.

2. Lookalike Audiences

Based on a seed audience (e.g., 100 users with names and emails), Facebook finds other users with similar behavior.

This is indirect targeting, used to expand reach to similar users even advertisers don’t know names or emails.

3. Geotargeting / Geofencing

Facebook allow anyone to use the user’s location (address or GPS) to limit where an ad appears. This usually being used by physical stores. If you ever notice when you pass by some stores, you more likely see their ads on news feed.

4. Interest, Demographic, and Behavioral Targeting

When no personal data is available, Facebook allows anyone to filter audiences by:

Age, gender, region, job title
Online behavior (e.g., searching for a laptop, following specific pages)
Past engagement with posts, videos, or websites

This is an indirect ways but still get ads appear to us.

Lesson

By utilize above methods, anyone, real advertisers, or even scammers, can show some messages to our face when we are scrolling on Facebook, Youtube, Instagram, etc. Social Network applications, one hand, create free tools to soothe the desire of connection in people, and one hand, sell privacy to anyone willing to pay.

Although most of ads is not harmful, make sure to share just enough on social networks, to avoid worst situations that scammers can use ads too !

Store datetime as ISO 8601 instead of timestamp

Like any programmer, I used to use Date for storing date time values on database, until I suffer with bugs related to timezone and DST (Daylight Saving Time). The most common symptom is the date fields, such as created_date or updated_date, often display 1 day prior to what it is set before: Let say an admin set the created_date to Jan 1st 2025 00:00:00 clients somehow see value Dec 31 2024, 23:00:00 .

I tried putting browser timezone information into adjusting timestamps but then I noticed that the code base became more complex and the bug still can’t be fixed when DST (Daylight Saving Time) happens. The bug will happen when:

most of databases use integer representing microseconds (or timestamp) to store datetime data
users locate in many countries with different timezones
Daylight Saving Time happens with no fixed schedule

Then I realize the power of standard: ISO 8601, is that it can be used to store date time values in plain text and still be sortable. Storing datetime as format YYYY-MM-DD HH:mm:ss at UTC, (or any format instructed in ISO 8601) can remove all headaches when using timestamp but also remain sorting & filtering capabilities. The only downside, is the frontend part and backend part has to make sure date time data is sent and received in ISO 8061 format instead of integers, and this conversion is simple enough and can help avoid days of debugging.