Category: Social Media

How To Create Viral Posts with a Hook

I used to think the best posts were the most informative ones.

The ones with the most data. The most research. The most carefully crafted sentences.

So I would spend hours writing.

Editing. Rewriting. Polishing.

And then I would publish.

And wait.

Sometimes, nothing happened.

A few likes. Maybe a comment or two from people who already knew me.

But no shares. No new followers. No real traction.

Meanwhile, I would scroll through my feed and see someone else’s post — shorter than mine, less detailed than mine — getting hundreds of reactions.

How?

I sat with that question for a long time.

Until I finally understood the real answer.

It was not about the content.

It was about the first line.

Nobody Reads What They Don’t Click

Here is something that took me embarrassingly long to accept.

People do not read posts.

They scan them.

They scroll past hundreds of updates every single day. They are moving fast. Their attention is already somewhere else.

And in that tiny moment — that split second — they decide.

Keep scrolling.

Or stop.

That decision happens before they read a single word of your actual content.

It happens at the first line.

That first line is called the hook.

And if your hook does not grab them, nothing else matters.

Not your insights. Not your story. Not your carefully structured arguments.

None of it.

Because they never got that far.

The Moment I Finally Understood This

I remember posting something on LinkedIn a while back.

It was a detailed post about IoT adoption challenges in Malaysia.

Lots of context. Lots of nuance. Lots of things I genuinely believed people needed to hear.

I opened with something like:

“The Internet of Things has been growing rapidly over the past decade, and many organisations are now beginning to recognise its potential…”

It barely moved.

A few weeks later, I wrote another post.

Same topic, roughly.

But this time I opened with:

“I almost gave up on Favoriot in 2019.”

That post reached thousands of people.

Same me. Same platform. Same audience.

Different first line.

Everything changed.

What Makes a Hook Actually Work

I have been studying this for a while now.

Not just reading about it.

Actually testing it. Watching what works. Noticing what stops the scroll.

And here is what I have learned.

A good hook does one of three things.

It makes people curious. It makes people feel something. Or it makes people think “that is exactly my problem.”

The best hooks do all three at once.

Let me break it down.

Type 1: The Curiosity Hook

This is the classic cliffhanger.

You reveal just enough to make people want more.

“I made one change to my LinkedIn profile and tripled my inbound messages.”

“Nobody told me this would happen when I became a founder.”

“I was completely wrong about how viral posts work.”

See what those have in common?

They open a loop.

The human brain hates open loops. It wants to close them.

So it keeps reading.

The key is to tease the answer without giving it away. Enough to promise value. Not enough to satisfy without reading further.

Type 2: The Emotion Hook

Facts tell. Feelings sell.

When you open with something emotionally real, people lean in.

“I cried after my first investor meeting. Not because it went badly. Because it went exactly as planned.”

“The day I realised I was becoming a human FAQ was the day everything changed.”

“I have given hundreds of talks. But one question from a student stopped me cold.”

Emotion creates connection.

It reminds people that behind every profile, there is a human being.

And human beings are drawn to other human beings, not information machines.

Type 3: The Problem Hook

This is my personal favourite.

You name a pain that your reader already feels.

Immediately.

Before they even know you understand them.

“Most IoT projects fail not because of technology. But because of this one blind spot.”

“You are creating content every day. But nobody outside your network is seeing it.”

“You have been writing posts for months. But your follower count has barely moved.”

When people read a hook like that, they stop scrolling because they think:

Wait. Is this person talking about me?

Yes.

That is exactly the feeling you want.

The Formula I Use Now

I am not going to pretend I have cracked some magic formula.

But I do have a starting checklist.

Before I publish anything, I ask myself five questions about my first line.

Does it make someone curious or create an open loop?

Does it touch a real emotion — not a manufactured one?

Does it name a problem my reader actually has?

Can it stand alone? If someone only read this one sentence, would they want more?

Would I stop scrolling if this appeared in my feed?

If the answer is no to most of those, I rewrite the opening.

Sometimes three or four times.

Because the rest of the post is irrelevant if the first line does not work.

The Mistake Most People Keep Making

The most common mistake I see?

People bury the hook.

They write a long preamble. They give context before they create curiosity. They explain the situation before they create tension.

Something like:

“As someone who has been in the technology space for over twenty years, I have seen many trends come and go. Today I want to share some thoughts about content creation and why it matters in the age of social media…”

By the time you reach the actual point, the reader is already gone.

Start with the tension. Start with the emotion. Start with the problem.

Then build the context.

Not the other way around.

One More Thing

I want to be honest about something.

Writing good hooks felt uncomfortable at first.

It felt like I was being dramatic. Like I was sensationalising. Like it was not really me.

But then I realised something important.

A hook is not manipulation.

A hook is respect.

It respects the reader’s time. It signals that what follows is worth their attention. It earns the right to be read.

If your content genuinely helps people, then writing a compelling hook is not a trick.

It is a responsibility.

So Here Is My Challenge to You

Go back to your last five posts.

Look at the first line of each one.

And ask yourself honestly:

Would you have stopped scrolling for that?

If the answer makes you a little uncomfortable, that is okay.

That is where the growth is.

Rewrite one opening today.

Just one.

See what happens.

I am curious to know.

What kind of hook has worked best for you? Drop it in the comments. Let’s learn from each other.

The Top 10 Things to Attract Readers on LinkedIn

By Dr. Mazlan Abbas

LinkedIn has changed more in the past twelve months than in the five years before that.

The algorithm most people are still using as a mental model no longer exists. The tactics that reliably worked in 2023 and 2024 are actively being penalised today. And the professionals who have not yet adapted are watching their reach quietly decline — often without understanding why.

I have been posting on LinkedIn for years. I have built a following, attracted speaking invitations, and grown FAVORIOT’s visibility primarily through consistent content on this platform. In that time I have watched every major shift in how the algorithm behaves.

Here is what I have learned — and what is actually working right now in 2026.

Why LinkedIn Has Become Harder — and More Rewarding

LinkedIn shifted its entire ranking model in early 2026. The old system rewarded you based on how many connections you had and how quickly a post picked up likes. The new system works more like TikTok for professionals.

It is now an interest graph, not a social graph.

What that means in practice: your content is no longer just shown to your connections. It is distributed to people who have demonstrated interest in your topic — whether or not they follow you. A well-crafted post from a smaller account can now reach further than a poorly crafted post from an account with fifty thousand followers.

This is actually good news for thought leaders who produce genuine insight.

But it also means that average content — generic advice, motivational quotes, promotional announcements — receives almost no distribution at all.

The bar has gone up. Here is how to clear it.

1. Start With a Hook That Earns the Click

LinkedIn shows readers only the first two lines of your post before they have to click “see more.”

Those two lines are your entire pitch.

If your opening line does not create curiosity, make a surprising claim, or signal clear value, most people scroll past. The algorithm also registers this behaviour. A post that loses readers immediately is pushed to fewer people. A post that earns the click gets rewarded with broader distribution.

The openers that work:

  • A specific, counterintuitive claim: “Most LinkedIn advice is designed for people who already have an audience. Here is what actually works when you are starting from zero.”
  • A direct provocation: “Your LinkedIn profile is losing you speaking opportunities. Here is what to fix this week.”
  • A numbered promise: “After 200+ keynotes, I still make this one mistake when pitching to new audiences.”

What does not work: “Excited to share some thoughts on…” or “I have been reflecting on…” These tell the reader nothing and give them no reason to stop scrolling.

2. Optimise for Dwell Time, Not Likes

The 2026 LinkedIn algorithm measures how long people actually spend reading your post — not just whether they clicked a reaction button.

A post that someone reads for thirty seconds now outperforms a post that collected fifty quick likes. LinkedIn calls this signal “dwell time,” and it has become one of the most important ranking factors in the feed.

What this means for how you write:

Keep paragraphs short — one to three sentences each. Use white space generously. Structure your post so the reader has a reason to keep going line by line. Write posts that are long enough to hold attention but tight enough that no sentence feels wasted.

The optimal post length for maximum dwell time tends to be 300 to 400 words. Long enough to build an argument, short enough to finish in a single sitting.

3. Use Carousels for Maximum Reach

Of all the formats currently available on LinkedIn, document carousels generate the highest average engagement — roughly 6.6 percent, compared to around 2 percent for text-only posts.

The reason is structural. Carousels force the reader to swipe through multiple slides. Each swipe extends dwell time and signals genuine interest to the algorithm. They are also highly shareable and saveable, which are the two engagement actions LinkedIn now values most.

What makes a carousel perform well:

  • Lead with a slide that makes a specific claim or promise
  • Use text-oriented slides over image-oriented ones — stories are easier to tell with words
  • Keep each slide focused on a single idea
  • End with a clear takeaway or call to action on the final slide

If you write long-form posts regularly, almost every one of them can be repurposed into a carousel. The content already exists. The format just makes it more discoverable.

4. Build Saves, Not Just Likes

LinkedIn added Saves and Sends to post analytics in late 2025. That was not a coincidence. It was a signal about what the platform now rewards.

A save tells the algorithm: this content is valuable enough to return to later. A send tells the algorithm: this content is worth sharing privately with someone else. These two actions now drive significantly more reach than a standard like.

The implication is clear. Create content people want to bookmark.

That means frameworks, checklists, step-by-step guides, data-backed insights, and lessons from real experience. The question to ask before posting is: would someone save this to refer back to later? If the answer is no, the post probably needs more substance.

5. Write for Your Niche, Not for Everyone

LinkedIn’s algorithm now identifies what it calls your “topic DNA.”

It distributes your content based on demonstrated expertise in a specific area, not based on your network size. A post about IoT platform mistakes reaches IoT practitioners and enterprise decision-makers — regardless of whether they follow you — because the algorithm recognises the topic and the audience that engages with it.

The practical consequence: broad, general content performs poorly. Specific, niche content performs disproportionately well.

Write for one person — the specific professional who would benefit most from what you know. A post written for IoT startup founders will outperform a post written for “anyone interested in technology.”

The more specific you are, the further the algorithm pushes your content into the right hands.

6. The First 60 Minutes Determine Everything

When you publish a post, LinkedIn initially shows it to a small sample of your network — roughly two to five percent of your connections.

How that sample responds in the first hour determines the total lifetime reach of the post. Research suggests that only five percent of posts that underperform in the first hour recover to reach a broader audience.

What this means in practice:

  • Post when your audience is most active, typically weekday mornings
  • Respond to every early comment quickly — this signals active conversation to the algorithm
  • Do not post and disappear immediately after publishing

The first hour is not just a window. It is the window.

7. Never Put External Links in the Post Body

This is one of the most commonly ignored rules on LinkedIn — and one of the most costly to break.

Posts that include external links in the body see approximately 60 percent less reach than equivalent posts without them. LinkedIn actively suppresses content that drives users away from the platform.

The workaround most people used — putting the link in the first comment — has also been penalised as of early 2026.

The better approach: make the post complete and valuable on its own. If you want to reference an article, a report, or a website, mention it by name in the post and let interested readers find it themselves. Or put the link in a comment, but do not lead with it or frame the post around it.

LinkedIn rewards content that keeps people on LinkedIn.

8. Personal Profiles Outperform Company Pages — By a Wide Margin

One of the clearest findings from 2026 LinkedIn research: personal profiles now generate five times more engagement than company pages.

The algorithm is built to surface authentic human voices, not brand broadcasts. A post from you as an individual — sharing a lesson, an opinion, a real experience — will reach further than the same content posted from a company page.

For anyone building a personal brand alongside a company or startup, this is the most important structural insight on this list.

Invest in your personal profile first. Let the company page support from the background.

The most visible founders and executives on LinkedIn are not posting from their company accounts. They are posting as themselves — and the company benefits from the credibility that follows.

9. Engage Like You Mean It

The 2026 algorithm has become very good at detecting hollow engagement.

“Great post!” and emoji-only comments no longer generate meaningful algorithmic benefit for you or the person you commented on. LinkedIn’s systems can distinguish between genuine professional conversation and automated or low-effort interaction — and they reward the former while increasingly suppressing the latter.

When you engage with another post, write a response that adds something. A different perspective. A follow-up question. A relevant experience. A specific disagreement.

When people comment on your posts, reply with the same quality. Conversations that go two or three levels deep generate far more reach than posts with fifty single-word reactions.

Engagement is not a vanity activity. It is how the algorithm learns who you are and who to show your content to.

10. Be Consistent — But Make Every Post Count

The algorithm in 2026 rewards depth and authority over posting volume.

One valuable, well-structured post per week consistently outperforms five forgettable ones. If you publish more frequently, make sure each post earns its place. Content that performs poorly — that loses readers quickly, generates no saves, and triggers no real conversation — signals low quality to the algorithm and can suppress the reach of your subsequent posts.

The professionals winning on LinkedIn right now are not posting more. They are posting better.

Build a sustainable rhythm that you can maintain for months, not weeks. Decide on your core topics and stay close to them. Let your “topic DNA” build over time. The algorithm rewards consistency within a niche more than it rewards volume across many topics.

Putting It Together

LinkedIn in 2026 is harder to game and more rewarding when you do it right.

The platform has moved decisively away from rewarding connections, follower counts, and quick likes. It now rewards demonstrated expertise, genuine engagement, content people save and share, and consistent presence within a defined niche.

That is actually good news for practitioners and founders who have real knowledge to share.

The tactics above are not shortcuts. They are the structural conditions under which LinkedIn now distributes content. Understanding them is not about gaming the algorithm — it is about making sure the algorithm can find the people who would benefit from what you already know.

If you have been posting on LinkedIn and feeling like the platform has stopped working, revisit these ten areas. The platform has not stopped working.

The playbook just changed.

Dr. Mazlan Abbas is the CEO and co-founder of FAVORIOT, an AIoT platform company. He has been listed as a Top 50 Global Thought Leader in IoT, Smart Cities, and GovTech. He writes about technology, startups, and personal brand building at mazlanabbas.com.

HOW-TO Grow Your Threads Social Media Playbook

By Dr. Mazlan Abbas

Most people who join Threads make the same mistake.

They treat it like Twitter. They post content, drop a link, and wait for followers.

That approach does not work here.

I have been observing social media platforms long enough to know that every platform has its own culture, its own rhythm, and its own algorithm logic. Threads is no different. And right now, in 2026, it is one of the most interesting opportunities available for anyone serious about building a personal brand or thought leadership presence.

Here is why.

The Window Is Still Open

Threads now has 400 million monthly active users. In January 2026, it surpassed X in daily active mobile users for the first time. That is a significant signal.

But more importantly for creators and thought leaders — organic reach on Threads is still unusually high.

On Instagram, a typical post reaches 5 to 10 percent of your followers. On Threads, a well-crafted post regularly reaches two to five times your follower count. Your content gets pushed to people who do not follow you yet.

That is the growth mechanic. And it will not last forever.

Platforms always start open and gradually close as they mature and introduce advertising models. We saw it with Facebook. We saw it with Instagram. We saw it with LinkedIn.

The creators who move early win the most. The ones who wait until a platform is saturated wonder why it no longer works.

What Makes Threads Different

Threads is not Twitter. It is not Instagram. It is not LinkedIn.

It is a text-first conversational platform that rewards authenticity and genuine engagement over polished broadcast content.

Think of it this way. Instagram is your portfolio. Threads is your coffee shop.

The algorithm on Threads is built around conversation. Posts with genuine replies outperform broadcasts. This means smaller accounts can compete with established ones. If you can spark real discussion, the platform will push your content further.

This is exactly the opposite of what most social media platforms do once they mature.

The Playbook

After studying what actually works on Threads in 2026, here is the playbook I recommend.

1. Optimise Your Profile First

Before you post a single word, make sure your profile is working for you.

Your bio needs to answer three questions immediately:

  • Who are you?
  • What do you talk about?
  • Why should someone follow you?

A weak bio says: “Entrepreneur. Speaker. Husband.”

A strong bio says: “IoT founder building FAVORIOT. 40 years in tech. Daily takes on AIoT, smart cities, and what the industry gets wrong.”

The difference is specificity. Give someone a reason to hit follow before they have ever read your posts.

Also connect your Threads account to Instagram. Your posts can surface on Instagram, and your existing Instagram followers can discover you on Threads. Cross-platform discovery is built into the system. Use it.

2. Post With a Strong Hook

The first line of every Threads post is everything.

If you lose someone in the first sentence, they scroll past. The platform does not give you a second chance.

The hooks that consistently work are:

  • The specific number: “I made this mistake in 3 out of my last 5 IoT projects.”
  • The pattern interrupt: “Stop building dashboards. Build outcomes.”
  • The curiosity gap: “The one thing we changed at FAVORIOT that reduced churn by half.”
  • The contrarian take: “Everyone is talking about AI in IoT. Most will fail for the same reason they failed before AI existed.”
  • The story opener: “Five years ago, we almost shut FAVORIOT down. Here is what happened.”

Notice the pattern. Every hook is specific, creates curiosity, and makes a promise that the rest of the post delivers on.

Generic openers like “Some thoughts on IoT today” or “A few tips on personal branding” get ignored.

3. Choose Your Content Format

Unlike Instagram, where video dominates, Threads gives different formats genuine opportunity.

The three formats worth understanding are:

Text-only posts. Simple and easiest to produce at volume. When the idea is strong, text alone performs very well. This is the native format of the platform.

Photo posts. Strong for personal storytelling and adding a human face to your content. A photo of you at a conference, at a whiteboard, or behind the scenes of your work adds context that text alone cannot.

Short video clips. Higher production effort, but worth it if you are already creating video for other platforms. Repurpose a keynote clip or a 60-second camera talk and post it natively.

The mix I suggest: 60 percent text-only, 30 percent photo, 10 percent video. Adjust based on what your own analytics show after 30 days.

4. Engagement Is Not Optional

Here is the single most important thing most people get wrong about Threads.

It is a conversation platform. If you treat it like a billboard — post and disappear — the algorithm treats you like a ghost.

There are two engagement obligations that matter.

Reply to your own comments within the first hour. When someone comments on your post, reply. This signals to the algorithm that your post is generating active conversation, which triggers more distribution. It also builds real relationships with people who took time to engage with you.

Spend time engaging with others in your niche. Not lazy comments like “Great post!” or “So true!” Those do nothing. Add genuine value. Share a different perspective. Ask a thoughtful follow-up question. When your comment is more insightful than most people’s posts, the creator’s audience notices you.

I would suggest spending 30 minutes daily on meaningful engagement with others. That time investment returns far more than simply posting more content.

5. Post Consistently — But Do Not Disappear After Two Weeks

The most common Threads failure pattern I observe is this: someone joins with enthusiasm, posts for two weeks, gets minimal early engagement, and quits.

They blame the platform. They say Threads does not work.

The problem is rarely the platform. The problem is they stopped before the algorithm had enough signal to know who to show their content to.

Consistency is the compound interest of social media. It takes time to build momentum. The creators who post daily for 90 days — even imperfectly — almost always outperform the ones who post perfectly for two weeks and disappear.

A sustainable rhythm beats a perfect one.

6. Use Topic Tags Strategically

Threads has its own version of hashtags called Topic Tags.

The approach that works is writing posts with natural-language, searchable phrasing rather than just tagging with labels. Think about how your audience would search for the topic, not how you would categorise it internally.

A post titled “How to avoid the 3 most expensive mistakes in IoT platform development” will surface in search and explore feeds far better than a post labelled “#IoT #tips #platform.”

Think of every Threads post as a small SEO document — clear, specific, and searchable.

7. Track What Works — Then Double Down

After 30 days of consistent posting, review your analytics.

Look at which posts generated the most replies, reposts, and profile visits. Look at which formats performed best. Look at when your audience is most active.

Then ask the right questions:

  • Was it the hook?
  • Was it the topic?
  • Was it the format?
  • Was it the time of posting?

Once you find a pattern, replicate it deliberately. If a contrarian take about IoT got ten times the engagement of a how-to tip, that is your signal. Create more contrarian takes.

Optimal posting time, based on data from millions of Threads posts, tends to be weekday mornings. But your specific audience may behave differently. Trust your own data over general advice.

The Mistake That Will Kill Your Growth

The biggest strategic mistake on Threads is treating it as a broadcast channel.

Post. Drop a link. Disappear. Repeat.

That is not how this platform works.

Threads rewards people who show up as humans — who share real perspectives, engage in real conversations, and build genuine community around specific ideas.

The creators growing fastest on Threads are not the ones with the most polished content. They are the ones who are most consistently present, most willing to share a real opinion, and most genuinely interested in the conversations they start.<br>

A Final Observation

Every time a new platform emerges, the majority of creators wait too long before taking it seriously.

They watch early movers build audiences and wonder what the secret was.

The secret is usually just timing and consistency.

Threads in 2026 is still in that early window. The organic reach is real. The opportunity is real. The platform is actively investing in creator features and expanding monetisation options.

But windows close.

The question is not whether Threads is worth your time. The question is whether you will show up consistently enough and early enough to benefit from it.

I hope this playbook gives you a clear starting point.

Now go post something.

Dr. Mazlan Abbas is the CEO and co-founder of FAVORIOT, an AIoT platform company. He writes about IoT, startups, smart cities, and personal brand building at mazlanabbas.com.

Why Universities Need a Real IoT Lab, Not Just Another Embedded Lab

I still remember a meeting with a group of lecturers, where I asked a simple question.

“Why do we really need an IoT Lab in universities?”

I paused for a moment.
Because deep down, I already knew the answer.

Most universities already have something they proudly call an IoT lab. Rows of ESP32 boards. Arduino kits. LEDs are blinking happily. LCD screens displaying temperature values. Students smile because something lights up.

And yet, something feels incomplete.

This is not IoT. This is just the beginning.

This blog is not meant to criticise universities. I have spent years inside them. I was once a lecturer designing syllabuses, labs, and assessments. This comes from care. From concern. From watching students graduate with confidence in embedded programming but struggle the moment systems become real, connected, and dependent upon.

This reflection is based on a recent lecture I delivered on the need to establish a proper IoT Lab in universities, one that reflects how systems are actually built, deployed, and trusted today.

Embedded Systems Taught Us How to Build Devices

Let me be very clear.

Embedded systems are important. They are foundational.

Students need to learn how to program microcontrollers. They need to understand sensors, actuators, interrupts, memory, and power consumption. All of that matters.

An embedded system is usually a standalone device. It senses something. It controls something. It logs data into local storage.

There is nothing wrong with that.

In fact, embedded systems are still used today in places with no connectivity. Remote areas. Harsh environments. Offline conditions.

But here is the problem.

Once the data is captured, someone has to physically go to the site, connect a laptop, download the data, return with it, and process it manually.

I have seen this happen too many times.

Two technicians. One vehicle. Hours of work. Just to retrieve data that could have been transmitted automatically.

I always ask myself… why are we still doing this in 2026?

Connectivity Changes Everything

The moment a device is connected to the internet, everything changes.

Data no longer waits for humans to come and collect it.
It flows.
It moves.
It becomes alive.

This is the moment embedded systems evolve into the Internet of Things.

Now we can monitor systems remotely.
Now we can detect failures early.
Now we can see battery levels dropping before devices die silently.
Now we can act before complaints arrive.

And yet, most university labs stop just before this moment.

Students are taught how to blink LEDs, but not how to send data reliably.
They learn how to display values, but not how to secure data in transit.
They build devices, but not systems.

And systems are what the real world depends on.

A Real IoT Lab Must Teach Technology Layers

IoT is not a single skill. It is a stack.

In my lecture, I stressed that a proper IoT Lab must expose students to multiple technology layers, not in theory, but through hands-on work.

Layer 1: Hardware and Firmware

This is where universities are already strong.

Sensors. Controllers. Actuators. Firmware logic. Power management.

Students should continue learning this well.

But they must also understand that this is just one layer.

Layer 2: Connectivity and Protocols

This is where gaps start to appear.

Students must learn how data travels.

Wi-Fi. Cellular. LPWAN.
Bluetooth. ZigBee. RFID.
MQTT. CoAP. REST. HTTP.
LoRa. NB-IoT. Sigfox.

Not as a list to memorise.
But as choices with consequences.

Which protocol suits low power?
Which network works for long range?
What happens when connectivity drops?

Without this understanding, troubleshooting becomes guesswork.

Layer 3: Platform and Middleware

This is the heart of IoT.

Devices do not talk directly to dashboards. They talk to platforms.

An IoT platform manages devices.
Authenticates them.
Stores data.
Provides APIs.
Handles scale.

This is where students should learn about device identities, data ingestion, databases, and analytics pipelines.

This is also where they start to understand why platforms like FAVORIOT exist in the first place.

Not to replace learning.
But to enable it.

Layer 4: Analytics and Visualisation

Dashboards are not the end goal.

They are the beginning of understanding.

Students should learn how data evolves from descriptive charts to deeper insights.
They should see patterns.
Spot anomalies.
Ask better questions.

This prepares them for real projects, not demos.

Security Must Exist Across All Layers

Security cannot be an afterthought.

Devices must be authenticated.
Data must be encrypted.
Platforms must be protected.
Applications must be hardened.

Most labs barely touch this.

And yet, this is where real systems fail.

When Systems Break, Knowledge Is Tested

I often tell students this.

The real test of IoT knowledge is not when everything works.

It is when something breaks.

Data stops arriving.
Dashboards go blank.
Alerts do not trigger.

At that moment, students panic if they only know how to code LEDs.

But students who understand layers start asking better questions.

Is it the device?
Is it the network?
Is it the platform?
Is it the visualisation?

This is the mindset a real IoT Lab must build.

Research, AI, and the Future of IoT Labs

Universities are not just about projects. They are about research.

To do meaningful research, students need data. Lots of it. Clean data. Continuous data.

IoT Labs enable this.

Once data flows reliably, students can apply machine learning.
They can explore pattern recognition.
They can experiment with predictive models.

Today, this also means understanding edge AI.

Inference running on devices.
Decisions made locally.
Latency reduced.
Systems are becoming smarter as they operate.

This is where IoT Labs naturally evolve into AIoT Labs.

And this is where universities must go.

This Is a Call to Universities, Lecturers, and Policymakers

If we want graduates who can build real systems, not just academic projects, we must change how we teach IoT.

IoT Labs must move beyond embedded programming.
They must teach architecture, trade-offs, and responsibility.
They must reflect how systems are deployed outside campus walls.

I believe universities can do this.
I believe lecturers want this.
I believe students deserve this.

But it requires intention.

It requires investment.
It requires collaboration with the industry.
It requires courage to redesign labs that have been unchanged for years.

If you are a lecturer, start asking what your lab is missing.
If you are a dean, ask whether your graduates can troubleshoot real systems.
If you are a policymaker, ask whether our talent pipeline matches national ambitions.

And if you are a student reading this, ask yourself one question.

Am I learning how to build a device… or how to build a system people can trust?

I would love to hear your thoughts, experiences, and struggles in building or teaching IoT.
Drop a comment. Let’s talk.

I Thought Favoriot Users Were Like Any Other SaaS Users. I Was Wrong.

For a long time, I carried a quiet assumption in my head.

I told myself, “A user is a user. SaaS is SaaS.”

I thought Favoriot users would behave like most consumer SaaS users. Log in daily. Click around. Expect things to feel smooth, friendly, almost playful. If something took too long, they would leave. If a screen felt confusing, they would complain. If onboarding was not instant, they would disappear.

That mental model sat comfortably in my head. Too comfortably.

Then one day, a simple question landed in my lap.

A question that forced me to stop using generic labels and actually picture real humans.

I paused.

Who exactly is using Favoriot?

And once I answered that honestly, everything shifted.

What I Actually See When I Think About Favoriot Users

When I close my eyes and picture a Favoriot user now, I don’t see someone lounging on a couch, scrolling through a polished interface with a coffee in hand.

I see something else.

I see sensors scattered on a desk.
Loose jumper wires tangled like spaghetti.
A laptop open with a dashboard on one screen.
Telegram buzzing on the other.
A multimeter nearby.
Sometimes a soldering iron.
Sometimes panic.
Sometimes excitement.

I see people trying to make something real work.

Ah. This is not a consumer SaaS crowd.

This is a builder crowd.

Builders, Not Browsers

Favoriot users are builders.

They don’t log in to be entertained.
They don’t log in to feel productive.
They log in because something must work.

A lecturer wiring ESP32 boards in a lab late in the evening.
A student is testing temperature data at 2 a.m. before demo day.
An engineer is checking why a sensor stopped reporting right after a rainstorm.

Their first question is almost never about aesthetics.

It’s usually raw and practical.

“Can I connect this device?”
“Is the data coming in?”
“Why did it stop at 3:17 p.m.?”
“Did I configure something wrongly or did the network die?”

They are hands-on by instinct.

And once I accepted this, I had to admit something uncomfortable.

I had been projecting the wrong expectations onto them.

Problem First, Not Feature First

Most consumer SaaS users start with features.

They ask things like:

“Does it have dark mode?”
“Can it sync with my calendar?”
“Is there a mobile app?”
“Can I customise the theme?”

Favoriot users start with a problem.

“I need to monitor the water level.”
“I must prove this concept works before funding.”
“My lecturer wants a dashboard by Friday.”
“My boss wants alerts, not charts.”

Features only matter if they help solve that problem quickly.

If a feature does not move them closer to a working outcome, it may as well not exist.

This was a big wake-up call for me.

I realised that talking about features without anchoring them to real use cases was missing the point entirely.

Learning While Doing Is the Default Mode

Another thing I misunderstood.

I used to think users came prepared. That they would read everything first. That they would know what they were doing.

Reality check.

A large portion of Favoriot users are learning while doing.

Students.
Fresh engineers.
Lecturers experimenting with new lab setups.
SMEs touching IoT for the first time.

They are not experts yet. And they know it.

They expect mistakes.
They expect trial and error.
They expect data that looks wrong at first.
They ask questions like:

“Did I wire this wrongly or configure it wrongly?”
“Why is the payload showing weird values?”
“Is this sensor faulty, or am I misunderstanding the units?”

Consumer SaaS users expect things to just work.

Favoriot users expect to work through things.

That difference matters more than most people realise.

A Bit of Friction Is Not the Enemy

Consumer SaaS products live in fear of friction.

One extra click and users leave.
One confusing screen, and churn happens.
One long form and conversion drops.

Favoriot users are different.

They tolerate friction if it leads somewhere meaningful.

They accept setup steps.
They read tutorials.
They debug payload formats.
They learn what MQTT or HTTP means.
They try again after failing.

As long as the payoff is real data and real insight, they stay.

I remember thinking to myself, “They are not lazy users. They are patient users with a purpose.”

That insight changed how I think about onboarding, documentation, and even UI decisions.

Usage Comes in Bursts, Not Habits

Here’s another mistaken assumption I had.

I assumed success meant daily logins.

That is true for many consumer tools.

It is not true for Favoriot.

Favoriot usage is project-based.

Users may log in intensely for two weeks.
Then disappear.
Then return when deployment starts.
Then vanish again.
Then come back when something breaks.

This is not abandonment.
This is reality.

Favoriot is not a habit-forming app.
It is a project enabling platform.

Once I stopped forcing a consumer SaaS lens onto usage patterns, the data suddenly made sense.

Ah. They didn’t leave. They just finished phase one.

Credibility Matters More Than Vibes

This part surprised me the most.

Favoriot users care deeply about credibility.

They ask questions like:

“Is this used by real organisations?”
“Can I show this to my supervisor?”
“Will this scale if my pilot succeeds?”
“Can I put this in my report or proposal?”

Consumer SaaS users care about brand feeling.
Favoriot users care about trust.

They want to know that what they are building on will not collapse when things get serious.

This is why things like:

Clear documentation.
Real case studies.
Honest limitations.
Professional dashboards.

matter more than flashy design.

They are building something that must stand scrutiny.

A Simple Mental Contrast That Helped Me

Once I framed it this way, everything clicked.

Consumer SaaS user:
Browses.
Seeks convenience.
Is the feature curious?
Hates setup.
Form daily habits.
Is emotion-led?

Favoriot user:
Builds.
Seeks control.
Is problem driven.
Accepts setup if useful.
Works in project bursts.
Is outcome-led.

Two very different humans.

Why This Changed How I Talk About Favoriot

I now remind myself constantly:

Stop comparing Favoriot to Notion, Canva, or Spotify.

Favoriot is closer to:

A lab bench.
A toolbox.
A test rig.
A learning environment.

This is why certain decisions suddenly felt obvious.

Why Lite plans for students matter.
Why simple dashboards matter.
Why examples matter more than slogans.
Why tutorials matter more than polish.
Why honesty beats hype.

Favoriot users don’t want magic.

They want clarity.

They want to understand what is happening.
They want to know what to do next.
They want confidence that they are not wasting time.

And when they succeed, something interesting happens.

They stay.
They recommend.
They come back with bigger ideas.

The Real Lesson I Had to Learn

The biggest mistake I made was not technical.

It was mental.

I assumed the wrong persona.
So I used the wrong language.
So I emphasised the wrong things.
So I measured the wrong signals.

Once I corrected that, everything else became easier.

Marketing messages became clearer.
Product decisions felt grounded.
User feedback made sense.

I remember thinking, “This is not about making things simpler for the sake of simplicity. It is about making things understandable for builders.”

That distinction matters.

Where This Leaves Me Now

Today, when I write, design, or explain Favoriot, I imagine a real person.

Someone with wires on the table.
Someone racing against a deadline.
Someone is trying to prove that an idea works.

If my message helps that person move forward, then it is doing its job.

If not, it needs rewriting.

And maybe that is the real takeaway.

Before we talk about growth, conversion, or positioning, we must first answer one honest question.

Who is actually on the other side of the screen?

If you are building, teaching, or learning with Favoriot, I would love to hear your story.

Drop a comment.

I Started a Startup at 56. This Is What the Journey Really Taught Me.

Techtamu Talk | 17 January 2026

On 17 January 2026, at around 10 in the morning, I stood before a room full of students, founders, and curious minds.

Before I spoke, I paused for a second.

“How do I explain a journey that never followed a straight line?”

Entrepreneurship, at least in my life, was never a planned destination. It was a series of connected experiences that only made sense much later.

That lecture was not about IoT.
It was not about startups.
It was about life, timing, courage, and knowing when to let go.

You Only Understand the Journey When You Look Back

I opened the session with a quote from Steve Jobs that has stayed with me for years:

You can’t connect the dots looking forward. You can only connect them looking backward.

That sentence explains my life better than any resume ever could.

When you are young, you worry too much about choosing the “right” path. The right course. The right job. The right company.

What nobody tells you is this.
Every experience counts, even the ones that feel like detours.

You just won’t see it yet.

From a Curious Child to a Technology Lifelong Learner

My interest in technology did not start in a lab or a classroom.

It started at home.

My late father was a clerk. But in the evenings, he repaired televisions and radios. I would sit beside him, watching circuits come back to life.

“So this is how things work.”

Then came science fiction.

Cartoons like The Jetsons showed a future that felt impossible at the time. Video calls. Smart watches. Flying machines.

Today, many of those ideas sit quietly in our pockets.

That early exposure planted a question in my mind that never left me.

“What if we could actually build these things?”

Living in Four Different Worlds

I consider myself fortunate. Few people get to experience all four.

Academia.
Corporate.
Government.
Startup.

I began as a lecturer at Universiti Teknologi Malaysia, immersed in theory and research. Later, I joined the corporate world at Celcom, where reality hits hard and fast. Customers matter. Deadlines matter. Revenue matters.

At MIMOS, I worked on national-scale research, including wireless sensor networks, long before the term IoT became popular.

Then came REDtone, where I helped build IoT initiatives inside a corporate structure.

Each world taught me something different.

But they also gave me baggage.

Experience gives confidence.
It also gives fear.

Young founders often believe everything is possible.
Older founders carry doubt.

“What if this fails?”
“What if I lose my savings?”

That voice gets louder with age.

Silicon Valley Changed Everything

At 56, I joined an immersion trip to Silicon Valley.

That trip changed my identity.

I walked into Plug and Play Accelerator and saw cubicles, whiteboards, and founders who looked just like us. That was where companies like Dropbox began.

I remember thinking:

“If this guy can do it, why can’t we?”

That was the moment I stopped seeing myself as a CEO-in-waiting.

I started seeing myself as an entrepreneur.

Not someday.
Not after retirement.
Now.

Starting Late Comes With a Price

I started my startup using personal savings. No incubator. No startup playbook. No fancy terms like ‘MVP’ or ‘pitching decks’.

Just belief and experience.

Our first idea was a smartwatch for the elderly with fall detection and emergency alerts. It looked noble. It sounded meaningful.

It failed.

The market was too small.
Children did not want to pay.
The device did not suit care homes.

That was my first real startup lesson.

Good intentions do not build businesses.
Paying customers do.

Learning the Art of the Pivot

In the startup world, pivoting is survival.

We repurposed the watch for Hajj and Umrah pilgrims. New market. Same core idea.

New problems appeared.

Unrealistic pricing expectations.
Battery life demands that defy physics.
Hardware sourcing from China.
Network roaming issues.
Travel agencies are unwilling to add cost.

Then came COVID-19. We proposed quarantine monitoring. It went nowhere.

Eventually, I made one of the hardest decisions of my life.

Ending a product.

I shared this honestly during the lecture.

Ending a product feels like ending a child you raised with love.
But holding on too long can kill the company.

A CEO must choose growth over attachment.

When More Products Mean Less Identity

We built other solutions too.

A civic complaint app sounded promising. Until each client wanted heavy customization and complaint volumes exploded beyond what they could manage.

A consumer tracking app failed because people care deeply about privacy and free alternatives already exist.

At some point, I realized something painful.

When you build too many products, people no longer know who you are.

Neither do you.

The Shift That Saved the Company

That realization led to our biggest change.

We stopped building products for users.

We started building a platform for builders.

That platform became Favoriot.

An IoT platform that lets others connect devices, visualize data, and deploy solutions quickly. Over time, intelligence was added so data could speak, not just sit on dashboards.

This shift reduced risk.

Instead of betting on one product, we enabled hundreds of use cases.

Why One Revenue Stream Is Never Enough

Another hard truth I shared with the audience.

Pure SaaS subscriptions rarely pay the bills in emerging markets.

We survived by building multiple streams.

Enterprise licensing.
Project-based solutions.
Training and certification with universities.

The platform stayed at the core. Everything else wrapped around it.

That balance kept the company alive.

Partners Build What You Cannot

No startup wins alone.

We built a partner ecosystem covering hardware, software, AI, and system integration. Today, that network spans multiple countries.

Each partner brings strength we do not have.

That is how scale really happens.

Marketing Without Big Budgets

We never had large marketing budgets.

So we wrote.
We shared.
We taught.

Blogs.
Social media.
Free e-books.

Inbound marketing works when your story is honest and your knowledge is real.

People do not buy immediately.
But they remember.

The Lesson I Hope You Carry Forward

I ended the lecture with a simple reminder.

Whatever path you take, it is building something inside you. Even when it feels random.

Do not fall in love with your product. Fall in love with solving problems.
Do not trust praise until someone pays.
Do not depend on one revenue stream.
Do not fear pivoting. Fear standing still.

And most of all, do not believe it is too late.

I started my startup at 56.

If I could begin then, what is stopping you now?

I would love to hear your thoughts.
What dots in your life are starting to connect? Share them in the comments.

When Writing Free eBooks Still Feels Like Shouting Into the Void

I did not expect this feeling to arrive so quietly.

No dramatic moment.
No emotional breakdown.
Just a soft question that kept returning while I stared at my screen.

Should I stop writing eBooks about IoT, startups, and entrepreneurship?

I have written several eBooks over the years. Some came from years of experience building platforms. Some from scars earned while running a startup. Some from observing founders struggle with the same blind spots again and again.

I made them free.
No paywall.
No upsell tricks.
Just knowledge, stories, and lessons shared openly.

Yet after my last three books (Hello IoT, The Favoriot Way: A Life Built on Curiosity and Courage, Favoriot : The Journey of an IoT Startup), something felt off.

Downloads slowed.
Shares dropped.
The quiet became louder.

At first, I blamed myself.

Maybe the topics are stale.
Maybe I am repeating myself.
Maybe people are tired of hearing from me.

Then another thought crept in.

Or maybe the world has changed.

The Moment I Could No Longer Ignore

I noticed something about my own habits before blaming anyone else.

I no longer Google as much.
I open ChatGPT.
I type a question.
I get an answer.

Direct.
Fast.
Clean.

And here is the uncomfortable truth.

I am guilty too.

I ask AI to summarise books.
I ask for key takeaways.
I skim instead of sitting with pages.

Who am I to complain when I do the same thing?

That realisation stung.

Because I used to love reading slowly. Highlighting sentences. Rereading paragraphs. Letting ideas sit for days.

Now, time feels compressed. Attention feels borrowed. Everything competes for mental space.

The Silent Shift No One Talks About

This is not about AI replacing writers.

It is about AI changing readers.

People no longer want to search.
They want answers.

They no longer want ten blog posts.
They want one response.

They no longer want to explore.
They want to arrive.

Why buy a book when a prompt gives you a clean summary?

Why spend hours reading when minutes feel enough?

That question hurts writers, but it is not wrong.

Books were once a journey.
Now they are treated like databases.

Tell me what matters. Skip the rest.

Short Attention Is Not a Moral Failure

I hear people complain about attention spans all the time.

But I do not think it is laziness.
I think it is survival.

We are flooded with inputs. Messages. Alerts. Updates. Noise.

Reading a 150-page eBook feels heavy when your mind is already full.

The new generation did not lose patience.
They adapted to overload.

They want clarity, not volume.
Direction, not depth.

At least not by default.

When Free Still Feels Expensive

Making my eBooks free was supposed to remove friction.

Yet free does not mean easy.

Reading still costs time.
Thinking still costs energy.

AI removed that cost.

One prompt feels cheaper than one chapter.

So why am I surprised?

The Hard Question I Keep Avoiding

I keep asking myself something uncomfortable.

Am I writing for impact, or am I writing out of habit?

In the past, writing eBooks felt like leaving a trail behind. Something lasting. Something searchable. Something meaningful.

Now it feels like throwing paper planes into a sky full of drones.

They fly faster.
They reach further.
They respond instantly.

Paper planes still matter.
But fewer people look up.

Books Versus Conversations

AI feels like a conversation.

Books feel like a lecture.

That difference matters.

People want interaction. They want follow-up questions. They want context tailored to their situation.

A book cannot ask back.

AI can.

And that changes expectations.

What Writing Used to Give Me

I did not write eBooks just for readers.

I wrote to think.

Writing forced clarity.
It slowed my thoughts.
It made experiences visible.

If I stop writing books, what replaces that?

Blogs?
Short posts?
Conversations?
Voice notes?

I do not know yet.

That uncertainty is unsettling.

Maybe Books Are No Longer the First Door

Here is a thought I am still wrestling with.

Books may no longer be entry points.
They may become reference points.

Not where people start, but where they return when they want depth.

AI gives direction.
Books give texture.

AI answers questions.
Books explain why the questions matter.

But fewer people reach that stage.

The Ego Check I Needed

Another truth I had to face.

I assumed free meant valuable.
I assumed experience meant relevance.

Neither guarantees attention.

The world does not owe writers readers.

Attention is earned every day.

Even by those who have written before.

Am I Really Stopping?

When I say I feel like stopping, I am not quitting writing.

I am questioning the format.

Maybe eBooks are not where my thoughts want to live anymore.

Maybe ideas want to breathe in smaller spaces.
Or in stories.
Or in conversations.

Or maybe fewer books, written slower, with deeper intent.

I am not sure yet.

What I Do Know

AI has changed how we read.
AI has changed why we read.
AI has changed when we read.

That shift is real. It is not a phase.

Fighting it feels pointless.

Understanding it feels necessary.

The Choice In Front of Me

I can keep writing eBooks and accept fewer readers.

I can stop writing books and find new ways to share ideas.

Or I can redefine what a book means in a world that no longer reads the same way.

Right now, I am sitting with the discomfort.

No dramatic announcement.
No final decision.

Just honesty.

A Quiet Ending With an Open Question

I still believe ideas matter.
I still believe stories shape thinking.
I still believe writing is worth doing.

But I no longer believe format guarantees relevance.

Maybe the real question is not whether I stop writing eBooks.

Maybe it is whether I am brave enough to write differently.

If you are a writer, a reader, or someone who quietly stopped reading books, I would love to hear your thoughts.

Have you felt this shift too?

Books Written by Dr. Mazlan Abbas

Success is a Decision: My CEO Journey

SUCCESS IS A DECISION, NOT A MIRACLE.

I still remember standing at my own “two doors” moment.

On one side was comfort — a stable career, predictable days, and a familiar path.
On the other was uncertainty — risk, sleepless nights, and the weight of leading something that didn’t even exist yet… FAVORIOT.

Becoming a CEO wasn’t something that happened overnight. It was a choice.

A choice to leave behind the safety of titles and the illusion of stability.
A choice to start from zero when people around me thought I’d already “made it.”
A choice to believe in an idea when others only saw obstacles.

That first day as CEO, there was no red carpet waiting. No big office. No team of hundreds. Just a laptop, a vision, and an endless staircase marked by courage, patience, discipline, and focus.

Every step demanded something.
Courage to face rejection.
Routine to build momentum.
Focus to silence the noise.
Discipline to show up — even when no one was watching.
And patience… the hardest of all.

Because success wasn’t a miracle waiting to happen. It was a series of small, stubborn decisions.

Each time I faced a setback — a failed pitch, a cancelled project, a delayed payment — I reminded myself why I opened that “new life” door in the first place.

Years later, FAVORIOT stands not just as a company, but as proof that choosing the harder door can change everything.

If you’re standing between comfort and courage right now…
remember this — your new life begins the moment you decide to walk through that door.