DEV Community: 🎓 Navid Ishaq

The Day 35 MCQs Marched Into Moodle Like They Owned the Place! 🚀😂

🎓 Navid Ishaq — Fri, 16 Oct 2026 07:38:54 +0000

An innocent Word document, a stubborn Moodle import, and a little converter that changed the whole story.

It Started With a Word Document...

There they were.

Thirty-five beautiful multiple-choice questions, sitting comfortably inside a Microsoft Word document.

Some spoke Spanish. Others translated everything into English.

A few carried pictures. Every question knew its correct answer.

They were organised. They were ready. They were excited.

They had only one dream.

To become a Moodle quiz. 🎓

And I thought, How difficult could that possibly be?

Famous last words.

Then Moodle Entered the Story... 😳

Moodle was waiting.

But getting those questions inside wasn't going to be as simple as opening the door.

Copy the question.

Paste the question.

Add the answers.

Mark the correct one.

Arrange the formatting.

Check the image.

Repeat.

Again.

And again.

By the fifth question, I was already looking at the remaining thirty like they were planning something against me.

The questions seemed perfectly happy.

I was not.

"Come on, guys," I thought. "There has to be a better way!"

Then Came a Little Idea... 💡

What if I didn't have to carry every question into Moodle myself?

What if I could build a little digital transporter?

Something that could look at my Word document, recognise the questions, understand the answer options and prepare everything in a format Moodle could read.

I started experimenting with Python and AI-assisted development.

A little code here.

A little testing there.

A few errors.

Some more testing.

And then...

The converter was born. ⚡

Not a giant platform.

Not some mysterious supercomputer.

Just a useful little tool with one important job:

Take my MCQs from Word and get them ready for Moodle.

The Secret Ticket Was Called GIFT 🎁

I discovered that Moodle understands a question-import format called GIFT.

And suddenly, the whole problem started looking different.

Instead of manually carrying questions into Moodle, I could prepare a GIFT file and let Moodle handle the import.

The new journey was beautifully simple:

Word Document → Converter → GIFT File → Moodle

That was it!

Well, almost.

The converter still needed to recognise the questions, identify their answers and check the structure.

And for questions with embedded images, Moodle XML offered another useful route.

But the idea was working.

My little digital transporter was ready.

The Moment of Truth... 🫣

Thirty-five questions.

Two languages.

Images.

Correct answers.

Everything waiting.

I ran the conversion process.

The program started doing its job.

Questions were identified.

Answers were matched.

Files were generated.

Twenty questions in one batch.

Fifteen in another.

And there they were.

My Moodle-ready files!

I looked at them with the kind of happiness only someone who has spent hours formatting questions can truly understand.

Now came the moment I'd been waiting for.

The Moodle import.

And in my imagination, something wonderful happened...

And Suddenly, the MCQs Started Jumping! 😂🎉

Question 1 put on its little graduation cap.

"I'm ready!"

Question 2 shouted, "Wait for me!"

Question 3 grabbed its answer options.

"Nobody gets left behind!"

And then...

WHOOSH! 🚀

Off they went.

One after another.

Spanish questions, English translations, correct answers — all heading towards their new Moodle classroom.

Question 19 was particularly excited.

Question 27 was waving at everyone.

And Question 35, the last one, turned around and shouted:

"FINALLY! NO MORE COPY AND PASTE!" 😂

Of course, the jumping MCQs were happening in my imagination.

But the relief was real.

A repetitive formatting problem had become an automation workflow.

And that felt wonderful.

The Little Lesson Behind the Big Smile ❤️

I love moments like this.

Not because the technology is unbelievably complicated.

But because a relatively small tool can make an irritating task much easier.

The questions didn't need changing.

The teacher didn't need to spend hours moving them manually.

The process needed a better route.

That's something I keep exploring through DeTLeng, my wider ecosystem of practical digital tools, learning environments and automation experiments.

Sometimes the most useful digital solution isn't a massive application.

Sometimes it's a small converter quietly doing a job that nobody wants to repeat.

And sometimes, in your imagination, it's thirty-five happy MCQs dancing their way into Moodle. 💃🕺

The End? Not Quite...

The first converter was a desktop-based Python tool.

But why stop there?

I can imagine a day when someone opens a website, drops in a Word document, chooses the questions they want and clicks one button.

No complicated setup.

No endless formatting.

Just a simple route from questions to a Moodle-ready file.

That's the direction I'd love to take this little project next.

Because the best part about building something useful?

Once it solves your problem, you start wondering whose problem it could solve next.

And the Moral of the Story?

If your questions are sitting in Word, dreaming of a better life inside Moodle...

Don't make them travel one by one.

Build them a bus! 🚌😂

And if the bus happens to be powered by Python, automation and a little AI-assisted creativity?

Even better.

Keep building. Keep experimenting. And never underestimate the power of solving one small problem.

Happy learning, happy automating — and happy MCQs! ❤️

— A self-taught builder exploring practical technology through DeTLeng.

python #automation #moodle #education

I Thought I Was Getting Into Meta's Muse AI. Then Came the Waitlist. 😭

🎓 Navid Ishaq — Thu, 15 Oct 2026 07:59:29 +0000

One YouTube thumbnail. One excited AI enthusiast. One registration journey. And one unexpected lesson about user trust.

It All Started With a YouTube Thumbnail

October 15, 2026.

Just another ordinary morning in Spain.

I opened YouTube, casually browsing through videos about AI, technology, and all the interesting things happening in this rapidly changing world.

Then something caught my attention.

"MUSE — Complete Tutorial"

Underneath the thumbnail was a website address:

muse.ai

Muse? What is Muse?

A new AI tool? A research assistant? Another chatbot? Something completely different?

I had no idea.

But curiosity is a dangerous thing when you love experimenting with technology. 😄

Within seconds, I opened the website.

I noticed Meta's branding.

Oh! So this was connected to Meta.

Now I was even more interested.

Enter My Old Friend, ChatGPT

Like many self-learners, I have a habit.

Whenever I discover a new technology, I start asking questions.

What is it? Who built it? What does it do? Why does it exist? And most importantly:

What can I learn from it?

So I asked ChatGPT about Muse.

My AI friend explained that Meta had launched Muse as a personal AI agent in September 2026.

Interesting!

But then came the disappointing part.

Muse was not generally available in Spain, where I live.

I stopped reading.

Wait a minute.

Let me check that myself!

I returned to the Muse website.

And there it was.

A login option.

A beautiful opportunity to prove my AI assistant wrong! 😂

I thought:

"Today, my dear ChatGPT, I am going to show you that your information is outdated!"

Oh, the confidence!

If only I knew what was coming.

The Login Button That Gave Me Hope

I clicked the login option.

A box appeared in the middle of the page.

Enter your email address.

Simple enough.

I entered my email.

Next came a verification step.

Check your email and enter the confirmation code.

No problem!

I opened my inbox, found the Meta verification message, copied the code, and entered it.

Everything seemed to be working.

My excitement was growing.

Then came the next screen.

First name.

Surname.

Date of birth.

Fine!

I filled in the requested information.

At this point, I was genuinely excited.

Email verified? Check.

Personal details entered? Check.

Registration moving forward? Check.

Surely the next screen would be my shiny new AI agent!

I imagined exploring Muse, discovering its capabilities, and perhaps learning something useful for my own AI automation experiments.

I clicked to continue.

And then...

BOOOOOOM! 💥

The screen displayed:

Join the waitlist for Muse

Muse isn't available in your country or region yet. We'll let you know when it's available to you.

And underneath?

A bright blue button.

Join waitlist

...

Wait.

WHAT?!

😭😭😭

My excitement disappeared.

For a moment, I just stared at the screen.

I had verified my email.

I had entered my name.

I had provided my date of birth.

I had followed the registration process.

And only now was I being told that the service was unavailable in my region?

My dear Muse...

Couldn't you have told me that BEFORE asking for my details?

I did not click the waitlist button.

I was too disappointed.

For a moment, I felt completely frozen.

Was This a Scam? No, That's Not My Claim.

After the initial shock, I started thinking more carefully.

I am not claiming that Meta intentionally deceived me.

I am not claiming that my personal information was misused.

And I cannot say from this experience alone what information was retained or how it was processed.

There may be legitimate technical reasons for the registration sequence.

For example, the process may involve creating a general Meta account, verifying identity, or checking age eligibility before determining which services someone can access.

I understand that.

But there is still a user-experience question worth asking.

If regional availability is already restricted, why not make that information clear before the user begins providing personal details?

That is the part I found disappointing.

The Real Problem Wasn't the Waitlist

Let's be clear.

I have no problem with a company releasing its product in selected countries first.

Products need infrastructure, testing, regulatory preparation, support, and gradual rollouts.

That's understandable.

My disappointment was about the sequence of information.

I entered the process believing I was getting closer to the product.

Every completed step increased that expectation.

Email verification felt like progress.

Entering personal details felt like progress.

Continuing to the next screen felt like progress.

Then the final message changed the entire meaning of the journey.

What I had interpreted as progress toward access turned out to be a registration process that did not give me access to Muse.

And that distinction matters.

A Small UX Change Could Make a Big Difference

Imagine a different experience.

A visitor opens Muse.

Before requesting an email address, the website explains:

"Muse is currently available only in selected regions. Please check availability before registering."

The visitor selects their country.

If Muse is unavailable, the website offers an optional waitlist.

Only then does it request the information necessary for that specific purpose.

That would be a much clearer experience.

For me, the ideal order would be:

Check Availability → Explain the Purpose → Request Necessary Information → Obtain Consent → Continue

Of course, eligibility checks are not always simple. Location detection can be imperfect, and some restrictions depend on more than a user's current country.

But that is an engineering and design problem worth solving.

The central idea is simple:

Don't let users discover an important eligibility restriction only after they have invested time and disclosed personal information, if that restriction could reasonably have been communicated earlier.

What This Taught Me About AI Ethics

I am not a traditional software developer.

I am a self-learner who enjoys experimenting with AI, websites, data tools, and automation.

Through my DeTLeng projects, I have built AI-assisted learning tools, data dashboards, and automation workflows.

One thing these experiments have taught me is that software is not just about making something work.

It is also about the experience of the person using it.

A technically successful process can still create a disappointing human experience.

An automated workflow can complete every step and still fail to respect a user's expectations.

And a beautifully designed interface can still create confusion if important information arrives at the wrong time.

That is why I believe good AI products need more than intelligence.

They need transparency.

They need thoughtful design.

And they need to earn trust.

Trust should not be an afterthought in the user journey.

And What Happened to My Excited AI Adventure?

Well...

I did what any disappointed technology enthusiast with a long-standing AI friendship might do.

I ran straight back to ChatGPT! 😂

A few minutes earlier, I had been preparing to celebrate proving my AI assistant wrong.

Now I was explaining how the registration process had raised my hopes before ending with a regional restriction.

Quite a plot twist!

But after the disappointment came a useful idea.

Why not turn the experience into a story?

Not an angry attack.

Not an accusation.

Just an honest account of one user's experience, with a little humor and a serious question about how we design technology.

And that is how this article was born.

My Takeaway

I still find Muse interesting.

I still want to explore new AI agents.

And I will continue experimenting with technology.

But this experience reminded me of something important:

A product can be technologically impressive and still have room to improve the way it treats its users.

If we want people to trust AI systems, we need to think about the small moments too.

The registration forms.

The eligibility messages.

The permissions.

The explanations.

And the expectations we create along the way.

Because behind every email address and every form submission is a real person.

Sometimes an excited person.

Sometimes an impatient person.

And sometimes a 56-year-old AI enthusiast in Spain who just wanted to play with a new technology! 😄

Over to You, DEV Community

I'm curious about your perspective.

Should an AI service check regional availability before requesting personal information, or is it reasonable to complete account registration first?

How would you design this onboarding experience?

I'd genuinely love to learn from developers, UX designers, and privacy-minded engineers.

Keep learning. Keep questioning. Keep building.

— A self-learner turning everyday technology experiences into practical lessons.

DeTLeng: https://www.detleng.com/

I Got Tired of Formatting Blog Posts, So I Built My Own Publishing Tool with AI

🎓 Navid Ishaq — Wed, 14 Oct 2026 21:15:18 +0000

One article. Six design styles. A reusable publishing workflow.

My Problem Wasn't Writing. It Was Everything After Writing.

I enjoy writing about technology, AI, education, and my experiments with digital solutions.

But every time I wanted to publish an article on Blogger, the same repetitive work appeared.

Formatting headings. Adjusting layouts. Adding branding. Inserting my standard header and footer. Making everything look consistent.

I thought:

Why am I repeating the same work when a computer could do it for me?

So I decided to build a little tool.

Not a massive application. Not another expensive subscription.

Just something useful.

Meet My Little Publishing Factory 🏭

I developed a Python-based article converter as part of my self-learning journey, using AI as a learning and development partner.

Here's my workflow:

Write my article in Microsoft Word or Markdown.
Run a simple Windows batch file.
Choose one of six predefined design styles, or let the converter select automatically.
Generate Blogger-ready HTML in a text file.
Copy, preview, and publish it in Blogger.

That's it!

My converter already knows my preferred layouts, branding, headers, and footers.

The six styles cover different kinds of content, from professional business articles and educational posts to technical tutorials and editorial writing.

For example, I recently selected my Navy Orange Editorial design.

The converter processed my Word document and produced the formatted HTML.

No need to rebuild the entire design for every article.

And importantly, I still review the output before publishing.

Here's What I Learned

I'm not a traditional software developer.

I've explored Python, databases, cloud platforms, automation, and web technologies through self-learning and hands-on experimentation.

AI has helped me explore ideas, understand problems, and develop practical solutions.

But I discovered something more valuable than simply asking AI to write code.

The real skill is learning to explain what you want to accomplish.

Instead of saying:

"Build me something with Python."

Try explaining:

"I publish articles regularly. My formatting is repetitive. I want a tool that takes a Word document, applies my preferred design, and generates HTML that I can paste into Blogger."

Now you have a real problem, a clear workflow, and an outcome you can test.

That's where useful building begins.

You Can Try This Approach Too

You don't have to start with a complicated application.

Find one task you repeat regularly.

Document how you do it today.

Ask AI to help you simplify the process. Test the result, understand what it does, improve it, and keep yourself responsible for the final output.

Your first tool might save only five minutes.

But the next time you use it, those five minutes are saved again.

The goal isn't to automate everything. It's to stop repeating work that no longer needs your attention.

My Bigger Lesson

I used to think technology was mainly about learning tools.

Now I increasingly think it's about understanding problems.

You don't need to be an expert to begin experimenting.

You need curiosity, clear thinking, patience, and the willingness to learn when something doesn't work.

I'm still learning. Still making mistakes. Still building.

And yes, sometimes a simple script gives me more satisfaction than an entire complicated application. 😄

You can explore my published articles at DeTLeng Insights and my broader digital learning projects at DeTLeng.

What repetitive task would you automate if you had your own little AI-assisted development partner?

I'd love to hear your ideas in the comments.

Keep learning. Keep experimenting. Keep building.

— A self-learner turning everyday problems into practical digital solutions.

I'm Not a Traditional Developer — Here's How I Built Real Websites with AI

🎓 Navid Ishaq — Wed, 14 Oct 2026 20:20:01 +0000

I Didn't Start as a Developer

I'm a self-learner who believes that technology should not be limited to people with formal programming backgrounds.

Over time, I've experimented with Python, SQL, BigQuery, Supabase, cloud platforms, cybersecurity, and AI tools. I've created dozens of websites and numerous GitHub repositories through independent learning.

My main project is DeTLeng, where I explore learning, data, and practical digital solutions.

But here's something interesting: knowing what you want to build is sometimes more important than knowing how to code it yourself.

From Conversations to Working Systems

Recently, I worked with AI to develop an inquiry system for DeTLeng Automation.

The goal was simple: a visitor describes repetitive manual work, submits a request, and receives an email confirmation. Our team receives the details automatically.

The journey wasn't perfect.

GitHub push conflicts interrupted deployment.
Cloudflare DNS and Resend email verification required careful configuration.
Some emails landed in Spam/Junk.
Render's free service sometimes took 40–60 seconds to wake up.
Even a simple success popup needed testing and refinement.

We investigated each issue, tested the changes, and kept improving.

Eventually, the email workflow and confirmation popup worked.

What AI Actually Taught Me

AI didn't eliminate the need to think.

I still had to explain requirements, understand problems, review results, protect existing functionality, and decide what needed fixing.

AI helped with implementation. I remained responsible for the decisions.

That's an important distinction.

You don't need to pretend to be an expert. You need curiosity, patience, clear communication, and the willingness to learn from mistakes.

Try It Yourself

Visit DeTLeng Automation and explore our Automation Desk.

If you have a real repetitive task, describe it through the form. You don't need technical terminology. Just explain what you do manually and what you wish could happen automatically.

The future of building software isn't only about who can write code. It's also about who can identify problems, ask better questions, and turn ideas into working solutions.

Keep learning. Keep experimenting. Keep building.

— A self-learner building with AI, one challenge at a time.