We already have the tools. What are we building?

We already have the tools. What are we building?

We were kids when my dad used to rent VCDs from Video City.

Yes, VCD pa talaga.

Netflix and Prime Video did not exist in our world during the early 2000s. Entertainment meant choosing a disc, loading it into the player, and hoping it would not freeze halfway through the movie.

One of the films my dad brought home remains a core memory to this day.

That film was Enemy at the Gates.

Back then, Taguig had not officially become a city yet. In the place where I grew up, people somehow knew whenever my dad had rented another movie.

We would connect our VCD player to an old 14-inch Sony CRT television. Just like that, our living room became a miniature cinema.

Puta, those were golden days!

I still remember some of my playmates losing their flip-flops after our “film showings”. Everyone rushed home as soon as the credits rolled, and apparently footwear became optional during evacuation.

One scene from Enemy at the Gates stayed with me.

The film depicted Soviet soldiers being sent into battle against the Nazis. Some were handed rifles. Others received only ammunition. If the soldier carrying the rifle died, the next man was expected to pick it up and continue fighting.

One of our neighbors joked:

> “Wow, only one lucky asshole will survive”

As a kid, that scene made me nervous. I kept wondering how Vassili Zaitsev, played by Jude Law, was supposed to survive the war.

I was not conducting a historical accuracy audit at that age. What stayed with me was the image of scarcity.

2 soldiers.

1 rifle.

1 supply of ammunition.

Every resource had to find its purpose.

Fast-forward to 2026, and our problem is almost the exact opposite.

We are surrounded by tools.

We have cloud platforms, open datasets, programming frameworks, free documentation, and artificial intelligence capable of helping us write, analyze, design, and build.

We have more computational firepower than any generation before us.

The tools are no longer scarce. But the intention is.

During the 3rd quarter of last year, I wanted to create a simple weather-monitoring page.

Nothing close to UP NOAH, of course. Those guys are already playing in the Champions League of meteorology.

I simply wanted to observe weather systems approaching the Philippines.

While browsing different weather visualizations, I noticed that some used imagery from the Himawari satellite series operated by the Japan Meteorological Agency.

That gave me a question:

> If I wanted to create my own animated weather imagery, where would I get the data?

My first instinct was to scrape images from other weather websites.

That approach led nowhere.

Then I realized something embarrassingly obvious.

> Why not go directly to the source?

The satellite images were publicly accessible from JMA itself.

The path looked something like this:

``text https://www.data.jma.go.jp/mscweb/data/himawari/img/se2/ ``

From there, I found files with names such as:

``text se2_b13_0200.jpg ``

The filenames followed a predictable pattern. Each image corresponded to a particular observation time.

Collect enough frames, arrange them chronologically, and you can produce an animation showing weather systems moving across Southeast Asia.

That discovery did not come from AI.

There was no magical prompt that handed me the idea.

No chatbot woke up one morning and decided that I needed a weather page.

It began with ordinary bloke curiosity.

I had a question. I followed the data. I found the source. Then I decided what I wanted to build.

AI entered the process afterward.

Once I understood the data source and the result I wanted, I used AI to help write parts of the code. It assisted me in building a serverless Node.js workflow that retrieved and processed the available satellite frames.

The idea was mine.

The implementation became a collaboration.

The result remains online today:

View the Himawari weather imagery project

> Source imagery: Japan Meteorological Agency. The frames are retrieved, processed, and animated by the author. This experimental page is not an official weather forecast. Consult PAGASA and local authorities for official warnings and emergency guidance.

Thank you to the people at JMA for keeping this scientific resource publicly accessible to researchers, weather enthusiasts, and independent builders.

Arigatō gozaimasu!

Because of their work, I can observe weather patterns affecting the Philippines from space.

More importantly, I now have a better idea of when I should do the laundry.

Para hindi maulanan. Hahaha.

That small project clarified something for me about artificial intelligence.

AI does not supply purpose.

It amplifies whatever purpose the human brings to it.

If the objective is to manufacture fake news, generate rage bait, or flood social media with nonsense, AI can make that process faster.

If the objective is to study weather patterns, learn a technical skill, or build something useful, AI can accelerate that too.

The tool does not choose the target. We do.

Vassili’s battlefield was scarcity. Ours is abundance without direction.

We already have access to the tools. We also have enough documentation to learn how most of them work.

What we often lack is a clear reason for using them.

Why not use AI to understand weather patterns?

Why not use it to help communities prepare for disasters?

Why not use it to learn?

We live in one of the most disaster-prone regions in the world. The Philippines regularly experiences typhoons, floods, earthquakes, volcanic eruptions, and other natural hazards.

That gives us countless opportunities to use technology as a force multiplier for work that actually matters.

I am not the first person to build a weather page.

Far from it.

Many people have done it before me, and many have done it far better.

I simply wanted to experience the process myself.

I wanted to begin with a question, locate the source, understand the problem, and produce something that worked.

AI did not give me the curiosity.

It did not decide what mattered to me.

It did not wake up and worry about whether my laundry would get soaked.

The human supplied the purpose.

AI helped with the execution.

If a random guy with curiosity and access to AI tools can build something like this, imagine what students could create.

Imagine what teachers could encourage.

Imagine what parents could guide their children toward building.

I hope we teach the next generation not only how to use AI, but why they should use it.

The prompt does not create purpose.

The person writing it does.

Sometimes the best use of cutting-edge technology is not building the next billion-peso or billion-dollar startup.

Sometimes, it is simply helping Mommy decide whether today is a good day to do the laundry.