📡 The Problem Is No Longer Finding News. It's Knowing Which Stories Matter.

We have never had access to so much information.

At any moment we can know what is happening in artificial intelligence, technology, markets, or practically any industry.

The problem is that having more information does not necessarily mean being better informed.

Every day hundreds of news items, posts, announcements, press releases, and analyses appear. Many talk about the same thing. Some make a lot of noise and turn out to be unimportant. Others go almost unnoticed and may be showing something much more interesting.

And in the middle of all that, you still have to decide what really deserves your attention.

When I started ViaMind Journal and got deeper into artificial intelligence, I also started experimenting with agents, automations, and different ways of building with AI.

At some point both paths crossed.

I like technology, telecommunications, AI, and understanding where these industries are moving.

But I did not want to create another site that simply accumulates news.

The question that started to interest me was different:

Could I use AI to find signal inside all that noise?

Not to generate more content.

But to review far more than one person could review, compare different sources, discard what is repeated, and select only the stories that really seem important.

And also try to explain why they matter.

That question is how ViaMind Radar was born.

What if AI did the heavy lifting?

The initial idea was to build a group of agents with different responsibilities: search for new stories, review different sources, discard duplicates, detect what may be truly relevant, and finally build a small selection worth reviewing.

That was the beginning of ViaMind Radar. The idea behind it is fairly simple: Less noise. More signal.

A radar for the things I want to follow

For now Radar is focused on four areas I follow constantly:

Artificial intelligence, telecommunications, technology and investments, and social trends related to technology.

The system reviews different sources daily and keeps selecting stories.

But finding news is only the first part.

The hard part is deciding which ones matter.

Because ten outlets may be talking about the same launch while a less visible story may be showing a regulatory change, new infrastructure, or a business decision with much bigger consequences.

That is why I do not want Radar to publish everything.

I want the opposite.

For it to dare to discard.

Because if after reviewing hundreds of signals I end up with a hundred news items in front of me, I did not solve the problem.

I just built another source of noise.

It is not enough to say what happened

I also wanted to experiment with another way of presenting news.

Every outlet has its audience, its priorities, and a particular way of interpreting what happens. That is completely normal.

My idea was to try to build a ViaMind view: pragmatic, consistent, and focused on separating what was reported from interpretation.

I do not believe AI can be completely impartial or remove all bias.

But we can design a system that contrasts information and tries to answer a question that, for me, is much more interesting:

Why does this matter? What changes. Who may benefit. Who may lose. What could happen next. And when a story that looks huge may not be as important as the headline suggests.

A real example

While I write this, one of the stories selected by Radar is about a European Commission decision related to ChatGPT and the Digital Services Act.

At first glance it may look like just another European regulatory story.

But the signal behind it is much more interesting.

Europe is starting to treat services like ChatGPT under obligations similar to those it applies to large information intermediaries.

That means new transparency, audit, and risk management requirements.

But it also shows something deeper:

the line between a chatbot and a search engine is starting to blur.

If an assistant answers our questions, searches the Internet, selects sources, and decides what to show us, it starts to occupy a place that until recently belonged mainly to traditional search engines.

And if that happens, regulators also start looking at it differently.

The consequences may go far beyond OpenAI and affect other assistants that incorporate search, navigation, and direct access to information.

That is exactly the kind of story I want Radar to find.

Not only knowing what happened.

Understanding what may change from there.

Radar is not trying to replace journalism

This also seems important to me.

ViaMind Radar is not trying to replace media outlets or the people who investigate and produce the original stories.

In fact, it depends on them.

Without good sources, journalists, analysis, documents, investigations, and people generating information, there would not be much to analyze.

Radar tries to build another layer on top.

One capable of searching, comparing, filtering, and explaining.

Because maybe one of our current problems is not a lack of information.

It may be exactly the opposite.

I ended up learning much more than AI

When I started I thought this would mainly be a technology project.

It was not.

Building it forced me to learn about source selection, relevance, duplicate stories, front pages, context, communication, and editorial criteria.

And especially about a question that seems simple but is not:

What makes a story truly important?

AI can review enormous amounts of information.

But deciding what deserves our attention still needs judgment.

And probably that combination between technology and judgment has been one of the most interesting parts of building Radar.

Who is it for?

For people who want to follow technology without having to follow everything published about technology.

People who work in artificial intelligence, telecommunications, technology, or business, but also those who simply want to understand what is changing and why.

I do not want someone to spend an hour inside ViaMind Radar. In fact, if it works well, the opposite should happen: enter, quickly understand what is happening, find a few interesting stories, and move on with your day.

And maybe this could go much further

Radar started focused on the areas that interest me most.

But talking about the project with friends and people related to communications, an interesting possibility appeared.

The editorial engine does not have to talk only about technology.

The same principle could be used for sports, education, health, gaming, energy, markets, or practically any industry.

A sports Radar could review hundreds of sources and select the stories really moving football or basketball.

A company could use something similar to follow competitors, regulators, suppliers, or a specific industry daily.

It could even work inside an organization to watch very specific topics and deliver the important signals without different teams constantly reviewing dozens of sources.

The logic would be practically the same:

good sources, good criteria, and a system capable of finding signal inside a lot of noise.

I think there is a lot to explore there.

But I do not want to get ahead of myself.

First I want it to do one thing really well

My focus now is much simpler:

I want to build a technology Radar that I myself want to open every day.

One that lets you understand in a few minutes what is happening in AI, telecommunications, and technology without visiting twenty sites, opening dozens of tabs, or reading five versions of the same story.

It is still a work in progress.

There are sources to add, criteria to improve, mistakes to fix, and many ideas I want to try.

But it already passed a test that was quite important to me:

I am using it myself.

Today I open Radar every day and I almost always find a story I had not seen and want to keep investigating.

And that, in a way, goes back to the problem this all started with.

We have more information available than ever.

The hard part is no longer finding it.

The hard part is knowing which stories deserve our attention.

ViaMind Radar is my first attempt to solve that problem.

There is still a lot to do, but so far I am quite happy with the result.

And we are just getting started.

📡 ViaMind Radar — Less noise. More signal.

It is already running and selecting new stories every day.

You can explore it at viamindradar.com.

Related reading:

• AI Did Not Give Me New Ideas. It Gave Me a Way to Build Them.
• The AI Bill: the Problem Almost Nobody Is Talking About
• When Jira Is Not Enough: How I Built My Own AI Planning System

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✍️ Claudio from ViaMind

“Dare to imagine, create and transform.”

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