Natives of uncertainty

We created nosDeu at a time when almost everything seems to be up for review. Artificial intelligence is changing the way we work, create, decide, and solve problems. Many tasks that until recently seemed complex are being democratized, and others, which we still don't know how to name or imagine, will appear along the way.

One of the reasons for trying was precisely the need to build a project with freedom of movement, capable of learning fast, adapting, and continuing to contribute even if tools, formats, or the way of working change.

Today it is artificial intelligence, but tomorrow it will be something else. The need to solve problems will still be there, and what we want to nurture is the ability to understand, test, relearn, and build useful solutions without getting trapped in a single way of looking at the world.

We like to look at the present and imagine the future with curiosity. From a place of optimism, it is easier to learn, experiment, play, make mistakes, and build solutions that have a positive impact on society. Not because we ignore risks, but because looking at the future solely through the lens of threat reduces our ability to act.

AI with sentidiño

We could have jumped on the bandwagon of claiming to be AI first, but what we really like to be is AI with sentidiño.

Artificial intelligence, or any new technological paradigm, cannot be the automatic answer to any question or problem. It can speed things up a lot, and precisely for that reason, it is best to use it calmly: knowing when it contributes, when it gets in the way, when to automate, when to review, and when to let a person look at something with more context.

It is also worth remembering something uncomfortable: generating is not finishing. If we use AI to send without reading, without understanding, and without working, we will only be contributing to what we at Datola call the shittification of deliverables (https://datola.es/newsletter/la-mierdificacion-de-los-entregables/), or workslop.

For nosDeu, sentidiño means not confusing speed and flashiness with value. It means using AI to better care for processes, broaden our judgment, and build solutions that truly add value.

Relearning

What is valid today might not be tomorrow.

It has always been this way, even though now we feel it closer, faster, and more evident. That is why one of the most important, and also most beautiful, capabilities of this era is relearning.

Relearning allows us to bring together the judgment that experience gives with the curiosity of looking at something again as if we still didn't fully know how it works.

We do not want to defend a way of doing things just because it is what we learned, because it worked for us for years, or because it gives us a certain sense of security. We enjoy questioning our processes, deliverables, meetings, reports, tools, metrics, and ways of collaborating, not to live in a permanent state of upheaval, but to avoid getting trapped in inertias.

There is a phrase we really like: "Since they didn't know it was impossible, they did it."

It reminds us that many times the biggest blockage is not in the real difficulty, but in everything we take for granted before trying: in the "we've always done it this way," the "that can't be done," or the "it's not worth trying." It's not about ignoring what we have learned or denying our limits, but about not turning them into a cage.

Do not delegate knowledge

We want to use artificial intelligence without delegating knowledge to it.

We are interested in having it help us think, not think for us. Having it help us cross-reference, organize, document, detect errors, explore paths, and build faster, without losing the ability to understand what we are doing.

Every interaction with a machine should make us a little smarter, not a little more dependent. It should help us learn, decide with better judgment, and build solutions that contribute something positive to society.

Delegating tasks can make a lot of sense, but delegating judgment does not.

AI can be a tremendous companion as long as we keep taking care of what matters: context, responsibility, memory, learning, and the ability to ask better questions. Because the difficult part won't be using a new tool, setting up an agent, or automating a task. The difficult part will still be properly understanding what problem we want to solve.

Sometimes it will be with AI, sometimes it will be an automation, sometimes it will be organizing data better, changing a process, having a pending conversation, or stopping doing something.

And in all those cases, the decision will still be ours.

The advantage was never the tool

With artificial intelligence, many advantages will be short-lived. Models will change, interfaces will change, and tools that seem magical today will be just another feature tomorrow. What seems differential today because of knowing how to use a specific technology may stop being so in a very short time.

ències.

The advantage was never just squeezing the tool, even though that sometimes helps. It lies in everything that allows using it with sense: understanding problems well, caring for context, having reliable data, designing clear processes, avoiding unnecessary dependencies, and continuing to relearn.

Because when everyone has access to similar tools, the difference will lie in who better understands what to do with them, what is not worth doing, and what problem they are trying to solve.

We will keep solving

Sometimes we think problems are like energy: they are neither created nor destroyed, they are transformed.

Tools, formats, and ways of working change, but deep down, similar questions keep appearing: what do we need to understand, what can a machine do better, what needs human judgment or perspective, and where can we add the most value.

What we do today might not make sense tomorrow, but that doesn't scare us. It reminds us that we are still part of something alive.

We are in a wonderful era to learn, build, and enjoy the journey.

To this life, and to this project, we only ask for energy, curiosity, and motivation in infinite doses.

The rest will change.