I believe in adding real value.

Not as a management platitude — as a first principle. Every person, in their professional and personal life, should be adding value to someone. From your own knowledge to your company. From your company to your customers. From your personal experience to the people around you.

This is the quintessence of life in society. We are all interconnected. We generate problems for each other, and we generate the solutions to those problems. The whole structure of civilisation is, at its core, a network of value exchanges — some of them transactional, some of them invisible, most of them taken for granted.

I’ve believed this for a long time. But I believe it more urgently now than I ever have. Because we are entering an era where the question of who is actually adding value — and who is merely processing information in circles — is about to be answered in the most unambiguous way possible.

The great clarification

Every repetitive white-collar job that adds no real value to the customer is going to be replaced by an agent running on artificial intelligence. The data entry. The format conversion. The report assembly. The meeting summary. The first draft of the document that everyone edits into the same document it was before.

I want to be clear about this: that is good news.

Not for the people whose jobs disappear, in the short term. That disruption is real and the transition will be uncomfortable for many. But at the systemic level, what is happening is a clarification — an enormous, accelerating, irreversible clarification of what human work is actually for.

Whether the model is sitting in a data centre owned by Anthropic, OpenAI, or Google, or whether it is open source and running on a local server with a couple of GPUs in your basement — it doesn’t matter. Intelligence is becoming a commodity. The ability to move digital information from one format to another, to synthesise a document, to draft a response, to classify an input — these are things AI can do today, in many contexts, better and faster than we can. That window is not closing.

What this means is that the tasks which remain — the ones that resist automation, the ones that require judgment, the ones that require someone to be accountable for the outcome — those tasks are now more visible than they have ever been. They were always the hardest. They were always the most valuable. But for decades, they were buried under layers of process, bureaucracy, and low-value activity that consumed the majority of most professionals’ working days.

The agents are clearing that ground. What’s left standing is the work that actually matters.

What I’ve seen from the inside

I’ve been building technology products for fifteen years — across modem programs at Intel that ended up in multiple generations of the iPhone, across eight years founding and running Eccocar as a B2B SaaS platform with enterprise clients, and now directing a sovereign data space at UC3M.

In that time, I’ve watched technical acumen go from being an asset to being table stakes. Knowing a tech stack deeply — and being able to deploy solutions with high margin — was always valuable. But for most of my career, deployment cycles were slow, debugging was expensive, and the distance between idea and shipped product was measured in weeks and quarters, not hours.

The tools changed everything about that.

What used to be a three-week cycle to find a bug, understand it, plan a fix, implement it, test it, and deploy it — is now fifteen minutes. Not because the thinking got easier. Because the execution layer got dramatically cheaper. We don’t spend seven meetings analysing a mistake. We ship a fix, observe what happens, and move forward. The feedback loop compressed by an order of magnitude.

The result is not that thinking matters less. It’s that thinking is now the primary constraint. When execution is cheap, the thing that limits you is the quality of the decision that precedes it. When prototyping is fast, the bottleneck is the clarity of the hypothesis being tested. When code can be generated, reviewed, and deployed in minutes, what differentiates outcomes is whether the person directing that process understands what they are actually trying to build — and why.

This is the shift that most discussions about AI in the workplace miss. They focus on what gets replaced. The more interesting question is what gets revealed.

The skills that compound

Technical acumen still matters — more than ever, actually. But it now means something different. It is less about the ability to write code fluently, and more about the ability to design systems: to understand how components interact, where failure propagates, what the second-order effects of a change will be.

The professionals who will compound in value over the next decade are the ones who can do three things simultaneously:

They can see the system — not just the task in front of them, but the workflow it belongs to, the problem it is solving, and the constraints it operates within.

They can make decisions under ambiguity — not wait for complete information, not escalate indefinitely, but form a judgment and commit to it while staying open to revision.

And they can take accountability for outcomes — not just for outputs. Not “I delivered the report” but “I improved the thing the report was supposed to improve.”

These skills were always the hardest to develop and the hardest to hire for. What’s changed is that AI is making it impossible to hide behind the other kind of work. The gap between someone who has these skills and someone who doesn’t is widening faster than any point in my career.

Why I’m writing this

I am not writing this to warn anyone. The tone of most AI commentary oscillates between breathless optimism and existential dread, and I find both exhausting.

I’m writing it because I think the value-addition frame — the simple, human idea that we are here to be useful to each other — is the most practical lens for understanding what is happening. The question is not whether AI will change your job. It will. The question is whether, when the process layer is stripped away, there is genuine value underneath.

For most people who are good at what they do, and honest about it, the answer is yes.

The agents are not coming for the value. They’re coming for the noise around it. And clearing that noise — if we let it — is the opportunity of a generation.

Fernando Martín is Managing Director of NEXMO Movement Data Hub (UC3M), Venture Builder at MOVEN, and founder of Eccocar. He writes here about venture building, AI agent operations, and the European technology landscape.

The Invariance — by Fernando Martín
In a constantly evolving world, only value is the invariance that holds everything together.

Thanks for reading. If this resonated, share it with someone who needs to read it.

Leave a comment