Technology companies had a record of hiring in Argentina during the first half of 2023, incorporating almost 30,000 new registered workers. According to the newspaper Clarín, the sector employs 486,000 qualified workers and represents 7.4% of total national private employment. Although they are often described as “the labor engine of the future” and their development is promising, the sector also has its recessions, particularly in terms of hiring: currently, companies such as Google, Amazon, Facebook and Twitter are going through a time of unprecedented layoffs.
Sofía Cáfaro and Augusto Figueroa are a couple that has been working for years in the universe of information technology (a field known by its English acronym, “IT”). Sofía trained as a Graphic Designer at the University of Buenos Aires and works as a UX designer. user experience), a discipline that he teaches at his same faculty. Broadly speaking, it is the process of defining the experience that a user lives when interacting with a company, its services and its products. Augusto, for his part, is a programmer, as he told us about his professional development in this note.
In all the years they have been in these last millennium professions, one thing is certain: the scenario changes all the time. It is not surprising if – in a world that moves at the pace of computing and was radically transformed since the existence of the Internet – the acceleration of change is the new norm. We spoke with SofÃa and Augusto about the evolution of work in technology.
August Figueroa and Sofa Cáffaro.
How is the demand for workers in the technological field evolving?
Augusto: We come from ten years of a very large technological bubble; There was an injection of money in that area and the pandemic enhanced it. That made it a very attractive area for professional training, which many people did. But that same injection of capital makes many people appear who sell smoke.
¿In what sense»?
Augusto: In artificial intelligence there is a concept called “inner alignment problemâ: When you ask an AI to solve a problem, they interfere with how you download it into language and how the AI interprets that language. The same thing happens in the real world: investors say “I want to multiply my money”, they aim to maximize the number of users, because that is representative of the things that make money. What they generated, however, was not a platform that solves problems for people, and therefore generates value. They only generated a number of users. That’s what I mean by “selling smoke”: to generate value, you have to give people something in exchange for their money (or time, or attention).
How did this impact companies and their work models?
Augusto: Now we are at a time where money is being made there. They are laying off a lot of people, and that has to do with the fact that investors were sold on the idea of unlimited growth, but there came a point where that idea fell apart. For example, They may be able to have 200 million registered users in an application, but without having a way to generate income from them.. That business model prevailed a lot: the idea of attracting a huge number of clients and then seeing how to make money with them. Many companies did it at the same time, perhaps they were five years old and they still don’t know how to generate income, so they go to a loss and investors withdraw their support.
SofÃa: It’s a question of strategy, really. The problem also came from how the idea of the user was conceived. Just because a person downloads an application doesn’t really mean anything. Companies became inflated with projects that were tests and experimentation. Once a startup gets financing, it can survive one or two years. The big problem was that, since the objective did not go beyond generating users, companies gave them things for free. Afterwards, those people were not willing to pay them.
There were many people working on giant projects, employees with high salaries, and when the pandemic eased, all the ones that were not working came to light. A year ago there was a wave of massive layoffs, and it largely goes back to that model. We are now at a plateau in terms of demand for technology workers; While there is work, the hiring process is much more finicky.
What is the solution or strategy on the part of these sectors?
SofÃa: Broadly speaking, that model changed to an opposite strategy: digital products have a price that represents what they are worth and the work that was invested in them. The most important thing is to have few users who pay for it and stay. This is called “retention†. But it is a trend that means there is less job offer.
Augusto: There will always be work in technology, what changes is what it takes to get into it. Before, it may have been enough to just know how to program to get a job, employers were willing to hire people junior that he learned as he went.
When none of what we were doing works, we have to think about how to implement other more elaborate things, for which there are not so many trained people. We went from a market full of people without much real skill or experience in the field, where everyone could go to work earning a lot (unlike all other industries, where you start earning well only once you are deep in the race).
This is a good time for those who were able to take advantage of that stage, develop and gain experience in the field. Those who put something together, tested it in the real world and understand well how their activity works are worth a lot in the labor market today.
In short, is it no longer enough to take a course to start working in the technology sector?
SofÃa: Many of these courses are called «bootcamps» and  they have a big problem: in technology you always work as a team, and most of the time there you learn to work individually. You will never solve a problem alone, it doesn’t make sense. In addition to handling tools, one needs to learn to externalize one’s thoughts well and understand other people.
That’s where the soft skills (communication and social and emotional intelligence to navigate an environment), which are gained in practice. What one learns by doing is very difficult to acquire just by studying (in addition to the fact that many of these courses are asynchronous, very different from the reality of work). In practice, no one does anything the same and no one knows what they are doing, which is precisely what it is about finding out: knowing what the problem is.
Augusto: Exactly, I believe there are three key elements: being clear that there is something to learn, learning it quickly and documenting the process. This is more than anything because every three or two years, the IT world, everything changes, faster and faster. Therefore, the ability to learn is much more relevant than fixed knowledge.
How have the work methods and relationships between different teams in the environment changed?
SofÃa: At this time, it is a priority that there be fluid communication between different teams. For example, many times developers spend a lot of time trying to solve something that later does not provide value, because the problem to be solved for the user was not well established.
In terms of methodologies, this is reflected in two different models. Before, tasks were done in silos, which are professional units (an accounts department, another department of designers, another department of programmers). That meant that all the processes took a long time, because each person worked separately.
Augusto: What happens with that model is that it becomes a slow and bureaucratic system in which communications never arrive when they should. One speaks to the other, who has to speak to the next person and so on. It’s a broken phone; For example, if those who do accounts see that something does not work, they tell the designers, who re-design things and notify the programmers to correct their work.
SofÃa: In addition, it was planned with Gantts, which is a waterfall work scheme where, until one thing is finished, the other team does not start. That, first of all, generates inconsistencies everywhere, because nothing is ever finished. Afterwards, all processes are greatly delayed. That’s why, now problems are worked on multidisciplinary, iterating the products as they progress. Before, you downloaded a program and it stayed the same forever. Now that is obsolete, and they are improved all the time through updates (non-stop). For example, Adobe releases Illustrator 1, 2, 3, 4, 5, etc. If they don’t, the programs die.
Although it has its breaks, it seems to be a sector that grows in the long term. How do you perceive the demand for these skills in the future?
Augusto: I think that, in a certain sense, it is a profession like being a mechanic. They will always be necessary and it is another specialist.
SofÃa: Actually, I would define it as another language. It is the one that allows you to talk to machines. If you, in the future, do not know how to talk to machines, there will be a problem. People who know are going to be worth a lot, which is what is happening now. Today ChatGPT is used by anyone. In a few years, with how technological progress is projected, I think it would be comparable to not knowing English: you are limited by a portion of the world that exists, which is gigantic, and on top of that you cannot see it! People who don’t work in technology have no idea what we’re talking about. It’s another planet, virtual.
Augusto: In fact, I think this is a problem of the present and not of the future. There are very few people who know how to dialogue with machines, very few people who know how to dialogue with technology in general. Even thinking about something as basic as the electricity in your house: knowing how to interact with the light switches, knowing that, if you wanted, you could change it for a dimmer [regulador de intesidad].
To close on the more personal side, what do you learn from each other by working in the same field (IT) but in different aspects?
Augusto: We realized that we complement each other a lot. It makes a lot of sense; We can see at the same time the abstract part of programming and the sensitive part of the user experience. Both have to do with the ability to empathize (to create things for other human beings). She looks at problem solving from one side: what’s wrong with the person and how it translates to a problem definition. Afterwards, I am aware of how the problem translates to the computer.
SofÃa: That’s how it works today, but, in an ideal case, I would have to be sitting with him or his team, and the process would be based less on the transfer of information and translations.
This content was originally published in RED/ACCIÓN and is republished as part of the “Human Journalism†program, an alliance for quality journalism between Rà O NEGRO and RED/ACCIÓN.