My Experience at Platzi Conf Bogotá 2026

Last August 29th, I attended my second Platzi Conf. It was such an amazing experience because it is one of the biggest tech conferences in Latin America and seeing speakers in person was incredible. I have learned so much from them and being part of the conference made me feel like I belonged to something important. However, the most important thing for me was hearing from experts perspectives on where technology is heading.

There were a lot of interesting talks, but these were the ones that I wanted to attend:

• How GPUs Are Accelerating Science By Katrina Riehl - NVIDIA
• What does it mean to be a developer today? By Ana Cunha - AWS
• Why AI Makes You Think More About Engineering By Javier Guignard - Platzi

In this blog, I want to share with you my experience and what I learned from these talks. I also want to encourage you to attend future editions or other tech conferences. I believe attending these kind of events can help you understand how really technology is heading.

How GPUs Are Accelerating Science By Katrina Riehl - NVIDIA

Many things we use every day, have hidden actors that we don’t usually see, and one of them is software. When you think about new scientific discoveries, you might imagine a person in a white coat looking through a microscope. However behind that, there is software controlling instruments, running simulations, analyzing data and creating visualizations. Modern science is not only using software; it is built on software. This was one of the ideas that caught my attention during this talk.

A lot of the software used in science is part of the open-source ecosystem. Python, for example, has become one the main languages used in scientific computing, with projects such as NumPy, SciPy and many others libraries built and maintained by communities. Open-source projects are helping scientists take advantage of GPUs as result as getting better performance improvements without changing the way they work.

My biggest takeaway from the talk was that open source is not only about making your code public. An open ecosystem also needs documentation, testing, bug fixes, infrastructure, governance, maintenance, and people helping the community. A sentence from the talk stuck in my head: “Make the ecosystem a little stronger than you found it”. For me, this wraps up the importance of open source very well. We use open source software almost every day as developers, and contributing something back, like documentation, test, bug report, can help the ecosystem better for everyone.

What does it mean to be a developer today? By Ana Cunha - AWS

Will AI replace me as a developer? Maybe, if we don’t change.

Programming has constantly evolved since its beginnings. In the 1950s, assembly programming required developers to understand machine-level instructions even for simple tasks. Later, compilers and higher-level programming languages made programming easier. Then came structured programming, object-oriented programming, microservices, cloud computing, and now AI. Developers have always had to adapt to new tools and new ways of building software.

Today, AI gives us the opportunity to expand our knowledge beyond our main specialization. This connects with the idea of being a T-shaped developer: having deep knowledge in one area while also understanding other areas around it. For example, a backend developer can use AI to explore frontend development, not only to generate code but also to ask questions and understand how it works.

However, my biggest takeaway was ownership. AI can write code, but the work still belongs to you, not to the tool. You are the one who decides what to build and why. AI can generate code much faster than we can review it, which makes understanding what we generate even more important. Don’t put into production something that you don’t understand.

For me, being a developer in the AI era doesn’t mean knowing how to generate more code. It means being curious, understanding what we are building, learning beyond your specialization, and taking responsibility for the result.

Why AI Makes You Think More About Engineering By Javier Guignard - Platzi

AI agents are changing the way we build software, but writing code faster doesn’t necessarily mean that we are building better software. One of my biggest takeaways from this talk was the importance of understanding the system and its dependencies before starting to code with AI agents.

Javier shared an interesting example from Platzi. Over the years, parts of the platform had been separated into different microservices and repositories. This architecture created a problem for AI agents: to understand a single domain, an agent might need to read multiple repositories and understand dependencies between different services and databases. More context means more tokens, more time,more complexity and more money.

Platzi decided to simplify parts of its architecture, even moving some services back into the monolithic when those services were strongly related and always scaled together. This doesn’t mean that microservices are bad. Some services still need to be independent because their domains or scaling requirements are different. For me, the important lesson was that architecture should have a reason behind it.

This connects again with ownership. Before asking an AI agent to modify a system, we need to understand its architecture, dependencies, and business context. AI can help us write the implementation, but as engineers, we still need to understand the impact of those changes.

This is me! 😄 Enjoying this amazing conference. Thank you Platzi for having me here. Happy coding! 😄