Alex Ballesté's Blog

A few weeks ago, I started thinking about a software project that I had almost completely forgotten. In 2013, Juanjo Meroño and I built LooWID, an open source video conferencing platform based on WebRTC. Some time later, Edu Rey joined us to help with the UI, giving the project an important qualitative leap in its user experience and making the product feel much more complete. We developed it for several years, adapting it to the rapidly changing browser and WebRTC ecosystem, until around 2018–2019 we eventually stopped maintaining it.The code remained public. The product remained there. But the technology around it moved on. Years later, I wondered what would happen if we tried to bring it back—not by trying to make the old application run again, but by asking AI to help us rebuild the product. The original project is still available on GitHub , and the result of the experiment is LooWID Remastered . From legacy code to a working product I used OpenCode as the main development agent. ...

In a previous article, I wrote about how AI is Changing the Economics of Prototyping . When prototypes become realistic enough to experience an entire system, they also become powerful tools for stakeholder alignment and project discovery. That experience made me think about a part of IT where we spend an enormous amount of time: operations . As an IT director, one of the things I want to explore more systematically is where our teams spend time on operational tasks that are difficult to automate. Not the obvious repetitive tasks that can easily become scripts or workflows, but those tasks that happen once in a while, are difficult to document completely, and require someone with enough experience to understand what is actually going on. A recent Odoo migration was a perfect example. I needed to migrate an Odoo Community installation from version 14 to version 18. I had installed the original system several years ago, but I had very little experience with this kind of migration. The...

From imagining software to experiencing it before it exists For more than two decades, Agile has transformed the way software is built. Its principles emerged in response to a world where requirements evolved continuously, long development cycles created unnecessary risk, and organisations needed mechanisms to learn while delivering value. By breaking work into small, working increments, Agile enabled teams to reduce implementation risk, gather feedback early and continuously refine their products. Prototyping has followed a similar objective. Long before generative AI, paper sketches, wireframes, clickable mock-ups and interface design tools were widely used to explore ideas, capture requirements and help stakeholders understand a problem before committing to implementation. These techniques have always been valuable because they encourage discussion at a stage where change is still inexpensive. The limitation was never the concept of prototyping itself. It was the cost of realism. B...