Abstract: It’s kind of difficult to distinguish if this is another marketing-created buzzword in the software development world, and even worse because it appears in many flavors: “low code”, “no code”, “codeless”, “scriptless”, and probably I’m missing some. If you try to find some objective opinion it’s hard to find any article or talk that is not provided by a vendor. In this talk I want to give my perspective and experience, analyzing when it makes sense, in which contexts, and most importantly, which considerations we should have to take into account to avoid the “automating chaos brings faster chaos”. Also, how does this ML and AI really help to your testing goals? I’ve been researching about the different low code solutions for test automation. My team has been using some of them in different contexts. We’ve seen that, if correctly used, is an interesting approach, especially now that it’s being harder to find people with coding skills to work on test automation. If you join me in this conversation you will learn about: - some bad practices that can lead to useless results, so you want to avoid, related to how these tools work with selectors, modularization, etc. - some practices that’s been useful for us, to get the results we expected and even faster, like how to structure the team and distribute responsibilities, how to integrate them in your ci-pipelines, etc. - and also how we’ve been using some of these tools to help our team members to grow, defining a new career path for test engineers, that in other ways wouldn’t have been possible or would have taken much longer.