Grabbing pre-built automation templates feels like an instant win, but actually adapting them to your real daily workflow is where things usually break down. You import the scenario or agent, but the moment you need to plug in your own custom data, error handling, or specific apps, the setup grinds to a halt. It’s rarely an issue of finding workflows to copy, but the friction of getting them to run reliably on your own projects. What usually breaks first when you try moving an AI automation template into your actual routine?

Hello. I am Aaron, and I lead a five-person team based in the Philippines. We have historically generated revenue by securing projects from clients and agencies in the U.S., Latin America, and Europe through platforms such as Upwork, Freelancer, and Toptal. However, as you are likely aware, the rise of AI agents and the spread of corporate automation have caused many developers to lose their jobs and flood the freelance market, thereby shrinking the space available for us to operate. Consequently, our revenue has not only gradually declined over the past few years but has also become significantly more volatile. Furthermore, the income levels of Asian developers remain substantially lower than those of their counterparts in the U.S., Latin America, and Europe. Additionally, as the pool of freelance talent from Europe, the U.S., and Latin America has expanded, the number of companies and clients seeking Asian developers has noticeably decreased. While we could manage this disparity in the past when work was plentiful, the current situation is vastly different. Recognizing that our existing methods can no longer guarantee stable, long-term income, I am currently exploring two new strategies. One strategy involves shifting our focus toward AI specialization, while the other entails expanding our operational regions to high-revenue markets such as the U.S., Latin America, and Europe. However, we currently lack the necessary capabilities to execute either of these plans effectively. Although we intend to pivot to AI, we have yet to secure the right experts for the transition. While our team possesses strong technical skills in AI automation, we lack extensive experience in specialized areas like advanced AI/LM (Large Language Models). We see a significant opportunity to generate high revenue by leveraging the rise of AI training platforms(Mercor, AfterQuery, DataAnnotation, Outlier, Turing, Snorkel ); however, we are hindered by a lack of developers with backgrounds in relevant natural sciences and by geographical limitations.