AI will continue to reshape how we code and design products, while flexible technologies like foldable phones become mainstream. This evolution will demand new human skills in oversight, optimization, and choosing the right tools.
At WondTech, we see the tech landscape moving towards a more complex blend of artificial capabilities and the human touch. Recent news has shown that AI is already capable of building foundational elements, like WordPress themes, which is truly exciting for aspiring and non-specialist developers. Anyone with an idea can now start building it much faster. However, it's crucial to remember that these tools, as we've seen, still leave behind some 'hidden bugs,' especially concerning performance. This means that the role of human developers won't disappear; it will transform. Instead of starting from scratch every time, developers will become more like quality engineers, optimizers, and auditors. Their task will be to refine AI-generated code, ensuring its efficiency and security. The ability to identify and fix issues that AI might miss will be a critical skill. Simultaneously, we're witnessing significant advancements in hardware. Reports of Samsung Display beginning OLED panel production for major devices like iPhones indicate that this technology is no longer just an experiment. Foldable devices are poised to become a common feature, opening new horizons for product design and user experience. Expect to see more major players embrace this trend in phones, and perhaps even in tablets and laptops, pushing the boundaries of what our devices can do. With the increasing use of AI in programming, the question of 'which AI model is best?' becomes even more paramount. It's no longer just about whether AI can write code, but about selecting the right tool for the specific task. Developers will need to understand the strengths and weaknesses of different models and how to deploy them effectively. The skill of 'right model selection' will be vital, requiring engineers to not only understand programming but also how to intelligently guide AI to achieve optimal results. In the future, the advantage won't be with those who write code the fastest, but with those who can most effectively direct AI to produce high-quality, high-performance code.
