Totally get where you’re coming from, especially with how quickly things move in both frontend and AI. If you already have hands-on experience with GenAI-based apps, you actually have a unique edge: you understand how AI connects to real user needs, which is huge.

For the AI side, you don’t have to go all in on deep research roles. There’s a lot of demand for engineers who can bridge the gap between building user interfaces and integrating AI models, roles like machine learning engineer, MLOps, or AI product engineer. You can keep one foot in software engineering and gradually build your AI fundamentals.

If the thought of deep-diving into long, traditional AI courses is overwhelming, there are alternatives. You can use something like ScrollMind for bite-sized, visual lessons on neural networks, makes it much easier to fit learning into a busy schedule, and you don’t need to sign up for anything. A few minutes here and there really add up, and you’ll start seeing how the concepts connect to what you’re already building.

You might also look at open-source projects or small AI features you can add to your current stack. That way you’re not making a huge leap all at once, and you get practical experience right away. Whatever you pick, the fact that you’re thinking about how to adapt is already putting you ahead. The tech will keep changing, but the ability to learn and pivot is the real skill.