First, embrace the AI tools rather than avoid them. As Valdarrama advises, “learn as much as possible about AI and how to use it to write better code.” The developers who pair their JavaScript or mobile framework skills with prompt-engineering savvy will outpace those who stick strictly to manual coding. In practical terms, this could mean using Copilot during development, integrating an LLM into your editor for quick fixes or leveraging AI to generate initial UI drafts that you then refine.
Second, focus on the fundamentals that AI can’t automate. This includes your understanding of user experience design, accessibility, performance tuning, and architectural principles. AI might generate a navigation menu for you, but you decide if that navigation delivers a good UX or if it meets your site’s performance budget. Strengthening your design collaboration skills is also key. Front-end devs who can speak the language of designers (and even use AI design tools) will be highly valuable in bridging the gap between vision and reality. We’re already seeing front-end development job postings evolve from “front-end developer” to “front-end architect.” Embrace this shift.
Third, develop your “critical eye” for AI output. Treat every AI suggestion as a starting point, not an absolute. If you’re a newer developer, this means you can’t skip learning proper coding practices, testing, or debugging. In fact, junior devs may need to learn more quickly now: The mundane tasks that used to be a safe training ground (like slicing a PSD into HTML or wiring up a simple form) might be handled by AI, so you’ll be challenged sooner with reviewing and improving AI-generated code. Seek mentorship and code reviews to accelerate your ability to spot mistakes. Take on those gritty tasks of validating and polishing AI code; that’s where you’ll sharpen the skills that AI lacks.
