AI researcher Chip Huyen provides crucial guidance for software engineers to remain competitive in an AI-driven tech landscape by 2025. She emphasizes that while AI won’t replace software engineers entirely, it will significantly transform their roles and required skill sets. Huyen advises engineers to focus on three key areas: understanding AI capabilities and limitations, developing expertise in AI operations (MLOps), and maintaining strong software engineering fundamentals. She stresses the importance of being able to evaluate AI models’ effectiveness and understanding when to implement AI solutions versus traditional programming approaches. The researcher particularly highlights the growing significance of MLOps skills, as companies increasingly need engineers who can deploy and maintain AI systems in production environments. Huyen warns against the common misconception that all engineers need to become AI researchers or experts in machine learning theory. Instead, she advocates for practical knowledge that enables engineers to effectively integrate AI tools into existing systems and workflows. The article concludes with Huyen’s observation that the most valuable engineers will be those who can bridge the gap between traditional software development and AI implementation, suggesting that upskilling should focus on practical applications rather than theoretical knowledge.