A Google insider has recently drawn attention across the technology community by urging aspiring AI product managers to “be like crabs.” While the phrase may sound unusual at first, it carries a deeper message about adaptability, lateral growth, and long-term success in the fast-changing field of artificial intelligence.
The advice was shared during an industry discussion focused on careers in AI product management. According to the Google professional, traditional career paths that emphasize linear, upward movement are becoming less effective in AI-driven environments. Instead, professionals should embrace sideways exploration—much like the movement of crabs—to build a broader skill set and stronger problem-solving abilities.
AI product management is a uniquely complex role. It requires an understanding of machine learning models, data pipelines, user experience, business strategy, and ethical considerations. Product managers who limit themselves to one discipline may struggle to lead effectively. By moving laterally across functions such as engineering, design, analytics, or operations, professionals can gain valuable insights that strengthen their leadership capabilities.
The demand for skilled AI product managers continues to rise as companies integrate artificial intelligence into everyday products and services. From recommendation engines and voice assistants to predictive analytics and automation tools, AI products require constant refinement. Professionals who adapt quickly and understand multiple aspects of product development are better positioned to succeed. These evolving industry expectations are often discussed in global technology insights, where experts analyze how major tech firms develop and scale AI solutions.
The “be like crabs” mindset also highlights resilience. Crabs are known for adjusting their direction rather than forcing a single path forward. Similarly, AI professionals face frequent changes in tools, frameworks, and regulations. Being willing to pivot—whether by learning new technologies or taking on cross-functional roles—can help individuals stay relevant in an unpredictable industry.
Google’s internal culture has long supported cross-team collaboration and continuous learning. Many successful AI leaders within the company did not begin their careers in product management. Some started in marketing, research, customer support, or finance before transitioning into AI-focused roles. These lateral experiences allowed them to understand user needs, business goals, and operational challenges more deeply.
This approach is especially important as AI increasingly intersects with finance and digital commerce. AI-powered systems are now used for fraud detection, credit risk assessment, personalized financial services, and automated decision-making. Product managers working in these areas must understand both technical and financial ecosystems. Insights into this convergence are commonly explored in financial technology innovation news, where analysts highlight how AI is transforming the fintech landscape.
For aspiring AI product managers, the message is clear: focus on skill development rather than titles alone. Learning how to collaborate with engineers, communicate with stakeholders, analyze data, and consider ethical implications will provide long-term value. Sideways career moves may not always feel like progress, but they often build the foundation needed for future leadership roles.
The advice also challenges traditional definitions of success. In fast-moving industries like artificial intelligence, rigid career ladders are giving way to flexible, experience-driven growth. Professionals who embrace curiosity, adaptability, and continuous learning are more likely to thrive.
As artificial intelligence continues to reshape industries worldwide, guidance from experienced insiders offers valuable perspective. The call to “be like crabs” is not about avoiding ambition—it’s about recognizing that growth can happen in many directions. For those aiming to build impactful careers in AI product management, lateral movement may be the smartest strategy of all.
