Building vs Digging (bgthread.github.io)

The article "Building vs Digging" explores the shifting landscape of software engineering in the age of AI, particularly with the rise of large language models (LLMs) that simplify coding tasks. Historically, engineers derived fulfillment from both "building" software and "digging" into complex code to solve problems. This dual engagement fostered a sense of accomplishment and cognitive development. However, the accessibility of LLMs has led to a passive approach to coding that undermines this effort-reward cycle, potentially leaving engineers, especially those who specialized in digging, feeling obsolete. For the AI/ML community, this presents significant implications regarding the relationship between identity and skill. As LLMs take over straightforward tasks, engineers face an identity crisis, where those defined by their debugging prowess may struggle to find value in an environment where their unique contributions become commoditized. The article emphasizes the importance of maintaining a balance between building and digging, suggesting that engineers who can adapt to the tools offered by LLMs while retaining their depth of knowledge will be better positioned for success. The challenge lies in redefining fulfillment in a field where traditional skill sets are being reshaped by AI advancements.