ai

Software developers face a constant challenge: the communication gap between them and customers. TLDR: customers will never speak the developers’ language. While both parties strive for the same goal—creating valuable, functional software—their perspectives, priorities, and vocabularies often differ. In this post, we’ll dive into the reasons for this difference, explore the implications, and discuss strategies for bridging the gap.

Previously in the series, we saw that AI tools have limitations. We also discussed maximizing our productivity by using them to write code - without shooting ourselves in our legs.

In this post, we’ll cover one more piece of the puzzle: how they can (or can’t) help us to refactor.

In the previous post, we saw the limitations of AI developer tools. Yes, they are not perfect. However, they are still able to improve our productivity significantly.

This time, we’ll dive into how we can effectively use them to achieve a better development experience, higher-quality output, and faster delivery.

With the rise of ChatGPT, Bard Gemini, GitHub Copilot, Devin, and other AI tools¹, developers started to fear that AI tooling would replace them. Even though their capabilities are indeed impressive, I don’t fear our jobs will go away in 2024.