Talking to machines

Creating a new programming language is an intricate and costly task with potential adoption challenges. However, there are instances when the current language fails to succinctly convey our intentions, leading to excess and unnecessary code.

For instance, consider the transformation from pure JavaScript to JSX in defining React components:

Pure JavaScript:

JSX:

Programming languages have evolved significantly over time. From being rooted in machine operations, modern languages are now designed with human usability at the forefront. Parallel to this, Domain Specific Languages (DSLs) are rising. While these are narrower in scope and cater to specific use cases, they promise enhanced efficiency and clarity in their domains, like how JSX revolutionized React coding. However, the journey of developing these DSLs has its challenges, predominantly the initial costs and adoption barriers.

With the emergence of Language Learning Models (LLMs), there's potential for change. While LLMs haven't yet impacted the creation of DSLs, their promise could make developing and adopting such languages more straightforward and cost-effective in the future.

As we witness the rise of LLMs and English as the new hot coding language, we are on the cusp of a new era in our dialogue with machines. And with digital creation becoming ever more accessible, how we express our intent to these machines will likely undergo a transformation.

How will we talk to machines?