AI BriefingWhat Remains for Humans When AI Compresses Expertise
Key point
The experience of borrowing expertise through AI to build a DSL compiler, which eventually led to publishing an arXiv paper.
Details
As a front-end developer with 8 years of experience building various SaaS products, I came to feel that even though the surface differs from domain to domain, the internal structure tends to repeat.
Starting from that intuition, I designed a DSL compiler, and in the process, I used AI not just as a simple coding assistant but as a tool for borrowing the way experts in each field think.
Thanks to the dramatically lowered cost of failure, I was able to keep pushing the project forward even after overhauling the architecture four times, which ultimately led to publishing an arXiv paper.
At the same time, there was a core part that remained no matter how much AI filled in.
- The sense of checking for yourself what you are actually asking
- The intuition to notice when your current approach is framing the problem itself incorrectly
- The human judgment of choosing a direction among multiple possibilities
The central point of the piece is the felt sense that while AI compresses expertise and dramatically increases speed, the last 20% still belongs to humans.
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