The Leftover Hard Parts
Some time ago, I asked an AI to write a fairly boring piece of code. It did a pretty good job. I changed a few things, ran the tests, and voila: I was looking at something that probably would have taken me most of the morning to write myself. This is the most exciting part of AI-assisted development for me: from idea to code in less than an hour. I felt great. Then a user hit a bug. They came…
The article discusses the challenges of using AI-assisted development in coding. The author reflects on how AI can quickly generate code that appears nearly complete, but hidden within is a "leftover hard part" that requires additional thought and consideration. This is the process of deciding what the product should do in unexpected situations, determining whether deviations are bugs or features, and setting user expectations.
The author notes that when AI-generated code isn't perfect, there's a need to understand and investigate the remaining 10% that wasn't accounted for. This can be difficult as the AI creates plausible code, making it harder to spot issues. The author mentions the satisfaction of traditional development loops - writing code, running it, fixing bugs, and iterating. However, AI removes this iterative feedback loop, requiring developers to spend more time inspecting and understanding large chunks of generated code.
Ultimately, the author argues that while AI can help write code faster, it doesn't eliminate the need for developers. Instead, it shifts the balance, making responsibility for the outcome even more crucial. Developers still need to understand the problem, make trade-offs, decide what not to build, and communicate decisions. The author suggests that as AI takes over more coding tasks, developers will increasingly focus on these higher-level responsibilities.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
