Ai Coding

In the rapidly evolving landscape of AI-assisted software engineering, we routinely fall into the “specs-to-code” cycle: a frustrating endless cycle of prompt engineering, trying to perfect instructions rather than engaging with the messy, architectural reality of our thoughts and of our projects. The reality is that the specs-to-code approach currently doesn’t work very effectively. LLM’s lack the contextual knowledge, but until the technology evolves, we must find more deliberate ways to work with LLMs. ...

Today I watched an incredible Google I/O presentation by Adam Bender titled “Software Engineering at the Tipping Point.” It perfectly articulated something I’ve been thinking about a lot: as AI automates the “how” of writing code, our jobs are rapidly shifting toward the “why.” For decades, as software engineers, we have poured our values, our ethos, and our intentions into products through our code. We used our techne—our technical craft—to express what we valued. We valued mastery over specific languages like Kotlin or framework architectures. ...