The Silent Death of Good Code: How AI Agents Are Reshaping Software Development

In a reflective blog post, software engineer Amit Prasad mourns what he calls "the silent death of Good Code" in an era increasingly dominated by AI coding agents. His observations offer a nuanced look at how the craft of software development is evolving in the face of automation.

What Makes Code "Good"?

Prasad defines "Good Code™" as code that is easy to read and understand, pleasing to develop with and maintain, exists for a specific reason without excess, and represents a rare combination of talent, experience, passion, and time investment that may not immediately benefit the business. He emphasizes that this type of code is increasingly rare in modern development.

A Tale of Two Rewrites

The post centers on a concrete example from Prasad's work at Modal, where a colleague rewrote an external system that integrated with the Linux kernel. The initial rewrite involved translating C code to Rust in preparation for custom feature work. While the resulting code wasn't bad or un-idiomatic, it failed to meet the standard of "Good Code" - it was hard to read, difficult to extend, and unclear why the rewrite was necessary in the first place.

Crucially, this initial rewrite relied heavily on coding agents. The colleague then invested time to understand the kernel subsystem and the reasoning behind the original C implementation, rewriting the Rust version himself. The difference was dramatic: the code flowed naturally, explained itself and the underlying subsystems, and may have even surpassed the original C implementation in quality.

The Productivity Paradox

Prasad acknowledges that AI agents have made him "definitely far more productive" in his day-to-day work. However, he notes that the code these agents produce is merely "acceptable" - it gets the job done and passes tests, but lacks the craftsmanship of truly good code. This creates a tension between productivity gains and code quality that many developers are grappling with.

A Broader Pattern

The author draws parallels to other fields where craftsmanship has evolved or diminished over time. He suggests that passionate practitioners of "Good Assembly" or "Good Circuits" may have seen their passions fade as their fields evolved. However, he views the change in software engineering as uniquely sudden, making the transition more jarring for those who value code craftsmanship.

The Future of Software Development

Prasad's post raises fundamental questions about the future of software development. As AI agents become more capable at generating functional code, will the emphasis on code quality and craftsmanship continue to diminish? Is the ability to write "Good Code" becoming an obsolete skill, much like hand-optimizing assembly code became less relevant as compilers improved?

The post doesn't offer easy answers, but it does highlight an important shift in the software development landscape. The tension between productivity and craftsmanship, between "acceptable" code and "Good Code," represents a fundamental challenge for the industry as it adapts to AI-assisted development.

For developers who have built careers on writing elegant, maintainable code, this transition may feel like a loss of something valuable. Yet for organizations focused on delivering working software quickly, the productivity gains from AI agents may outweigh concerns about code quality. The challenge will be finding ways to preserve the benefits of craftsmanship while embracing the efficiency gains that AI tools provide.

The silent death of Good Code may be inevitable, but understanding what we're losing in the process is essential for making informed decisions about how we develop software in the AI era.