This article examines how traditional code reviews often miss critical bugs that lead to significant production failures, highlighting a $2.1 million loss caused by a simple validation error. It discusses the inefficiencies of the process, the high costs involved, and the increasing role of AI in optimizing code review tasks.

The article explores how advancements in AI coding tools will reshape software engineering in 2026. It highlights shifts in infrastructure, testing practices, and the importance of human oversight as LLMs generate code. The author raises questions about the evolving roles of engineers and the implications for project estimates and build vs. buy decisions.

The article stresses the importance of software engineers providing code that they have manually and automatically tested before submission. It emphasizes accountability in code reviews and the use of coding agents to assist in proving code functionality. Developers should include evidence of their tests to respect their colleagues' time and efforts.