The cost of writing code has plummeted thanks to AI coding agents, fundamentally disrupting decades of software engineering practices. Simon Willison argues that while producing code has become nearly free, delivering quality software remains expensive and complex. This shift challenges core assumptions about development trade-offs.

Traditional software engineering built habits around expensive coding time - extensive planning, careful feature prioritization, and constant micro-decisions about refactoring or testing. Developers routinely weighed whether tasks justified their time investment. Now, coding agents can generate hundreds of lines of code in minutes, forcing engineers to reconsider what's worth building. The ability to run parallel agents simultaneously amplifies this disruption, enabling one developer to implement, refactor, and document across multiple codebases at once.

Despite cheaper code generation, good code still demands substantial effort. Quality software requires working functionality, comprehensive testing, proper documentation, graceful error handling, and maintainability considerations. While AI tools assist with many aspects, developers must still ensure the final product meets quality standards. The industry now faces the challenge of developing new habits that leverage these capabilities while maintaining software excellence.