Software Testing Unleashed - QA, DevEx & Quality Engineering

Still Coding or Just Prompting? Software Engineering 2034 - Kevlin Henney

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"The world runs on software; that is not going anywhere." - Kevlin Henney

In this episode, I talk with Kevlin Henney, author and speaker, about what software engineering will actually look like in 2034. Kevlin challenges the hype around AI code generation testing and explains why most developers using generative AI are actually removing the fun parts of their job while creating legacy code faster. We explore why programming languages won't change as radically as people think, why your testing skills will become your most valuable asset, and what recent data already shows about declining code quality on GitHub.

Kevlin Henney is an independent consultant, speaker, writer and trainer who has contributed to the current development of programming techniques, software architecture and unit testing. He has been a columnist for numerous magazines and websites and has served on many committees. He is also co-author of "A Pattern Language for Distributed Computing" and "On Patterns and Pattern Languages" from the "Pattern-Oriented Software Architecture" series, as well as editor of "97 Things Every Programmer Should Know" and co-editor of "97 Things Every Java Programmer Should Know".

Highlights:

  • Developers who rely on generative AI to produce code without understanding it become maintenance programmers, stripped of the creative work they find meaningful.
  • Programming language turnover is slower than the industry assumes: every top-five language in active use was invented in the 20th century, and no language from the 2020s appears in the top 20.
  • Code quality on GitHub was already declining by early 2024, with rising code churn and more duplicate code directly traceable to AI-generated output.
  • The skills that differentiate developers in an AI-driven environment are precision, testing, and the ability to ask what software should actually do, not familiarity with any particular tool.
  • Natural language programming does not remove the need for software expertise: most spreadsheets, built by non-developers, are unmaintainable, incomprehensible, and buggy, which is the predictable result of imprecise specification.
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    Software Testing Unleashed - QA, DevEx & Quality EngineeringBy Richard Seidl | Software Development & Testing Expert