The Dark Side of AI Code Generation

Will AI take your coding job? Not if you can test. Kevlin Henney on why most developers will just create legacy code faster and how to be the exception. "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. 00:00:00 Introduction 00:06:15 The Future of Software Engineering 00:12:33 Insights on AI's Impact 00:18:49 The Role of Developers in 2034 00:24:55 Preparing for the new Software Dev Landscape 📘 Free e-book: The 7 success factors of software testing. 25 years of project experience in one 33-page workbook, now also in English 👉 https://tul.fm/ebook 🎯 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. 🔗 Links Blog Post for Episode: https://www.richard-seidl.com/en/podc... 🎙️ More from Richard Seidl Website: https://www.richard-seidl.com Linkedin:   / richardseidl   Podcast Software Testing: https://www.testing-unleashed.fm #softwaretesting #QA #futureofsoftwareengineering