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description: Kevlin Henney's YOW! 2025 talk surveys the past, present, and future of programming languages. Key observations: mainstream language rankings (TIOBE, RedMonk,...
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# The Past, Present & Future of Programming Languages • Kevlin Henney • YOW! 2025

**[GOTO Conferences](https://daily.dev/sources/goto)** · 51 min read · 1 upvotes · 0 comments

## Summary

Kevlin Henney's YOW! 2025 talk surveys the past, present, and future of programming languages. Key observations: mainstream language rankings (TIOBE, RedMonk, IEEE Spectrum) have been remarkably stable for years, dominated by languages invented in the 20th century. Most foundational programming concepts — coroutines, iterators, if-then-else, for loops, channels — trace back to the 1950s–1970s. Go is framed as 'the perfect 1970s language,' and Rust is described as 'so last decade.' The rate of mainstream language change has slowed further because LLMs are now consumers of programming languages, and AI coding ability is proportional to training data — disadvantaging new languages. Betteridge's law is invoked to dismiss the idea that AI will end top programming languages.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=nNWROjHZzuU>

## Questions this post answers

### Why do popularity rankings like TIOBE and RedMonk show mostly older programming languages dominating the top spots?

Programming language adoption changes far more slowly than most software trends because mainstream codebases, job markets, and tooling accumulate over decades, creating strong inertia. Rankings from TIOBE, RedMonk, and IEEE Spectrum all show a heavy skew toward 20th-century languages like Python, Java, C++, and JavaScript, with genuinely new languages confined to a long tail rather than displacing incumbents quickly.

_daily.dev helps developers weighing a new language against an entrenched stack track how adoption trends actually move._

### How does AI code generation affect which programming languages become popular?

AI coding assistants are becoming consumers of programming languages, not just information sources, and they default to languages they have seen the most training data for, such as Python, JavaScript, and TypeScript. As Anders Hejlsberg, creator of TypeScript, C#, and Turbo Pascal, has noted, an AI's ability to write code in a language is proportional to how much of that language it has been exposed to, which disadvantages new languages and further entrenches existing mainstream ones.

_developers deciding whether AI tooling favors their language choice can follow this reasoning on daily.dev._

### Where did the if-then-else construct in programming languages originally come from?

The else keyword traces back to Klaus Samelson, who introduced it into ALGOL 60 in the early 1960s, building on earlier work by figures like Grace Hopper (who used 'otherwise' in Flow-Matic) and John McCarthy (who also used 'otherwise' in early Lisp control structures). Before this, languages typically used guard-style conditionals without a true compound if-then-else structure.

_anyone curious about the origins of everyday language syntax can dig into programming history on daily.dev._

---

Tags: [#ai](https://daily.dev/tags/ai), [#functional-programming](https://daily.dev/tags/functional-programming)

[View this post on daily.dev](https://daily.dev/posts/the-past-present-future-of-programming-languages-kevlin-henney-yow-2025-qhpx30x89)

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