Conor Hoekstra, expert in programming languages, discusses the sustained success of programming languages, the rarity of big tech companies adopting new languages, the evolution of programming from ones and zeros to prompt engineering, challenges of using AI editing services, the future of programming and job opportunities, a comparison of Python, Rust, and C++, and exploring the benefits and annoyances of co-pilot in programming.
The evolution of programming languages in the C++ space may impact its popularity and long-term prospects, drawing parallels to the decline of COBOL.
Languages with extensive libraries and easy-to-use tools, like Python, have a competitive edge in driving language adoption.
LLMs have the potential to facilitate language switching and quick code porting, saving time by generating code in different languages and enabling real-time code review during pair programming sessions.
Deep dives
The future of programming languages
The conversation explores the potential successors or competitors to C++ for hardware and GPU programming, as well as the changes in programming languages over time. They discuss how large language models like GPT can be used in programming today and speculate on the future of programming.
The challenge of sustaining programming languages
The podcast episode raises concerns about the sustained success of programming languages like C++. While acknowledging that C++ will still be around in the future, they discuss how the evolution of languages in the C++ space may impact its popularity and long-term prospects, drawing parallels to the decline of COBOL.
The importance of ecosystems and tooling
The conversation highlights the significance of ecosystems and tooling in driving language adoption. They emphasize that languages with extensive libraries and easy-to-use tools, like Python, have a competitive edge. They also discuss the potential impact of plugin ecosystems and code generation plugins in simplifying programming tasks and increasing productivity.
The current state of AI-assisted programming
The conversation touches on AI-assisted programming tools, including GPT-based models like ChatGPT. While acknowledging their limitations and occasional inaccuracies, they recognize the value of these tools in increasing productivity and providing assistance in certain programming tasks, though they note that higher reliability systems are still essential for critical applications.
Benefits of Using Rust over C++
The podcaster discusses the decision to use Rust over C++ for a personal project. Despite being less familiar with Rust, the speaker found it more enjoyable to target Rust for code generation. Additionally, the podcaster highlights the advantages of using a statically typed language like Rust for models such as LLMs due to the greater compile-time guarantees and less error-prone code compared to C++.
The Power of Dynamic Typing and Language Switching
The episode explores the benefits of dynamic typing in languages like Python, which allow faster programming without the need to fight with a static type system. The podcaster emphasizes the importance of speed and flexibility when exploring and experimenting with code. Furthermore, the conversation delves into the potential of LLMs to facilitate language switching and quick code porting, saving time by generating code in different languages and even enabling real-time code review during pair programming sessions.
