Programming LanguagesConference50min
The Perfect Programming Language for the AI Era: How Should It Look?
The talk explores what an ideal programming language for the AI era might look like. It examines how expressiveness, safety, and performance shape human–AI collaboration, compares modern languages like Rust and Python, and discusses trade‑offs between cost, correctness, and extensibility in next‑generation language design.
talk.summaryAiDisclaimer
Vlad DyachenkoRealtyCalendar
talkDetail.whenAndWhere
Friday, June 19, 14:45-15:35
Room 4B
talks.roomOccupancytalks.noOccupancyInfo
Briefly speaking, let’s look at the current landscape of programming languages and imagine what a next-generation language designed for both humans and machines would look like.
The software development landscape is undergoing a seismic shift. Three years after ChatGPT’s debut, AI coding assistants have moved from novelty to necessity. But here’s the paradox: while AI can write code in any language, the choice of language dramatically affects the quality, cost, and reliability of AI-generated code. This talk raises a fundamental question: What characteristics define the perfect programming language for the AI era?
In this talk, we’ll explore the evolution of programming languages in the age of AI: how expressiveness, safety, and performance converge to form a new paradigm of communication between humans and intelligent systems. We’ll compare modern statically and dynamically typed languages such as Rust, Python, Go, and Ruby, and draw lessons from their strengths and limitations. We’ll discuss the economics of “cheap tokens” versus “expensive correctness,” how compilers become feedback systems for agents, and why traits, macros, and extensibility matter more than ever.
The software development landscape is undergoing a seismic shift. Three years after ChatGPT’s debut, AI coding assistants have moved from novelty to necessity. But here’s the paradox: while AI can write code in any language, the choice of language dramatically affects the quality, cost, and reliability of AI-generated code. This talk raises a fundamental question: What characteristics define the perfect programming language for the AI era?
In this talk, we’ll explore the evolution of programming languages in the age of AI: how expressiveness, safety, and performance converge to form a new paradigm of communication between humans and intelligent systems. We’ll compare modern statically and dynamically typed languages such as Rust, Python, Go, and Ruby, and draw lessons from their strengths and limitations. We’ll discuss the economics of “cheap tokens” versus “expensive correctness,” how compilers become feedback systems for agents, and why traits, macros, and extensibility matter more than ever.
Vlad Dyachenko
Solutions Architect / OSS Contributor
Vlad is a seasoned full-stack developer with over a decade of experience building and maintaining scalable B2B platforms, as well as a dedicated open-source contributor. He currently works at RealtyCalendar as a staff engineer, focusing on production reliability, systems design, and cross-functional engineering using languages like Ruby, Golang, and Rust. He enjoys working at the intersection of infrastructure, developer experience, and open-source tooling.
He is a member of the Diesel.rs contributor team and the creator of opencryptolist.xyz, a platform dedicated to fostering open-source contributions in the blockchain industry. Vlad has open-sourced, maintained, and contributed to several libraries in the Ruby and Rust ecosystems (including finance-rb, solscan-mcp, and visual-cryptography).
Vlad is a seasoned full-stack developer with over a decade of experience building and maintaining scalable B2B platforms, as well as a dedicated open-source contributor. He currently works at RealtyCalendar as a staff engineer, focusing on production reliability, systems design, and cross-functional engineering using languages like Ruby, Golang, and Rust. He enjoys working at the intersection of infrastructure, developer experience, and open-source tooling.
He is a member of the Diesel.rs contributor team and the creator of opencryptolist.xyz, a platform dedicated to fostering open-source contributions in the blockchain industry. Vlad has open-sourced, maintained, and contributed to several libraries in the Ruby and Rust ecosystems (including finance-rb, solscan-mcp, and visual-cryptography).